US20030033088A1 - Method of generating chemical compounds having desired properties - Google Patents
Method of generating chemical compounds having desired properties Download PDFInfo
- Publication number
- US20030033088A1 US20030033088A1 US10/188,801 US18880102A US2003033088A1 US 20030033088 A1 US20030033088 A1 US 20030033088A1 US 18880102 A US18880102 A US 18880102A US 2003033088 A1 US2003033088 A1 US 2003033088A1
- Authority
- US
- United States
- Prior art keywords
- compounds
- chemical
- activity
- synthesis
- data
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Abandoned
Links
- 0 NC(Cc1ccccc1)C(N(CCC1)[C@]1C(NC(CCC*C(N)=N)C(O)=O)=O)=O Chemical compound NC(Cc1ccccc1)C(N(CCC1)[C@]1C(NC(CCC*C(N)=N)C(O)=O)=O)=O 0.000 description 1
- KZPHUKKNYYFTQO-NYHXXUGCSA-N O=C(C1CCCC1)[C@H](CCC1)N1C(/C=C1/C=CC1)=O Chemical compound O=C(C1CCCC1)[C@H](CCC1)N1C(/C=C1/C=CC1)=O KZPHUKKNYYFTQO-NYHXXUGCSA-N 0.000 description 1
Images
Classifications
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J19/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J19/0046—Sequential or parallel reactions, e.g. for the synthesis of polypeptides or polynucleotides; Apparatus and devices for combinatorial chemistry or for making molecular arrays
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61P—SPECIFIC THERAPEUTIC ACTIVITY OF CHEMICAL COMPOUNDS OR MEDICINAL PREPARATIONS
- A61P7/00—Drugs for disorders of the blood or the extracellular fluid
- A61P7/02—Antithrombotic agents; Anticoagulants; Platelet aggregation inhibitors
-
- C—CHEMISTRY; METALLURGY
- C07—ORGANIC CHEMISTRY
- C07K—PEPTIDES
- C07K1/00—General methods for the preparation of peptides, i.e. processes for the organic chemical preparation of peptides or proteins of any length
- C07K1/04—General methods for the preparation of peptides, i.e. processes for the organic chemical preparation of peptides or proteins of any length on carriers
- C07K1/047—Simultaneous synthesis of different peptide species; Peptide libraries
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B15/00—ICT specially adapted for analysing two-dimensional or three-dimensional molecular structures, e.g. structural or functional relations or structure alignment
- G16B15/30—Drug targeting using structural data; Docking or binding prediction
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16B—BIOINFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR GENETIC OR PROTEIN-RELATED DATA PROCESSING IN COMPUTATIONAL MOLECULAR BIOLOGY
- G16B35/00—ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/10—Analysis or design of chemical reactions, syntheses or processes
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/60—In silico combinatorial chemistry
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/60—In silico combinatorial chemistry
- G16C20/62—Design of libraries
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/00583—Features relative to the processes being carried out
- B01J2219/0059—Sequential processes
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/00583—Features relative to the processes being carried out
- B01J2219/00592—Split-and-pool, mix-and-divide processes
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/00583—Features relative to the processes being carried out
- B01J2219/00596—Solid-phase processes
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/00583—Features relative to the processes being carried out
- B01J2219/00599—Solution-phase processes
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/0068—Means for controlling the apparatus of the process
- B01J2219/00686—Automatic
- B01J2219/00689—Automatic using computers
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/0068—Means for controlling the apparatus of the process
- B01J2219/00686—Automatic
- B01J2219/00691—Automatic using robots
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/0068—Means for controlling the apparatus of the process
- B01J2219/00695—Synthesis control routines, e.g. using computer programs
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/0068—Means for controlling the apparatus of the process
- B01J2219/00698—Measurement and control of process parameters
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/0068—Means for controlling the apparatus of the process
- B01J2219/007—Simulation or vitual synthesis
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/00718—Type of compounds synthesised
- B01J2219/0072—Organic compounds
-
- B—PERFORMING OPERATIONS; TRANSPORTING
- B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
- B01J—CHEMICAL OR PHYSICAL PROCESSES, e.g. CATALYSIS OR COLLOID CHEMISTRY; THEIR RELEVANT APPARATUS
- B01J2219/00—Chemical, physical or physico-chemical processes in general; Their relevant apparatus
- B01J2219/00274—Sequential or parallel reactions; Apparatus and devices for combinatorial chemistry or for making arrays; Chemical library technology
- B01J2219/00718—Type of compounds synthesised
- B01J2219/0072—Organic compounds
- B01J2219/00725—Peptides
-
- C—CHEMISTRY; METALLURGY
- C40—COMBINATORIAL TECHNOLOGY
- C40B—COMBINATORIAL CHEMISTRY; LIBRARIES, e.g. CHEMICAL LIBRARIES
- C40B40/00—Libraries per se, e.g. arrays, mixtures
- C40B40/04—Libraries containing only organic compounds
- C40B40/10—Libraries containing peptides or polypeptides, or derivatives thereof
-
- C—CHEMISTRY; METALLURGY
- C40—COMBINATORIAL TECHNOLOGY
- C40B—COMBINATORIAL CHEMISTRY; LIBRARIES, e.g. CHEMICAL LIBRARIES
- C40B50/00—Methods of creating libraries, e.g. combinatorial synthesis
- C40B50/08—Liquid phase synthesis, i.e. wherein all library building blocks are in liquid phase or in solution during library creation; Particular methods of cleavage from the liquid support
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/30—Prediction of properties of chemical compounds, compositions or mixtures
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16C—COMPUTATIONAL CHEMISTRY; CHEMOINFORMATICS; COMPUTATIONAL MATERIALS SCIENCE
- G16C20/00—Chemoinformatics, i.e. ICT specially adapted for the handling of physicochemical or structural data of chemical particles, elements, compounds or mixtures
- G16C20/70—Machine learning, data mining or chemometrics
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y10—TECHNICAL SUBJECTS COVERED BY FORMER USPC
- Y10T—TECHNICAL SUBJECTS COVERED BY FORMER US CLASSIFICATION
- Y10T436/00—Chemistry: analytical and immunological testing
- Y10T436/11—Automated chemical analysis
Abstract
A computer based, iterative process for generating chemical entities with defined physical, chemical and/or bioactive properties. During each iteration of the process, (1) a directed diversity chemical library is robotically generated in accordance with robotic synthesis instructions; (2) the compounds in the directed diversity chemical library are analyzed to identify compounds with the desired properties; (3) structure-property data are used to select compounds to be synthesized in the next iteration; and (4) new robotic synthesis instructions are automatically generated to control the synthesis of the directed diversity chemical library for the next iteration.
Description
- 1. Field of the Invention
- The present invention relates generally to the generation of chemical entities with defined physical, chemical or bioactive properties, and particularly to the automatic generation of drug leads via computer-based, iterative robotic synthesis and analysis of directed diversity chemical libraries.
- 2. Related Art
- Conventionally, new chemical entities with useful properties are generated by identifying a chemical compound (called a “lead compound”) with some desirable property or activity, creating variants of the lead compound, and evaluating the property and activity of those variant compounds. Examples of chemical entities with useful properties include paints, finishes, plasticizers, surfactants, scents, flavorings, and bioactive compounds, but can also include chemical compounds with any other useful property that depends upon chemical structure, composition, or physical state. Chemical entities with desirable biological activities include drugs, herbicides, pesticides, veterinary products, etc. There are a number of flaws with this conventional approach to lead generation, particularly as it pertains to the discovery of bioactive compounds.
- One deficiency pertains to the first step of the conventional approach, i.e., the identification of lead compounds. Traditionally, the search for lead compounds has been limited to an analysis of compound banks, for example, available commercial, custom, or natural products chemical libraries. Consequently, a fundamental limitation of the conventional approach is the dependence upon the availability, size, and structural diversity of these chemical libraries. Although chemical libraries cumulatively total an estimated 9 million identified compounds, they reflect only a small sampling of all possible organic compounds with molecular weights less than 1200. Moreover, only a small subset of these libraries is usually accessible for biological testing. Thus, the conventional approach is limited by the relatively small pool of previously identified chemical compounds which may be screened to identify new lead compounds.
- Also, compounds in a chemical library are traditionally screened (for the purpose of identifying new lead compounds) using a combination of empirical science and chemical intuition. However, as stated by Rudy M. Baum in his article “Combinatorial Approaches Provide Fresh Leads for Medicinal Chemistry,”C&EN, Feb. 7, 1994, pages 20-26, “chemical intuition, at least to date, has not proven to be a particularly good source of lead compounds for the drug discovery process.”
- Another deficiency pertains to the second step of the conventional approach, i.e., the creation of variants of lead compounds. Traditionally, lead compound variants are generated by chemists using conventional chemical synthesis procedures. Such chemical synthesis procedures are manually performed by chemists. Thus, the generation of lead compound variants is very labor intensive and time consuming. For example, it typically takes many chemist years to produce even a small subset of the compound variants for a single lead compound. Baum, in the article referenced above, states that “medicinal chemists, using traditional synthetic techniques, could never synthesize all of the possible analogs of a given, promising lead compound” (emphasis added). Thus, the use of conventional, manual procedures for generating lead compound variants operates to impose a limit on the number of compounds that can be evaluated as new drug leads. Overall, the traditional approach to new lead generation is an inefficient, labor-intensive, time consuming process of limited scope.
- Recently, attention has focused on the use of combinatorial chemical libraries to assist in the generation of new chemical compound leads. A combinatorial chemical library is a collection of diverse chemical compounds generated by either chemical synthesis or biological synthesis by combining a number of chemical “building blocks” such as reagents. For example, a linear combinatorial chemical library such as a polypeptide library is formed by combining a set of chemical building blocks called amino acids in every possible way for a given compound length (i.e., the number of amino acids in a polypeptide compound). Millions of chemical compounds theoretically can be synthesized through such combinatorial mixing of chemical building blocks. For example, one commentator has observed that the systematic, combinatorial mixing of 100 interchangeable chemical building blocks results in the theoretical synthesis of 100 million tetrameric compounds or 10 billion pentameric compounds (Gallop et al., “Applications of Combinatorial Technologies to Drug Discovery, Background and Peptide Combinatorial Libraries,”Journal of Medicinal Chemistry, Volume 37, Number 9, pages 1233-1250, Apr. 29, 1994).
- To date, most work with combinatorial chemical libraries has been limited only to peptides and oligonucleotides for the purpose of identifying bioactive agents; little research has been performed using non-peptide, non-nucleotide based combinatorial chemical libraries. It has been shown that the compounds in peptide and oligonucleotide based combinatorial chemical libraries can be assayed to identify ones having bioactive properties. However, there is no consensus on how such compounds (identified as having desirable bioactive properties and desirable profile for medicinal use) can be used.
- Some commentators speculate that such compounds could be used as orally efficacious drugs. This is unlikely, however, for a number of reasons. First, such compounds would likely lack metabolic stability. Second, such compounds would be very expensive to manufacture, since the chemical building blocks from which they are made most likely constitute high priced reagents. Third, such compounds would tend to have a large molecular weight, such that they would have bioavailability problems (i.e., they could only be taken by injection).
- Others believe that the compounds from a combinatorial chemical library that are identified as having desirable biological properties could be used as lead compounds. Variants of these lead compounds could be generated and evaluated in accordance with the conventional procedure for generating new bioactive compound leads, described above. However, the use of combinatorial chemical libraries in this manner does not solve all of the problems associated with the conventional lead generation procedure. Specifically, the problem associated with manually synthesizing variants of the lead compounds is not resolved.
- In fact, the use of combinatorial chemical libraries to generate lead compounds exacerbates this problem. Greater and greater diversity has often been achieved in combinatorial chemical libraries by using larger and larger compounds (that is, compounds having a greater number of variable subunits, such as pentameric compounds instead of tetrameric compounds in the case of polypeptides). However, it is more difficult, time consuming, and costly to synthesize variants of larger compounds. Furthermore, the real issues of structural and functional group diversity are still not directly addressed; bioactive agents such as drugs and agricultural products possess diversity that could never be achieved with available peptide and oligonucleotide libraries since the available peptide and oligonucleotide components only possess limited functional group diversity and limited topology imposed through the inherent nature of the available components. Thus, the difficulties associated with synthesizing variants of lead compounds are exacerbated by using typical peptide and oligonucleotide combinatorial chemical libraries to produce such lead compounds. The issues described above are not limited to bioactive agents but rather to any lead generating paradigm for which a chemical agent of defined and specific activity is desired.
- Thus, the need remains for a system and method for efficiently and effectively generating new leads designed for specific utilities.
- The present invention is directed to a computer based system and method for automatically generating chemical entities with desired physical, chemical and/or biological properties. The present invention is also directed to the chemical entities produced by this system and method. For purposes of illustration, the present invention is described herein with respect to the production of drug leads. However, the present invention is not limited to this embodiment.
- Specifically, the present invention is directed to an iterative process for generating new chemical compounds with a prescribed set of physical, chemical and/or biological properties, and to a system for implementing this process. During each iteration of the process, (1) a directed diversity chemical library is robotically generated in accordance with robotic synthesis instructions; (2) the compounds in the directed diversity chemical library are analyzed under computer control, and structure-activity/structure-property models (collectively referred to as structure-activity models hereafter) are constructed and/or refined; and (3) new robotic synthesis instructions are generated to control the synthesis of the directed diversity chemical library for the next iteration.
- More particularly, during each iteration of the process, the system of the present invention robotically synthesizes, in accordance with robotic synthesis instructions, a directed diversity chemical library comprising a plurality of chemical compounds. The chemical compounds are robotically analyzed to obtain structure-activity/structure-property data (collectively referred to as structure-activity data hereafter) pertaining thereto. The structure-activity data is stored in a structure-activity/structure-property database (referred to as structure-activity database hereafter). The structure-activity database also stores therein structure-activity data pertaining to previously synthesized compounds.
- The system of the present invention evaluates, under computer control, the structure-activity data of the chemical compounds obtained from all previous iterations (or a subset of all previous iterations as specified by user input, for example) and constructs structure-activity models that substantially conform to the observed data.
- The system of the present invention then identifies, under computer control, reagents, from a reagent database, which, when combined, will produce compounds which are predicted to (1) exhibit improved activity/properties, (2) test the validity of the current structure-activity models, and/or (3) discriminate between the various structure-activity models. Under the system of the present invention, a plurality of structure-activity models may be tested and evaluated in parallel.
- Then, the system of the present invention generates, under computer control, new robotic synthesis instructions which, when executed, enable robotic synthesis of chemical compounds from selected combinations of the identified reagents. Such new robotic synthesis instructions are used to generate a new directed diversity chemical library during the next iteration.
- Further features and advantages of the present invention, as well as the structure and operation of various embodiments of the present invention, are described in detail below with reference to the accompanying drawings. In the drawings, like reference numbers indicate identical or functionally similar elements. Also, the leftmost digit(s) of the reference numbers identify the drawings in which the associated elements are first introduced.
- The present invention will be described with reference to the accompanying drawings, wherein:
- FIG. 1 is a block diagram of a lead generation system according to a preferred embodiment of the present invention;
- FIG. 2 is a flow diagram depicting the preferred flow of data and materials among elements of the lead generation system of the present invention;
- FIGS.3-6 are flowcharts depicting the operation of the lead generation system according to a preferred embodiment of the present invention;
- FIG. 7 is a preferred block diagram of a structure-activity database which forms a part of the lead generation system of the present invention;
- FIG. 8 illustrates a preferred database record format common to records in the structure-activity database;
- FIG. 9 is a preferred block diagram of analysis robots which are part of the lead generation system of the present invention;
- FIG. 10 illustrates an embodiment of the present invention in which candidate compounds are ranked according to their predicted three-dimensional receptor fit;
- FIG. 11 is used to describe the preferred, high level operation of the present invention; and
- FIG. 12 is a schematic of an example thrombin directed diversity chemical library.
- 1. General Overview
- The present invention is directed to the computer-aided generation of chemical entities with a prescribed set of physical, chemical and/or bioactive properties via computer-based, iterative robotic synthesis and analysis of directed diversity chemical libraries. The present invention is also directed to the new chemical entities generated by operation of the present invention.
- According to the present invention, a directed diversity chemical library is not the same as a combinatorial chemical library. As discussed above, a combinatorial chemical library comprises a plurality of chemical compounds which are formed by combining, in every possible way for a given compound length (i.e., the number of building blocks in a compound), a set of chemical building blocks. For example, suppose that three chemical building blocks (designated as A, B, and C) are used to generate a combinatorial chemical library. Also suppose that the length of the compounds in the combinatorial chemical library is equal to two. In this case, the following compounds would be generated: AA, AB, AC, BA, BB, BC, CA, CB, and CC.
- In contrast, a directed diversity chemical library comprises a plurality of chemical compounds which are formed by selectively combining a particular set of chemical building blocks. Thus, whereas discovery using combinatorial chemical libraries tends to be scattershot and random (essentially constituting a “needle in a haystack” research paradigm), the use by the present invention of directed diversity chemical libraries results in an optimization approach which is focused and directed.
- As shown in FIG. 11, the present invention includes a
Chemical Synthesis Robot 112 which operates in accordance withrobotic synthesis instructions 204 to synthesize a DirectedDiversity Chemical Library 208. TheChemical Synthesis Robot 112 synthesizes the DirectedDiversity Chemical Library 208 by selectively mixing a set of chemical building blocks from aReagent Repository 114 in accordance with therobotic synthesis instructions 204. - In one example of the present invention, discussed here to generally illustrate the present invention, these chemical building blocks comprise approximately 100 commercially available reagents suitable for generating thrombin inhibitors. However, it should be understood that the present invention is not limited to this example. Preferably, the
Chemical Synthesis Robot 112 combines these reagents using well known synthetic chemistry techniques to synthesize inhibitors of the enzyme thrombin. Each inhibitor is generally composed of, but not restricted to, three chemical building blocks. Thus, the DirectedDiversity Chemical Library 208 preferably comprises a plurality of thrombin inhibitors generally composed of, but not restricted to, three sites of variable structure (i.e., trimers). - Again, however, it should be understood that the present invention is not limited to this thrombin example. The present invention is equally adapted and intended to generate chemical compounds (other than thrombin inhibitors) having other desired properties, such as paints, finishes, plasticizers, surfactants, scents, flavorings, bioactive compounds, drugs, herbicides, pesticides, veterinary products, etc., and/or lead compounds for any of the above. In fact, the present invention is adapted and intended to generate chemical compounds having any useful properties that depend upon structure, composition, or state.
- Still referring to FIG. 11, the Directed
Diversity Chemical Library 208 generated by theChemical Synthesis Robot 112 is provided to ananalysis robot 116. Theanalysis robot 116 analyzes (chemically, biochemically, physically, and/or biophysically) the compounds in the DirectedDiversity Chemical Library 208 to obtain structure-activity/structure-property data (called herein Structure-Activity Data) 210 pertaining to the compounds. Such structure-activity/structure-property data 210 includes well known structure-activity/structure property relationship data (collectively referred to as structure-activity relationships or SAR hereafter) pertaining to the relationship(s) between a compound's activity/properties and its chemical structure. Preferably, theanalysis robot 116 assays the compounds in the DirectedDiversity Chemical Library 208 to obtain, for example, enzyme activity data, cellular activity data, toxicology data, and/or bioavailability data pertaining to the compounds. Optionally, theanalysis robot 116 also analyzes the compounds to identify which of the compounds were adequately synthesized, and which of the compounds were not adequately synthesized. This could be useful, since not all combinations of chemical building blocks may interact as expected. Theanalysis robot 116 further analyzes the compounds to obtain other pertinent data, such as data pertaining to the compounds' composition, structure and electronic structure. - This data obtained by the analysis robot116 (i.e., physical data, synthesis data, enzyme activity data, cellular activity data, toxicology data, bioavailability data, etc.) collectively represents the Structure-
Activity Data 210 shown in FIG. 11. The Structure-Activity Data 210 is stored in a Structure-Activity Database 122, and is provided to aSynthesis Protocol Generator 104. - The
Synthesis Protocol Generator 104 uses the Structure-Activity Data 210 of the chemical compounds in the DirectedDiversity Chemical Library 208, as well as historical structure-activity data 212 pertaining to chemical compounds that were previously synthesized (or known), to derive and/or refine structure-activity models that substantially conform to the observed data. - The synthesis protocol generator then identifies, under computer control, reagents, from a
Reagent Repository 114, which, when combined with each other, will produce compounds which are predicted (by the structure-activity models) to (1) exhibit improved activity/properties, (2) test the validity of the current structure-activity models, and/or (3) discriminate between the various structure-activity models. Under the system of the present invention, one or more structure-activity models may be tested and evaluated in parallel. - In addition, the
Synthesis Protocol Generator 104 classifies any compounds which possess the desired activity/properties as new leads (lead compounds) 216. - After performing this analysis, the
Synthesis Protocol Generator 104 generates newrobotic synthesis instructions 204 which pertain to the synthesis of chemical compounds from combinations of the identified reagents. These newrobotic synthesis instructions 204 are provided to theChemical Synthesis Robot 112. - Then, the process described above is repeated. In particular, the
Chemical Synthesis Robot 112 operates in accordance with the newrobotic synthesis instructions 204 to synthesize a new DirectedDiversity Chemical Library 208 by selectively combining the identified reagents. Theanalysis robot 116 analyzes the new DirectedDiversity Chemical Library 208 to obtain Structure-Activity Data 210 pertaining to the compounds in the new DirectedDiversity Chemical Library 208. TheSynthesis Protocol Generator 104 analyzes the Structure-Activity Data 210 pertaining to the compounds in the new DirectedDiversity Chemical Library 208 to improve the structure-activity models, and to generate newrobotic synthesis instructions 204. - Thus, the present invention is an iterative process for generating new chemical entities having a set of physical, chemical and/or biological properties optimized towards a prescribed target. During each iteration, a Directed
Diversity Chemical Library 208 is generated, the compounds in the DirectedDiversity Chemical Library 208 are analyzed, structure-activity models are derived and elaborated, androbotic synthesis instructions 204 are generated to control the synthesis of the DirectedDiversity Chemical Library 208 for the next iteration. - Preferably, elements of the present invention are controlled by a data processing device, such as a computer operating in accordance with software. Consequently, it is possible in the present invention to store massive amounts of data, and to utilize this data in a current iteration to generate
robotic synthesis instructions 204 for the next iteration. In particular, since the elements of the present invention are controlled by a data processing device, it is possible to store the Structure-Activity Data 210 obtained during each iteration. It is also possible to utilize the historical structure-activity data 212 obtained during previous iterations, as well as other pertinent structure-activity data obtained by other experiments, to generaterobotic synthesis instructions 204 for the next iteration. In other words, the synthesis of the DirectedDiversity Chemical Library 208 for the next iteration is guided by the results of all previous iterations (or any subset of the previous iterations, as determined by user input, for example). Put another way, the present invention “learns” from its past performance such that the present invention is “intelligent”. As a result, theleads 216 identified in subsequent iterations are better (i.e., exhibit physical, chemical and/or biological properties closer to the prescribed values) than theleads 216 identified in prior iterations. - According to a preferred embodiment of the present invention, one or more robots (i.e., the Chemical Synthesis Robot112) are used to robotically synthesize the Directed
Diversity Chemical Library 208 during each iteration. Also, one or more robots (i.e. the analysis robot 116) are used to robotically analyze the compounds contained in the DirectedDiversity Chemical Library 208 during each iteration. As used herein, the term “robot” refers to any automated device that automatically performs functions specified by instructions, such as therobotic synthesis instructions 204 which theChemical Synthesis Robot 112 receives from theSynthesis Protocol Generator 104. The integrated use of data processing devices (i.e., the Synthesis Protocol Generator 104) and robots (i.e., theChemical Synthesis Robot 112 and the analysis robot 116) in the present invention enables the automatic and intelligent synthesis and screening of very large numbers of chemical compounds. - The structure and operation of the present invention shall now be described in greater detail.
- 2. Structure of the Present Invention
- FIG. 1 is a structural block diagram of a lead generation/
optimization system 102 according to a preferred embodiment of the present invention. The druglead generation system 102 comprises a central processing unit (CPU), such as aprocessor 106, which operates according tocontrol logic 108. According to the present invention, theprocessor 106 and thecontrol logic 108 collectively represent aSynthesis Protocol Generator 104. - The
control logic 108 preferably represents a computer program such that theprocessor 106 operates according to software instructions contained in thecontrol logic 108. Alternatively, theprocessor 106 and/or thecontrol logic 108 are implemented as a hardware state machine. - A suitable form for the
processor 106 is an Indigo, Indy, Onyx, Challenge, or Power Challenge computer made by Silicon Graphics, Inc., of Mountain View, Calif. Another suitable form for theprocessor 106 is a Connection Machine computer made by Thinking Machines Corporation of Boston, Mass. Any other suitable computer system could alternatively be used. - A
communication medium 110, comprising one or more data buses and/or IO (input/output) interface devices, connect theSynthesis Protocol Generator 104 to a number of peripheral devices, such as aninput device 121, anoutput device 123, aChemical Synthesis Robot 112, one ormore analysis robots 116, and adata storage device 118. - The
input device 121 receives input (such as data, commands, etc.) from human operators and forwards such input to theSynthesis Protocol Generator 104 via thecommunication medium 110. Any well known, suitable input device may be used in the present invention, such as a keyboard, pointing device (mouse, roller ball, track ball, light pen, etc.), touch screen, etc. User input may also be stored and then retrieved, as appropriate, from data/command files. - The
output device 123 outputs information to human operators. TheSynthesis Protocol Generator 104 transfers such information to theoutput device 123 via thecommunication medium 110. Any well known, suitable output device may be used in the present invention, such as a monitor, a printer, a floppy disk drive, a text-to-speech synthesizer, etc. - The
Chemical Synthesis Robot 112 receives robotic synthesis instructions from theSynthesis Protocol Generator 104 via thecommunication medium 110. TheChemical Synthesis Robot 112 operates according to the robotic synthesis instructions to selectively combine a particular set of reagents from aReagent Repository 114 to thereby generate structurally and functionally diverse chemical compounds. These chemical compounds form a DirectedDiversity Chemical Library 208. - The
Chemical Synthesis Robot 112 is preferably capable of mix-and-split, solid phase chemistry for coupling chemical building blocks. TheChemical Synthesis Robot 112 preferably performs selective microscale solid state synthesis of a specific combinatorial library of directed diversity library compounds. TheChemical Synthesis Robot 112 preferably cleaves and separates the compounds of the Directed Diversity Chemical Library 208 (FIG. 2) from support resin and distributes the compounds into preferably 96 wells with from 1 to 20 directed diversity library compounds per well, corresponding to an output of 96 to 1920 compounds per synthetic cycle iteration. This function may alternatively be performed by a well known liquid transfer robot (not shown). Chemical synthesis robots suitable for use with the present invention are well known and are commercially available from a number of manufacturers, such as the following:TABLE 1 Manufacturer City State Model Advanced ChemTech Louisville KY 357 MPS 390 MPS Rainin Woburn MA Symphony Perkin-Elmer Corporation Applied Foster City CA 433A Biosystems Division Millipore Bedford MA 9050 Plus - All of the instruments listed in Table 1 perform solid support-based peptide synthesis only. The Applied Biosystems and the Millipore instruments are single peptide synthesizers. The Rainin Symphony is a multiple peptide synthesizer capable of producing up to 20 peptides simultaneously. The Advanced ChemTech instruments are also multiple peptide synthesizers, but the 357 MPS has a feature utilizing an automated mix-and-split technology. The peptide synthesis technology is preferred in producing the directed diversity libraries associated with the present invention. See, for example, Gallop, M. A. et al.,J. Med. Chem. 37, 1233-1250 (1994), which is herein incorporated by reference in its entirety.
- Peptide synthesis is by no means the only approach envisioned and intended for use with the present invention. Other chemistries for generating chemical diversity libraries can also be used. For example, the following are suitable: peptoids (PCT Publication No WO 91/19735, Dec. 26, 1991), encoded peptides (PCT Publication WO 93/20242, Oct. 14, 1993), random bio-oligomers (PCT Publication WO 92/00091, Jan. 9, 1992), benzodiazepines (U.S. Pat. No. 5,288,514), diversomeres such as hydantoins, benzodiazepines and dipeptides (Hobbs DeWitt, S. et al.,Proc. Nat. Acad. Sci. USA 90:6909-6913 (1993)), vinylogous polypeptides (Hagihara et al., J. Amer. Chem. Soc. 114 : 6568 (1992)), nonpeptidal peptidormimetics with a Beta-D-Glucose scaffolding (Hirschmann, R. et al., J. Amer. Chem. Soc. 114 : 9217-9218 (1992)), analogous organic syntheses of small compound libraries (Chen, C. et al., J. Amer. Chem. Soc. 116: 2661(1994)), oligocarbamates (Cho, C. Y. et al., Science 261:1303 (1993)), and/or peptidyl phosphonates (Campbell, D. A. et al., J. Org. Chem. 59:658(1994)). See, generally, Gordon, E. M. et al., J. Med. Chem. 37: 1385 (1994). The contents of all of the aforementioned publications are incorporated herein by reference.
- A number of well known robotic systems have also been developed for solution phase chemistries. These systems include automated workstations like the automated synthesis apparatus developed by Takeda Chemical Industries, LTD. (Osaka, Japan) and many robotic systems utilizing robotic arms (Zymate II, Zymark Corporation, Hopkinton, Mass.; Orca, Hewlett-Packard, Palo Alto, Calif.) which mimic the manual synthetic operations performed by a chemist.
- Any of the above devices are suitable for use with the present invention. The nature and implementation of modifications to these devices (if any) so that they can operate as discussed herein will be apparent to persons skilled in the relevant art.
- The
analysis robots 116 receive the chemical compounds synthesized by theChemical Synthesis Robot 112. This is indicated byarrow 113. Theanalysis robots 116 analyze these compounds to obtain structure-activity data pertaining to the compounds. - FIG. 9 is a more detailed structural block diagram of the
analysis robots 116. Theanalysis robots 116 include one ormore assay modules 902, such as an enzymeactivity assay module 904, a cellularactivity assay module 906, atoxicology assay module 908, and/or abioavailability assay module 910. The enzymeactivity assay module 904 assays the compounds synthesized by theChemical Synthesis Robot 112 using well known procedures to obtain enzyme activity data relating to the compounds. The cellularactivity assay module 906 assays the compounds using well known procedures to obtain cellular activity data relating to the compounds. Thetoxicology assay module 908 assays the compounds using well known procedures to obtain toxicology data relating to the compounds. Thebioavailability assay module 910 assays the compounds using well known procedures to obtain bioavailability data relating to the compounds. - The enzyme
activity assay module 904, cellularactivity assay module 906,toxicology assay module 908, andbioavailability assay module 910 are implemented in a well known manner to facilitate the preparation of solutions, initiation of the biological or chemical assay, termination of the assay (optional depending on the type of assay) and measurement of the results, commonly using a counting device, spectrophotometer, fluorometer or radioactivity detection device. Each of these steps can be done manually or by robots in a well known manner. Raw data is collected and stored on magnetic media under computer control or input manually into a computer. Useful measurement parameters such as dissociation constants or 50% inhibition concentrations can then be manually or automatically calculated from the observed data, stored on magnetic media and output to a relational database. - The
analysis robots 116 optionally include a structure andcomposition analysis module 914 to obtain two dimensional structure and composition data relating to the compounds. Preferably, the structure andcomposition analysis module 914 is implemented using a liquid chromatograph device and/or a mass spectrometer. In one embodiment, a sampling robot (not shown) transfers aliquots from the 96 wells to a coupled liquid chromatography-mass spectrometry system to perform sample analysis. - The structure and
composition analysis module 914 may be utilized to determine product composition and to monitor reaction progress by comparison of the experimental results to the theoretical results predicted by theSynthesis Protocol Generator 104. The analysis module may use, but is not limited to, infra-red spectroscopy, decoding of a molecular tag, mass spectrometry (MS), gas chromatography (GC), liquid chromatography (LC), or combinations of these techniques (i.e., GC-MS, LC-MS, or MS-MS). Preferably, the structure andcomposition analysis module 914 is implemented using a mass spectrometric technique such as Fast Atom Bombardment Mass Spectrometry (FABSMS) or triple quadrapole ion spray mass spectrometry, optionally coupled to a liquid chromatograph, or matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS). MALDI-TOF MS is well known and is described in a number of references, such as: Brummell et al., Science 264:399 (1994); Zambias et al., Tetrahedron Lett. 35:4283 (1994), both incorporated herein by reference in their entireties. - Liquid chromatograph devices, gas chromatograph devices, and mass spectrometers suitable for use with the present invention are well known and are commercially available from a number of manufacturers, such as the following:
TABLE 2 GAS CHROMATOGRAPHY Manufacturer City State Model Hewlett-Packard Company Palo Alto CA 5890 Varian Associates Palo Alto CA Shimadzu Scientific Inst. Columbia MD GC-17A Fisons Instruments Beverly MA GC 8000 -
TABLE 3 LIQUID CHROMATOGRAPHY Manufacturer City State Model Hewlett-Packard Company Palo Alto CA 1050, 1090 Varian Associates Inc. Palo Alto CA Rainin Instrument Co. Woburn MA Shimadzu Scientific Inst. Columbia MD LC-10A Waters Chromatography Milford MA Millennium Perkin-Elmer Corporation Norwalk CT Hitachi Instruments Inc. San Jose CA -
TABLE 4 MASS SPECTROSCOPY Manufacturer City State Model Hewlett-Packard Company Palo Alto CA Varian Associates Inc. Palo Alto CA Kratos Analytical Inc. Ramsey NJ MS80RFAQ Finnigan MAT San Jose CA Vision 2000, TSQ-700 Fisons Instruments Beverly MA API LC/MS, AutoSpec Perkin-Elmer Sciex Norwalk CT API-III - Modifications to these devices may be necessary to fully automate both the loading of samples on the systems as well as the comparison of the experimental and predicted results. The extent of the modification may vary from instrument to instrument. The nature and implementation of such modifications will be apparent to persons skilled in the art.
- The
analysis robots 116 may optionally further include a chemicalsynthesis indicia generator 912 which analyzes the structure and composition data obtained by the structure andcomposition analysis module 914 to determine which compounds were adequately synthesized by theChemical Synthesis Robot 112, and which compounds were not adequately synthesized by theChemical Synthesis Robot 112. Preferably, the chemicalsynthesis indicia generator 912 is implemented using a processor, such asprocessor 106, operating in accordance with appropriate control logic, such ascontrol logic 108. Preferably, thecontrol logic 108 represents a computer program such that theprocessor 106 operates in accordance with instructions in thecontrol logic 108 to determine which compounds were adequately synthesized by theChemical Synthesis Robot 112, and which compounds were not adequately synthesized by theChemical Synthesis Robot 112. Persons skilled in the relevant art will be able to producesuch control logic 108 based on the discussion of the chemicalsynthesis indicia generator 912 contained herein. - The
analysis robots 116 may also include a three dimensional (3D)receptor mapping module 918 to obtain three dimensional structure data relating to a receptor binding site. The 3Dreceptor mapping module 918 preferably determines the three dimensional structure of a receptor binding site empirically through x-ray crystallography and/or nuclear magnetic resonance spectroscopy, and/or as a result of the application of extensive 3D QSAR (quantitative structure-activity relationship) and receptor field analysis procedures, well known to persons skilled in the art and described in: “Strategies for Indirect Computer-Aided Drug Design”, Gilda H. Loew et al., Pharmaceutical Research, Volume 10, No. 4, pages 475-486 (1993); “Three Dimensional Structure Activity Relationships”, G. R. Marshall et al., Trends In Pharmaceutical Science, 9: 285-289 (1988). Both of these documents are herein incorporated by reference in their entireties. - The
analysis robots 116 may additionally include a physical and/or electronic property analysis module(s) 916 which analyzes the compounds synthesized by theChemical Synthesis Robot 112 to obtain physical and/or electronic property data relating to the compounds. Such properties may include water/octanol partition coefficients, molar refractivity, dipole moment, fluorescence etc. Such properties may either be measured experimentally or computed using methods well known to persons skilled in the art. - Referring again to FIG. 1, the
data storage device 118 is a read/write high storage capacity device such as a tape drive unit or a hard disk unit. Data storage devices suitable for use with the present invention are well known and are commercially available from a number of manufacturers, such as the 2 gigabyte Differential System Disk, part number FTO-SD8-2NC, and the 10 gigabyte DLT tape drive, part number P-W-DLT, both made by Silicon Graphics, Inc., of Mountain View, Calif. Areagent database 120 and a Structure-Activity Database 122 are stored in thedata storage device 118. - The
reagent database 120 contains information pertaining to the reagents in theReagent Repository 114. In particular, thereagent database 120 contains information pertaining to the chemical substructures, chemical properties, physical properties, biological properties, and electronic properties of the reagents in theReagent Repository 114. - The Structure-
Activity Database 122 stores Structure-Activity Data 210, 212 (FIG. 2) pertaining to the compounds which were synthesized by theChemical Synthesis Robot 112. Such Structure-Activity Data analysis robots 116, as described above. The Structure-Activity Data analysis robots 116 is transferred to and stored in the Structure-Activity Database 122 via thecommunication medium 110. - FIG. 7 is a more detailed block diagram of the Structure-
Activity Database 122. The Structure-Activity Database 122 includes a structure andcomposition database 702, a physical and electronic properties database(s) 704, achemical synthesis database 706, achemical properties database 708, a 3Dreceptor map database 710, and abiological properties database 712. The structure andcomposition database 702 stores structure andcomposition data 714 pertaining to compounds synthesized by theChemical Synthesis Robot 112 and analyzed by theanalysis robots 116. Similarly, the physical andelectronic properties database 704,chemical synthesis database 706,chemical properties database receptor map database 710, andbiological properties database 712 store physical andelectronic properties data 716,chemical synthesis indicia 718,chemical properties data receptor map data 722, andbiological properties data 724, respectively, pertaining to compounds synthesized by theChemical Synthesis Robot 112 and analyzed by theanalysis robots 116. The structure andcomposition data 714,electronic properties data 716,chemical synthesis indicia 718,chemical properties data 720,receptor map data 722, andbiological properties data 724 collectively represent the Structure-Activity Data - Preferably, the structure and
composition database 702, physical andelectronic properties database 704,chemical synthesis database 706,chemical properties database receptor map database 710, andbiological properties database 712 each include one record for each chemical compound synthesized by theChemical Synthesis Robot 112 and analyzed by theanalysis robots 116. (Other database structures could alternatively be used.) FIG. 8 depicts a preferreddatabase record format 802 for these records. - Each database record includes: (1) a
first field 804 containing information identifying the compound; (2) asecond field 806 containing information identifying the reagents from theReagent Repository 114 that were combined to produce the compound; (3) athird field 808 containing information indicating the predicted mass and structure of the compound and information identifying the label assigned to the compound (the information contained in thethird field 808 is described below); (4) afourth field 810 indicating the rating factor (described below) assigned to the compound; and (5) afifth field 812 containing structure-activity data. The information stored in thefifth field 812 is database specific (also, thefifth field 812 may include one or more sub-fields). For example, thefifth field 812 in records of the structure andcomposition database 702 stores structure andcomposition data 714, whereas thefifth field 812 in records of theelectronic properties database 704 storeselectronic properties data 716. - 3. Operation of the Present Invention
- The operation of the lead generation/
optimization system 102 shall now be described in detail with reference to aflowchart 302 shown in FIG. 3, and a flow diagram 202 shown in FIG. 2.Flowchart 302 represents the preferred operation of the present invention. The flow diagram 202 depicts the preferred flow of data and materials between the elements of thelead generation system 102. - As stated above, the lead generation/
optimization system 102 implements an iterative process where, during each iteration, (1) a DirectedDiversity Chemical Library 208 is generated; (2) the compounds in the DirectedDiversity Chemical Library 208 are analyzed and new lead compounds 216 are classified, structure-activity/structure-property models with enhanced predictive and discriminating capabilities are constructed, and compounds which are predicted to exhibit improved activity/properties are identified for synthesis during the next iteration; and (3)robotic synthesis instructions 204 are generated to control the synthesis of the DirectedDiversity Chemical Library 208 for the next iteration. The steps of flowchart 302 (that is, steps 304-316) are performed during each iteration of this iterative process as indicated bycontrol line 317 inflowchart 302. Generally, (1) the DirectedDiversity Chemical Library 208 is generated duringstep 304; (2) the compounds in the DirectedDiversity Chemical Library 208 are analyzed and new lead compounds 216 are classified, structure-activity/structure-property models with enhanced predictive and discriminating capabilities are constructed, and compounds which are predicted to exhibit improved activity/properties are identified for synthesis during the next iteration during steps 306-314; and (3)robotic synthesis instructions 204 are generated to control the synthesis of the DirectedDiversity Chemical Library 208 for the next iteration duringstep 316 . The operation of the lead generation/optimization system 102 according to the steps offlowchart 302 shall now be discussed in detail. - As represented by
step 304, theChemical Synthesis Robot 112 robotically synthesizes a plurality of chemical compounds in accordance with robotic synthesis instructions 204 (flowarrow 252 in FIG. 2). Preferably, theChemical Synthesis Robot 112 synthesizes the chemical compounds by selective mixing ofreagents 206 from a Reagent Repository 114 (flowarrows robotic synthesis instructions 204. The chemical compounds synthesized by theChemical Synthesis Robot 112 collectively represent a Directed Diversity Chemical Library 208 (flowarrow 254 in FIG. 2). - The
robotic synthesis instructions 204 are generated by aSynthesis Protocol Generator 104 in a manner which is described below (flowarrow 250 in FIG. 2). Therobotic synthesis instructions 204 identify whichreagents 206 from theReagent Repository 114 are to be mixed by theChemical Synthesis Robot 112. Therobotic synthesis instructions 204 also identify the manner in whichsuch reagents 206 are to be mixed by the Chemical Synthesis Robot 112 (i.e., which of thereagents 206 are to be mixed together, and under what chemical and/or physical conditions, such as temperature, length of time, stirring, etc.). - As represented by
step 306,analysis robots 116 receive the DirectedDiversity Chemical Library 208 generated by the Chemical Synthesis Robot 112 (flowarrow 256 in FIG. 2). Theanalysis robots 116 robotically analyze the chemical compounds in the DirectedDiversity Chemical Library 208 to obtain Structure-Activity Data 210 pertaining to such compounds (flowarrow 258 in FIG. 2). - As represented by
step 308, theanalysis robots 116 store the Structure-Activity Data 210 in a Structure-Activity Database 122 contained in a data storage device 118 (flowarrow 260 in FIG. 2). This structure-activity database 112 also stores structure-activity data pertaining to chemical compounds which were synthesized and analyzed in previous iterations by theChemical Synthesis Robot 112 and theanalysis robots 116, respectively, as well as other pertinent structure-activity data obtained from independent experiments. - The operation of the lead generation/
optimization system 102 while performingsteps - During
step 306, assay modules 902 (FIG. 9) robotically assay the chemical compounds in the DirectedDiversity Chemical Library 208 to obtainphysical properties data 716,chemical properties data 720 and biological properties data 724 (FIG. 7) pertaining to the chemical compounds. For example, the enzymeactivity assay module 904 robotically assays the chemical compounds using well known assay techniques to obtain enzyme activity data relating to the compounds. Such enzyme activity data includes inhibition constants K1, maximal velocity Vmax, etc. The cellularactivity assay module 906 robotically assays the compounds using well known assay techniques to obtain cellular activity data relating to the compounds. Thetoxicology assay module 908 robotically assays the compounds using well known assay techniques to obtain toxicology data relating to the compounds. Thebioavailability assay module 910 robotically assays the compounds using well know assay techniques to obtain bioavailability data relating to the compounds. Such enzyme activity data, cellular activity data, toxicology data, and bioavailability data represent thephysical properties data 716,chemical properties data 720 and thebiological properties data 724 shown in FIG. 7. Alternatively,physical properties data 716 may be obtained by the physical and electronicproperty analysis module 916. Instep 308, thephysical properties data 716 is stored in thephysical properties database 704, thechemical properties data 720 is stored in thechemical properties database 706 and thebiological properties data 724 is stored in thebiological properties database 712. - Also during
step 306, the electronicproperty analysis module 916 automatically analyzes the chemical compounds contained in the DirectedDiversity Chemical Library 208 to obtainelectronic properties data 716 pertaining to the chemical compounds. Suchelectronic properties data 716 is stored in theelectronic properties database 704 duringstep 308. - Additionally during
step 306, the 3Dreceptor mapping module 918 obtainsreceptor map data 722 representing the three dimensional structure pertaining to a receptor binding site being tested. The 3Dreceptor mapping module 918 preferably determines the three dimensional structure of the receptor binding site empirically through x-ray crystallography, nuclear magnetic resonance spectroscopy, and/or as result of the application of extensive 3D QSAR and receptor field analysis procedures. Suchreceptor map data 722 is stored in the 3Dreceptor map database 710 duringstep 308. - Also during
step 306, an optional structure andcomposition analysis module 914 analyzes the chemical compounds contained in the DirectedDiversity Chemical Library 208 to obtain structure andcomposition data 714 pertaining to the chemical compounds. Such structure andcomposition data 714 is stored in the structure andcomposition database 702 duringstep 308. - The operation of the structure and composition analysis module914 (and also the chemical synthesis indicia generator 912) during
steps - As represented by
step 404, the structure andcomposition analysis module 914 analyzes the chemical compounds in the DirectedDiversity Chemical Library 208 to obtain structure andcomposition data 714 pertaining to the compounds. Preferably, the structure andcomposition analysis module 914 analyzes the chemical compounds using well known mass spectra analysis techniques. - As represented by
step 405, the structure andcomposition data 714 is stored in a structure andcomposition database 702 which forms part of the Structure-Activity Database 122 (FIG. 7). - As represented by
step 406, the chemicalsynthesis indicia generator 912 receives the structure andcomposition data 714. The chemicalsynthesis indicia generator 912 also retrieves from the Structure-Activity Database 122 the predicted mass and structural data relating to the compounds in the DirectedDiversity Chemical Library 208. Such data (i.e., the predicted mass and structural data) is preferably retrieved from the third field 808 (FIG. 8) of the records of the Structure-Activity Database 122 pertaining to the compounds in the DirectedDiversity Chemical Library 208. The manner in which the predicted mass and structural data is generated and stored in the Structure-Activity Database 122 is considered in an ensuing discussion pertaining tosteps - As represented by
step 408, the chemicalsynthesis indicia generator 912 compares the structure and composition data 714 (obtained by the structure and composition analysis module 914) with the predicted mass and structural data (retrieved from the Structure-Activity Database 122) to generatechemical synthesis indicia 718. Thechemical synthesis indicia 718 indicates which of the chemical compounds from the DirectedDiversity Chemical Library 208 were adequately synthesized, and which were not adequately synthesized. - Preferably, during
step 408 the chemicalsynthesis indicia generator 912 compares, for each compound, the measured mass of the compound (which is part of the structure and composition data 714) to the predicted mass of the compound. If the measured mass and the predicted mass differ by less than a predetermined amount, then the chemicalsynthesis indicia generator 912 determines that the chemical compound was adequately synthesized. If the measured mass and the predicted mass differ by more than the predetermined amount, then the chemicalsynthesis indicia generator 912 determines that the chemical compound was not adequately synthesized. This predetermined amount depends on the sensitivity of the instrument used for the structure and composition analysis. - As represented by
step 410, the chemicalsynthesis indicia generator 912 generateschemical synthesis indicia 718 pertaining to the compounds in the DirectedDiversity Chemical Library 208, and stores suchchemical synthesis indicia 718 in thechemical synthesis database 706. Suchchemical synthesis indicia 718 for each compound is a first value (such as “1”) if the compound was adequately synthesized (as determined in step 408), and is a second value (such as “0”) if the compound was not adequately synthesized. - The performance of
steps step 410. Afterstep 410 is completed, control passes to step 310 (FIG. 3). - As represented by
step 310, the Structure-Activity Data 210 pertaining to the compounds in the DirectedDiversity Chemical Library 208 is provided to the Synthesis Protocol Generator 104 (flowarrow 262 in FIG. 2). TheSynthesis Protocol Generator 104 also receives data pertaining to the desired activity/properties 214 (flowarrow 272 in FIG. 2). This is also called “desired structure/property profile 214” or the “prescribed set”. Such data pertaining to desired activity/properties 214 was previously entered by human operators using theinput device 121, or read from a file. TheSynthesis Protocol Generator 104 compares the Structure-Activity Data 210 of the compounds in the DirectedDiversity Chemical Library 208 against the desired activity/properties 214 to determine whether any of the compounds substantially conforms to the desired activity/properties 214. - Preferably, the
Synthesis Protocol Generator 104 instep 312 assigns a rating factor to each compound in the DirectedDiversity Chemical Library 208, based on how closely the compound's activity/properties match the desired activity/property profile 214. The rating factor may be represented by either numerical or linguistic values. Numerical rating factors represent a sliding scale between a low value (corresponding to an activity/property profile far from the prescribed set 214) and a high value (corresponding to an activity/property profile identical, or very similar, to the prescribed set 214). Linguistic rating factors take values such as “poor,” “average,” “good,” “very good,” etc. Preferably, theSynthesis Protocol Generator 104 stores the rating factors of the compounds in the fourth field 810 (FIG. 8) of their respective records in the Structure-Activity Database 122. - Also in
step 312, any compound from the DirectedDiversity Chemical Library 208 that substantially conforms to the desired activity/properties profile 214 is classified as a new lead compound. The rating factor may also be used to select new leads if an insufficient number of compounds substantially exhibiting the desired activity/properties 214 is found. - As represented by
step 314, theSynthesis Protocol Generator 104 retrieves from the Structure-Activity Database 122 historical structure-activity data 212 pertaining to the chemical compounds synthesized in previous iterations (flowarrows 264 and 266). Also duringstep 314, theSynthesis Protocol Generator 104 accesses thereagent information database 120 and retrievesdata 218 pertaining to reagents contained in the Reagent Repository 114 (flowarrows reagent data 218 and the Structure-Activity Data Reagent Repository 114 which, when combined, will produce compounds which are predicted to (1) exhibit improved activity/properties, (2) test the validity of the current structure-activity models, and/or (3) discriminate between the various structure-activity models. Under the system of the present invention, one or more structure-activity models may be tested and evaluated in parallel. - Preferably, during the first iteration of
flowchart 302, theSynthesis Protocol Generator 104 uses structural, electronic and physicochemical diversity criteria and, optionally, receptor fit criteria to generate an initial DirectedDiversity Chemical Library 208. The initial choice is aimed at maximizing the information content of the resulting chemical library within the domain of interest, as measured by the presence of chemical functionalities, hydrogen bonding characteristics, electronic properties, topological and topographical parameters, etc. - The operation of the
Synthesis Protocol Generator 104 while performingstep 314 shall now be further described with reference to a flowchart shown in FIG. 6. - As represented by
step 602, theSynthesis Protocol Generator 104 analyzes the Structure-Activity Data 210 pertaining to the compounds in the directeddiversity library 208 and the historical structure-activity data 212 obtained from previous iterations, and constructs structure-activity models with enhanced predictive and discriminating ability. - In a preferred embodiment of the present invention,
step 602 involves the construction of functional structure-activity models, and in particular models wherein the activity is represented as a linear combination of basis functions of one or more molecular features. Such molecular features may include topological indices, physicochemical properties, electrostatic field parameters, volume and surface parameters, etc., and their number may range from a few tens to tens of thousands. The coefficients are preferably determined using linear regression techniques. If many features are used, linear regression may be combined with principal component analysis, which is a well known technique for selecting the most important set of features from a large table. - In a preferred embodiment of the present invention, the basis functions used in the linear regression procedure are selected using a well known genetic function approximation (GFA) algorithm as described in Rogers and Hopfinger,J. Chem. Inf. Comput. Sci. 34:854 (1994), which is herein incorporated by reference in its entirety. In the GFA algorithm, a structure-activity model is represented as a linear string which encodes the features and basis functions employed by the model. A population of linearly encoded structure-activity models is then initialized by a random process, and allowed to evolve through the repeated application of genetic operators, such as crossover, mutation and selection. Selection is based on the relative fitness of the models, as measured by a least squares error procedure, for example. Friedman's lack-of-fit algorithm, described in J. Friedman, Technical Report No. 102, Laboratory for Computational Statistics, Department of Statistics, Stanford University, Stanford, Calif., November 1988, herein incorporated by reference in its entirety, or other suitable metrics well known to persons skilled in the art, may also be used. GFA can build models using linear polynomials as well as higher-order polynomials, splines and Gaussians. Upon completion, the procedure yields a population of models, ranked according to their fitness score.
- The present invention employs a plurality of analytic filters (represented by
steps 604 and 606) to intelligently select reagents (from the Reagent Repository 114) to use during the next iteration, and to more intelligently select compounds to synthesize during the next iteration. The use of such analytic filters increases the probability that the compounds ultimately selected for synthesis during the next iteration will exhibit improved activity/properties. Since the method only synthesizes and analyzes compounds which have a high probability of having the desired activity/properties 214, the present invention is much more efficient, effective, and expedient than conventional lead generation processes. - As represented by
step 604, theSynthesis Protocol Generator 104 applies a first sequence of analytic filters to identify candidate reagents from theReagent Repository 114 which are appropriate for the generation of the directed diversity chemical library for the next iteration. Such filters may identify and select reagents based on a number of factors, including (but not limited to) the cost of the reagents, the presence or absence of certain functional groups and/or hydrogen bonding characteristics, conformational flexibility, predicted receptor fit, etc. - As represented by
step 606, theSynthesis Protocol Generator 104 generates a list of compounds based on the reagents selected instep 604. Each of these compounds incorporates one or more of the reagents identified instep 604 . In one embodiment of the invention, theSynthesis Protocol Generator 104 generates the list of compounds by combining these reagents in every possible way for a given compound length, such as three (in which case the compounds in the list would be trimers). - Not all of these compounds in the list will be synthesized during the next iteration. The
Synthesis Protocol Generator 104 instep 606 applies a second sequence of analytic filters to identify candidate compounds from the list of compounds which are appropriate for the generation of the DirectedDiversity Chemical Library 208 for the next iteration. These analytic filters base their analysis on a number of factors, including (but not limited to) total volume and surface area, conformational flexibility, receptor complementarity, etc. These analytic filters may also base their analysis on whether a compound was previously successfully or unsuccessfully synthesized (as indicated by thechemical synthesis indicia 718, described above). According to an embodiment of the present invention, the candidate compounds identified by operation of the first and second sequences of filters are synthesized during the next iteration to generate a new DirectedDiversity Chemical Library 208. - According to an alternate embodiment of the present invention, the primary use of the first and second sequence of filters, particularly the filters employed in
step 606, is to eliminate unsuitable compounds from further consideration, rather than to select a set of compounds to synthesize for the next iteration. In this alternate embodiment, the selection of a set of compounds to synthesize for the next iteration is performed instep 608. The set of compounds determined instep 608 is an optimal or near-optimal one. - As represented by
step 608, theSynthesis Protocol Generator 104 ranks the candidate compounds identified instep 606, individually or in combination, according to their predicted ability to (1) exhibit improved activity/properties, (2) test the validity of the current structure-activity models, and/or (3) discriminate between the various structure-activity models. The candidate compounds may also be ranked according to their predicted three-dimensional receptor fit. The phrase “individually or in combination” means that theSynthesis Protocol Generator 104 analyzes and ranks the candidate compounds each standing alone, or, alternatively, analyzes and ranks sets of the candidate compounds. - In a preferred embodiment of the present invention, the highest-ranking models identified in
step 602 are used instep 608 to select a set of compounds which, as a set, best satisfy the following requirements: (1) exhibit improved activity as predicted by the highest ranking structure-activity models, (2) test the validity of the highest ranking structure-activity models, and/or (3) discriminate between the highest ranking structure-activity models. Requirements (2) and (3) allow for the selection of compounds which need not necessarily exhibit improved activity but, rather, prove or disprove some of the highest ranking structure-activity models, or discriminate most effectively between them. In other words, requirements (2) and (3) enable the elaboration or improvement of the models from one iteration to the next. The final set of compounds may contain compounds which satisfy one, two or all three of the conditions listed above. Which requirement is emphasized in any iteration depends on the amount and quality of structure-activity data, the predictive power of the current structure-activity models, and how closely the activity/properties of the compounds in the last directed diversity chemical library match the desired activity/properties. Typically, as more and more directed diversity chemical libraries are generated, emphasis will shift from requirements (2) and (3) to requirement (1). - The task in
step 608 of selecting the optimal set of compounds for the next directed diversity chemical library involves a search over the entire set of subsets of the candidate compounds (identified during step 606), wherein each subset has k members, where k may vary from one subset to the next and is preferably within the following range: 1000≦k≦5000. Given a list of n compounds produced duringstep 606, the present invention instep 608 identifies which subset of k compounds best satisfies requirements (1), (2) and (3) outlined above. The number of distinct k-subsets of an n-set S is given by EQ. 1: - where k1 and k2 represent the minimum and maximum number of members in a subset, respectively. As indicated above, k1is preferably equal to 1000 and k2 is preferably equal to 5000. This task is combinatorially explosive, i.e., in all but the simplest cases, N is far too large to allow for the construction and evaluation of each individual subset given current data processing technology. As a result, a variety of stochastic modeling techniques can be employed, which are capable of providing good approximate solutions to combinatorial problems in realistic time frames. However, the present invention envisions and includes the construction and evaluation of each individual subset once computer technology advances to an appropriate point.
- In a preferred embodiment of the present invention, in
step 608 each subset of candidate compounds is represented as a binary string which uniquely encodes the number and indices of the candidate compounds comprising the subset. A population of binary encoded subsets is then initialized by a random process, and allowed to evolve through the repeated application of genetic operators, such as crossover, mutation and selection. Selection is based on the relative fitness of the subsets, as measured by their ability to satisfy requirements (1), (2) and (3) discussed above. Upon completion, the present invention yields a population of subsets, ranked according to their ability to satisfy requirements (1), (2) and (3). The highest ranking set is then processed in accordance withstep 610. - In a preferred embodiment of the present invention, candidate compounds may also be ranked according to their predicted three-dimensional receptor fit. This is conceptually illustrated in FIG. 10, wherein candidate trimer compounds are generated in
step 606 from available building blocks (reagents) A, B, and C (identified in step 604), to produce a list of candidate compounds. These candidate compounds are then evaluated and ranked instep 608 based on their three-dimensional receptor complementarity as well as other criteria (as described herein). FIG. 10 depicts, for illustrative purposes, anexample candidate compound 1004 interacting with a three-dimensional receptor map 1002. The highest ranking set 1006 is then processed in accordance withstep 610. - As represented by
step 610, based on the rankings determined instep 608, theSynthesis Protocol Generator 104 generates a list of compounds to be synthesized during the next iteration, and a list of reagents which, when combined, will produce these compounds, and the manner in which these reagents are to be combined. TheSynthesis Protocol Generator 104 also generates a description of how the compounds are to be distributed amongst the individual wells of the DirectedDiversity Chemical Library 208. Upon the creation of this data,step 314 is complete, and control passes to step 316 (FIG. 3). - Referring again to FIG. 3, in
step 316 theSynthesis Protocol Generator 104 generates robotic synthesis instructions 204 (flowarrow 250 in FIG. 2) which, when executed by theChemical Synthesis Robot 112, enable theChemical Synthesis Robot 112 to robotically synthesize (duringstep 304 of the next iteration of flowchart 302) the chemical compounds from selected combinations ofparticular reagents 206 from theReagent Repository 114, as specified instep 314. Such chemical compounds collectively represent a new DirectedDiversity Chemical Library 208. The operation of theSynthesis Protocol Generator 104 while performingstep 316 shall now be described with reference to a flowchart shown in FIG. 5. - As represented by
step 504, theSynthesis Protocol Generator 104 predicts the molecular mass and structure of the compounds identified instep 314 using well known procedures. - As represented by
step 508, theSynthesis Protocol Generator 104 assigns a unique label to each of the compounds. Preferably, compounds are stored in 96 well plates, and each unique label is associated with a code that references the wells and plates in which the compound is stored. The purpose of these labels is to track the synthesis, analysis and storage of each individual compound and its associated data. TheSynthesis Protocol Generator 104 creates a record in the Structure-Activity Database 122 for each compound. In practice, for each compound, theSynthesis Protocol Generator 104 creates a record in each database of the Structure-Activity Database 122 (see FIG. 7). These records preferably have the format shown in FIG. 8. TheSynthesis Protocol Generator 104 stores the labels and the predicted mass and structure information (determined in step 504) associated with the compounds in thethird field 808 of these new records. - In
step 510, theSynthesis Protocol Generator 104 generatesrobotic synthesis instructions 204 to synthesize the chemical compounds identified instep 314. The manner in which theSynthesis Protocol Generator 104 generates suchrobotic synthesis instructions 204 is implementation dependent and is contingent on the particular characteristics of the chemical synthesis robot which is used in thelead generation system 102. The manner in which theSynthesis Protocol Generator 104 generates therobotic synthesis instructions 204 will be apparent to persons skilled in the relevant art. - The performance of
step 316 is complete after the completion ofstep 510. Then, control passes to step 304 (FIG. 3) to begin the next iteration offlowchart 302. - In summary, the present invention is a system and method for automatically generating chemical compounds having desired properties. It should be noted that the terms and phrases “automatically” and “computer controlled” (and the like) as used herein mean that the present invention is capable of operating without human intervention. This is achieved by using automated devices, such as computers and robots. However, it should be understood that the present invention allows and envisions human intervention (i.e., operator aid, operator input, and/or operator control), particularly when selecting compounds for synthesis during the next iteration, and when generating robotic synthesis instructions. Thus, the phrase “computer control” does not rule out the possibility that optional human intervention may be involved in the process. For example, the robotic synthesis instructions may be generated manually in accordance with well known procedures using information provided by the
Synthesis Protocol Generator 104. Such human intervention is allowed but optional; the present invention can operate without any human intervention. - In an alternative embodiment of the present invention, a plurality of
systems 102 operate in parallel to generate and analyze lead compounds. This is called distributed directed diversity. Thesystems 102 are preferably centrally controlled by a master computer system (not shown). Details of this master computer system will be apparent to persons skilled in the relevant art. - One example of the present invention is directed towards the generation and analysis of libraries of thrombin inhibitors. This example shall now be discussed.
- Thrombin is a serine protease involved in both the blood coagulation cascade and platelet activation. When the circulatory system is injured, a cascade of reactions is initiated which leads to the production of thrombin. Thrombin catalyzes the conversion of fibrinogen to fibrin, which forms polymers, and the activation of factor XIII, which catalyzes fibrin crosslinking leading to the formation of fibrin clots. Thrombin also activates the thrombin receptor, which together with other signals induces platelet aggregation, adhesion and activation, and the formation of haemostatic plugs. Aberrant activation or regulation of the coagulation cascade is a major cause of morbidity and mortality in numerous diseases of the cardiovascular system and their associated surgical treatment. Current medical opinion holds that a triad of treatment regimes, including thrombolytic, antiplatelet and anticoagulant therapy, should be used in a variety of cardiac diseases, including recurrent acute myocardial infarction, peripheral arterial disease, atrial fibrillation and the prevention of thromboembolic complications during valvular replacement, orthopedic surgery and percutaneous angioplasty. There is also an unmet therapeutic need for orally active anticoagulants in deep vein thrombosis. Since thrombin catalyzes the terminal step in the clotting cascade, and also plays a major role in platelet activation, thrombin inhibitors should prove therapeutically effective as anticoagulants, and should additionally possess antiplatelet activity.
- In the example being considered herein, the desired bioactivity property is potent inhibition of the thrombin enzyme which is involved in blood clotting. Competitive inhibition of thrombin would prevent both the coagulation and platelet activation processes mediated by thrombin. However, many other proteases in blood and other tissues have specificity profiles similar to thrombin. In particular, plasmin and tissue plasminogen activator, which promote the hydrolysis of fibrin clots and thus have functions crucial to the elimination of circulatory system occlusions, are proteases with primary specificities similar to thrombin. It is also desirable that therapeutically useful thrombin inhibitors do not inhibit these proteases or other enzymes involved in fibrinolysis. Therefore, the properties which are to be optimized include potent thrombin inhibition, but weak or no inhibition of enzymes such as plasmin, tissue plasminogen activator and urokinase.
- Each thrombin inhibitor generated by the present invention preferably comprises three sites of variable structure. The use of thrombin inhibitors having three sites is based on the goal, in medicinal drug research, of obtaining a great deal of diversity (both functional and structural) while minimizing molecular space and weight. Trimers are preferably used since, generally, trimers are smaller and lighter than compounds comprising greater numbers of units, such as tetrameric compounds and pentameric compounds. Obtaining drugs with minimum size and molecular weight is an advantage because it generally minimizes cost and maximizes oral bioavailability.
- The present example (shown in FIG. 12) is directed towards the generation and analysis of libraries of thrombin inhibitors of
type 1202 related to D-Phe-Pro-Arg 1204, wherein the initial directed diversity library is composed of Y-proline-Z, where Y may be one of ten D-Phe substitutes and Z one of 100-500 commercially available primary amines from aReagent Repository 114. The choice of amines Z and D-Phe substitutes Y is determined under computer control using theSynthesis Protocol Generator 104. The D-Phe substitutes may be derived from any carboxylic acid or sulfonic acid for compounds oftype 1206 or, separately, may be a primary or secondary amine linked to the peptide backbone as a urea for compounds oftype 1208. Preferably, the directeddiversity library 208 for compounds oftype 1206 is assembled by theChemical Synthesis Robot 112 using well known solid phase methods and is released as mixtures of 10 compounds per well in a 96 well format in accordance with therobotic synthesis instructions 204 received from theSynthesis Protocol Generator 104. The initial directeddiversity library 208 is assembled using one amine Z and ten D-Phe variants Y per well. More than one 96 well plate may be used, and the resulting directeddiversity library 208 may contain 1000-5000 members. Thelibrary 208 is then submitted to theanalysis robot 116, which analyses thelibrary 208 and generates data pertaining thereto that can be used to evaluate the degree of inhibition of thrombin and other enzymes of interest (such data is called Structure-Activity Data 210). - Based on criteria set forth in the desired activity/property profile214 (FIG. 2) and the
SAR data 210 obtained from the initial directed diversity library, the second iteration directed diversity library is generated using the ten best amines Z. The second iteration directeddiversity library 208 is synthesized using solid phase methods and is released as one compound per well in a 96 well format in accordance with therobotic synthesis instructions 204 received from theSynthesis Protocol Generator 104. The directeddiversity library 208 is generated from the ten selected amines Z (one amine per well) using D-Phe and D-Phe substitutes Y producing one D-Phe or D-Phe variant per well. This directeddiversity library 208 thus contains 100 members. Thelibrary 208 is then submitted to theanalysis robot 116, to evaluate the degree of inhibition of thrombin and other enzymes of interest (as represented by SAR data 210). This establishes the most active members of the directeddiversity library 208 as defined by the criteria set forth in the desiredproperty profile 214. - A third iteration directed diversity library is then assembled based on
SAR data 210 obtained from the second iteration library as defined by the criteria set forth in the desiredproperty profile 214 using the ten best amines Z and additional 100-500 D-Phe substitutes Y chosen under computer control. The D-Phe substitute Y may be derived from carboxylic acids or sulfonic acids. The directeddiversity library 208 is assembled using well known solid phase methods and released as mixtures of ten compounds per well in a 96 well format according to therobotic synthesis instructions 204 received from theSynthesis Protocol Generator 104. Thus, the third iteration directeddiversity library 208 is assembled from ten amines and 100-500 D-Phe substitutes in a manner analogous to the first iteration directed diversity library to produce a 1000-5000 member library. Thethird iteration library 208 is then submitted to theanalysis robot 116, to evaluate the degree of inhibition of thrombin and other enzymes of interest (as represented by SAR data 210). - Based on criteria set forth in the desired
property profile 214 andSAR data 210 obtained from the third iteration directed diversity library, the fourth iteration directed diversity library is then generated from the 10 most active mixtures in the third iteration directed diversity library. The fourth iteration directeddiversity library 208 is synthesized using solid phase methods analogous to the first iteration directed diversity library and is released as one compound per well in a 96 well format according to therobotic synthesis instructions 204 received from theSynthesis Protocol Generator 104. The fourth iteration directeddiversity library 208 is generated from the ten selected D-Phe variants using the ten amines Z from the third iteration directed diversity library. Thefourth iteration library 208 is then submitted to theanalysis robot 116, to evaluate the degree of inhibition of thrombin and other enzymes of interest (as represented by SAR data 210). This fourth iteration directeddiversity library 208 thus contains 100 members and establishes the most active members of thelibrary 208 as defined by the criteria set forth in the desiredproperty profile 214. - This process may be repeated any number of times (as specified by user input, for example) under computer control.
- Additionally, this iterative process is repeated for
compounds 1208. The new iterations of directeddiversity libraries 208 are related to D-Phe substitutes wherein primary or secondary amines are linked to the peptide backbone as a urea moiety. Four generations of directed diversity libraries are performed as above with these new D-Phe substitutes to produce a new chemically distinct series of chemical leads. - While various embodiments of the present invention have been described above, it should be understood that they have been presented by way of example only, and not limitation. Thus, the breadth and scope of the present invention should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.
Claims (5)
1. A computer based method of automatically generating compounds having a prescribed set of properties, comprising the steps of:
(1) robotically synthesizing, in accordance with robotic synthesis instructions, a directed diversity chemical library comprising a plurality of chemical compounds;
(2) robotically analyzing said chemical compounds to obtain structure-activity data pertaining thereto;
(3) comparing, under computer control, said structure-activity data of said chemical compounds against said prescribed set of properties to identify any of said chemical compounds substantially conforming to said prescribed set of properties;
(4) classifying, under computer control, said identified chemical compounds as lead compounds;
(5) analyzing, under computer control, said structure-activity data of said compounds and historical structure-activity data pertaining to compounds synthesized and analyzed in the past to derive structure-activity models having enhanced predictive and discriminating capabilities;
(6) identifying, under computer control and in accordance with said structure-activity models, reagents from a reagent database that, when combined, will produce a set of compounds predicted to exhibit activity/properties more closely matching said prescribed set of properties;
(7) generating, under computer control, robotic synthesis instructions that, when executed, enable robotic synthesis of said set of compounds; and
(8) repeating steps (1)-(7), wherein step (1) is repeated using said generated robotic synthesis instructions.
2. The method of claim 1 , wherein step (6) comprises the step of:
identifying, under computer control and in accordance with said structure-activity models, reagents from a reagent database that, when combined, will produce a second set of compounds predicted to have a superior ability to validate said structure-activity models, wherein said first and second sets of compounds are not mutually exclusive;
wherein step (7) comprises the step of generating, under computer control, robotic synthesis instructions that, when executed, enable robotic synthesis of said second set of compounds.
3. The method of claim 1 , wherein step (6) comprises the step of:
identifying, under computer control and in accordance with said structure-activity models, reagents from a reagent database that, when combined, will produce a second set of compounds predicted to have a superior ability to discriminate between said structure-activity; models, wherein said first and second sets of compounds are not mutually exclusive;
wherein step (7) comprises the step of generating, under computer control, robotic synthesis instructions that, when executed, enable robotic synthesis of said second set of compounds.
4. The method of claim 1 , wherein step (6) comprises the step of:
identifying, under computer control and in accordance with said structure-activity models, reagents from a reagent database that, when combined, will produce a second set of compounds predicted to have a superior ability to validate said structure-activity models, and a third set of compounds predicted to have a superior ability to discriminate between said structure-activity models, wherein said first, second, and third sets of compounds are not mutually exclusive;
wherein step (7) comprises the step of generating, under computer control, robotic synthesis instructions that, when executed, enable robotic synthesis of said second and third set of compounds.
5. The method of claim 1 , wherein step (6) comprises the step of:
identifying, under computer control and in accordance with said structure-activity models, reagents from a reagent database that, when combined, will produce a second set of compounds predicted to have superior three-dimensional receptor fit, wherein said first and second sets of compounds are not mutually exclusive;
wherein step (7) comprises the step of generating, under computer control, robotic synthesis instructions that, when executed, enable robotic synthesis of said second set of compounds.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US10/188,801 US20030033088A1 (en) | 1994-09-16 | 2002-07-05 | Method of generating chemical compounds having desired properties |
Applications Claiming Priority (6)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
US08/306,915 US5463564A (en) | 1994-09-16 | 1994-09-16 | System and method of automatically generating chemical compounds with desired properties |
US08/535,822 US5574656A (en) | 1994-09-16 | 1995-09-28 | System and method of automatically generating chemical compounds with desired properties |
US08/698,246 US5684711A (en) | 1994-09-16 | 1996-08-15 | System, method, and computer program for at least partially automatically generating chemical compounds having desired properties |
US08/904,737 US5901069A (en) | 1994-09-16 | 1997-08-01 | System, method, and computer program product for at least partially automatically generating chemical compounds with desired properties from a list of potential chemical compounds to synthesize |
US09/213,156 US6434490B1 (en) | 1994-09-16 | 1998-12-17 | Method of generating chemical compounds having desired properties |
US10/188,801 US20030033088A1 (en) | 1994-09-16 | 2002-07-05 | Method of generating chemical compounds having desired properties |
Related Parent Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US09/213,156 Division US6434490B1 (en) | 1994-09-16 | 1998-12-17 | Method of generating chemical compounds having desired properties |
Publications (1)
Publication Number | Publication Date |
---|---|
US20030033088A1 true US20030033088A1 (en) | 2003-02-13 |
Family
ID=23187448
Family Applications (6)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US08/306,915 Expired - Lifetime US5463564A (en) | 1994-09-16 | 1994-09-16 | System and method of automatically generating chemical compounds with desired properties |
US08/535,822 Expired - Lifetime US5574656A (en) | 1994-09-16 | 1995-09-28 | System and method of automatically generating chemical compounds with desired properties |
US08/698,246 Expired - Lifetime US5684711A (en) | 1994-09-16 | 1996-08-15 | System, method, and computer program for at least partially automatically generating chemical compounds having desired properties |
US08/904,737 Expired - Lifetime US5901069A (en) | 1994-09-16 | 1997-08-01 | System, method, and computer program product for at least partially automatically generating chemical compounds with desired properties from a list of potential chemical compounds to synthesize |
US09/213,156 Expired - Lifetime US6434490B1 (en) | 1994-09-16 | 1998-12-17 | Method of generating chemical compounds having desired properties |
US10/188,801 Abandoned US20030033088A1 (en) | 1994-09-16 | 2002-07-05 | Method of generating chemical compounds having desired properties |
Family Applications Before (5)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US08/306,915 Expired - Lifetime US5463564A (en) | 1994-09-16 | 1994-09-16 | System and method of automatically generating chemical compounds with desired properties |
US08/535,822 Expired - Lifetime US5574656A (en) | 1994-09-16 | 1995-09-28 | System and method of automatically generating chemical compounds with desired properties |
US08/698,246 Expired - Lifetime US5684711A (en) | 1994-09-16 | 1996-08-15 | System, method, and computer program for at least partially automatically generating chemical compounds having desired properties |
US08/904,737 Expired - Lifetime US5901069A (en) | 1994-09-16 | 1997-08-01 | System, method, and computer program product for at least partially automatically generating chemical compounds with desired properties from a list of potential chemical compounds to synthesize |
US09/213,156 Expired - Lifetime US6434490B1 (en) | 1994-09-16 | 1998-12-17 | Method of generating chemical compounds having desired properties |
Country Status (9)
Country | Link |
---|---|
US (6) | US5463564A (en) |
EP (1) | EP0781436A4 (en) |
JP (1) | JPH10505832A (en) |
AU (1) | AU688598B2 (en) |
CA (1) | CA2199264A1 (en) |
HU (1) | HUT77914A (en) |
IL (1) | IL115292A (en) |
TW (1) | TW420779B (en) |
WO (1) | WO1996008781A1 (en) |
Cited By (19)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20020048610A1 (en) * | 2000-01-07 | 2002-04-25 | Cima Michael J. | High-throughput formation, identification, and analysis of diverse solid-forms |
US20020098518A1 (en) * | 2000-01-07 | 2002-07-25 | Douglas Levinson | Rapid identification of conditions, compounds, or compositions that inhibit, prevent, induce, modify, or reverse transitions of physical state |
US20020177167A1 (en) * | 2000-01-07 | 2002-11-28 | Levinson Douglas A. | Method and system for planning, performing, and assessing high-throughput screening of multicomponent chemical compositions and solid forms of compounds |
US20020183938A1 (en) * | 2000-04-07 | 2002-12-05 | Kobylecki Ryszard Jurek | Investigating different physical and/or chemical forms of materials |
US20030059837A1 (en) * | 2000-01-07 | 2003-03-27 | Levinson Douglas A. | Method and system for planning, performing, and assessing high-throughput screening of multicomponent chemical compositions and solid forms of compounds |
US20030106492A1 (en) * | 2001-09-07 | 2003-06-12 | Douglas Levinson | Apparatus and method for high-throughput preparation, visualization and screening of compositions |
US20030138940A1 (en) * | 2000-01-07 | 2003-07-24 | Lemmo Anthony V. | Apparatus and method for high-throughput preparation and characterization of compositions |
US20040105817A1 (en) * | 2002-10-30 | 2004-06-03 | Sylvain Gilat | Identifying therapeutic compounds based on their physical-chemical properties |
US20050130220A1 (en) * | 2000-01-07 | 2005-06-16 | Transform Pharmaceuticals, Inc. | Apparatus and method for high-throughput preparation and spectroscopic classification and characterization of compositions |
US20060129329A1 (en) * | 2001-04-09 | 2006-06-15 | Kobylecki Ryszard J | Investigating different physical and/or chemical forms of materials |
US20070021929A1 (en) * | 2000-01-07 | 2007-01-25 | Transform Pharmaceuticals, Inc. | Computing methods for control of high-throughput experimental processing, digital analysis, and re-arraying comparative samples in computer-designed arrays |
US20070020662A1 (en) * | 2000-01-07 | 2007-01-25 | Transform Pharmaceuticals, Inc. | Computerized control of high-throughput experimental processing and digital analysis of comparative samples for a compound of interest |
CN110277144A (en) * | 2018-03-15 | 2019-09-24 | 国际商业机器公司 | Have the new chemical compound of desirable properties to construct the new chemical structure for synthesis using the chemical data creation of accumulation |
WO2019236761A1 (en) * | 2018-06-06 | 2019-12-12 | Syngulon Sa | Engineering antimicrobial peptides |
WO2020236314A1 (en) * | 2019-05-21 | 2020-11-26 | The Regents Of The University Of Michigan | Property modulation with chemical transformations |
US10957419B2 (en) | 2016-08-01 | 2021-03-23 | Samsung Electronics Co., Ltd. | Method and apparatus for new material discovery using machine learning on targeted physical property |
US10998087B2 (en) * | 2016-08-25 | 2021-05-04 | The Government of the United States of Amercia as represented by the Secretary of Homeland Security | Systems and methodologies for desigining simulant compounds |
US11581067B2 (en) | 2018-01-17 | 2023-02-14 | Samsung Electronics Co., Ltd. | Method and apparatus for generating a chemical structure using a neural network |
WO2023165898A1 (en) * | 2022-03-03 | 2023-09-07 | Cytiva Sweden Ab | Method and device for synthesizing molecules |
Families Citing this family (318)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CA2012139C (en) * | 1990-03-08 | 2004-01-13 | Michael P. Teter | Apparatus and method for predicting physical and chemical properties of materials |
US5703792A (en) * | 1993-05-21 | 1997-12-30 | Arris Pharmaceutical Corporation | Three dimensional measurement of molecular diversity |
NZ267843A (en) * | 1993-05-27 | 1997-10-24 | Selectide Corp | Libraries of synthetic test compound attached to separate phase synthesis supports |
US6087186A (en) | 1993-07-16 | 2000-07-11 | Irori | Methods and apparatus for synthesizing labeled combinatorial chemistry libraries |
US20060277017A1 (en) * | 1993-11-04 | 2006-12-07 | Sproch Norman K | Method for the characterization of the three-dimensional structure of proteins employing mass spectrometric analysis and computational feedback modeling |
US7047171B1 (en) * | 1995-12-08 | 2006-05-16 | Sproch Norman K | Method for the characterization of the three-dimensional structure of proteins employing mass spectrometric analysis and computational feedback modeling |
US5577239A (en) * | 1994-08-10 | 1996-11-19 | Moore; Jeffrey | Chemical structure storage, searching and retrieval system |
US5463564A (en) | 1994-09-16 | 1995-10-31 | 3-Dimensional Pharmaceuticals, Inc. | System and method of automatically generating chemical compounds with desired properties |
CA2204912C (en) * | 1994-11-10 | 2005-01-04 | David Sarnoff Research Center, Inc. | Liquid distribution system |
US5585069A (en) * | 1994-11-10 | 1996-12-17 | David Sarnoff Research Center, Inc. | Partitioned microelectronic and fluidic device array for clinical diagnostics and chemical synthesis |
US5985119A (en) * | 1994-11-10 | 1999-11-16 | Sarnoff Corporation | Electrokinetic pumping |
US5603351A (en) | 1995-06-07 | 1997-02-18 | David Sarnoff Research Center, Inc. | Method and system for inhibiting cross-contamination in fluids of combinatorial chemistry device |
US5712171A (en) | 1995-01-20 | 1998-01-27 | Arqule, Inc. | Method of generating a plurality of chemical compounds in a spatially arranged array |
US5612894A (en) * | 1995-02-08 | 1997-03-18 | Wertz; David H. | System and method for molecular modeling utilizing a sensitivity factor |
WO1996029659A1 (en) * | 1995-03-17 | 1996-09-26 | Kureha Kagaku Kogyo Kabushiki Kaisha | Biochemical information processor, biochemical information processing method, and biochemical information recording medium |
US5657255C1 (en) * | 1995-04-14 | 2002-06-11 | Interleukin Genetics Inc | Hierarchic biological modelling system and method |
US6284459B1 (en) | 1995-04-25 | 2001-09-04 | Discovery Partners International | Solid support matrices with memories and combinatorial libraries therefrom |
US6416714B1 (en) | 1995-04-25 | 2002-07-09 | Discovery Partners International, Inc. | Remotely programmable matrices with memories |
US5874214A (en) | 1995-04-25 | 1999-02-23 | Irori | Remotely programmable matrices with memories |
US5925562A (en) * | 1995-04-25 | 1999-07-20 | Irori | Remotely programmable matrices with memories |
US6331273B1 (en) | 1995-04-25 | 2001-12-18 | Discovery Partners International | Remotely programmable matrices with memories |
US6025129A (en) * | 1995-04-25 | 2000-02-15 | Irori | Remotely programmable matrices with memories and uses thereof |
US6100026A (en) * | 1995-04-25 | 2000-08-08 | Irori | Matrices with memories and uses thereof |
US5751629A (en) | 1995-04-25 | 1998-05-12 | Irori | Remotely programmable matrices with memories |
US6017496A (en) | 1995-06-07 | 2000-01-25 | Irori | Matrices with memories and uses thereof |
US5961923A (en) * | 1995-04-25 | 1999-10-05 | Irori | Matrices with memories and uses thereof |
US6329139B1 (en) | 1995-04-25 | 2001-12-11 | Discovery Partners International | Automated sorting system for matrices with memory |
US6120665A (en) * | 1995-06-07 | 2000-09-19 | Chiang; William Yat Chung | Electrokinetic pumping |
WO1997009342A1 (en) * | 1995-09-08 | 1997-03-13 | Scriptgen Pharmaceuticals, Inc. | Screen for compounds with affinity for rna |
US6266622B1 (en) * | 1995-12-13 | 2001-07-24 | Regents Of The University Of California | Nuclear receptor ligands and ligand binding domains |
EP0892963A1 (en) * | 1996-01-26 | 1999-01-27 | David E. Patterson | Method of creating and searching a molecular virtual library using validated molecular structure descriptors |
US6185506B1 (en) * | 1996-01-26 | 2001-02-06 | Tripos, Inc. | Method for selecting an optimally diverse library of small molecules based on validated molecular structural descriptors |
US5880972A (en) * | 1996-02-26 | 1999-03-09 | Pharmacopeia, Inc. | Method and apparatus for generating and representing combinatorial chemistry libraries |
CA2251781A1 (en) | 1996-03-20 | 1997-09-25 | Charles Nicolette | A method for identifying cytotoxic t-cell epitopes |
CA2198433A1 (en) * | 1996-03-22 | 1997-09-23 | Sheila Helen Hobbs Dewitt | Information management system for automated multiple simultaneous synthesis |
US6220743B1 (en) * | 1996-04-05 | 2001-04-24 | The Dow Chemical Co. | Processes and materials selection knowledge-based system |
WO1997037953A1 (en) * | 1996-04-08 | 1997-10-16 | Glaxo Group Ltd. | Mass-based encoding and qualitative analysis of combinatorial libraries |
US5840256A (en) * | 1996-04-09 | 1998-11-24 | David Sarnoff Research Center Inc. | Plate for reaction system |
KR20000011069A (en) | 1996-05-09 | 2000-02-25 | 스리-디멘셔널 파마슈티컬스 인코포레이티드 | Micro-plate thermal shift assay and apparatus for ligand development and multi-variable protein chemistry optimization |
US6044212A (en) * | 1996-05-24 | 2000-03-28 | Advanced Life Sciences, Inc. | Use of automated technology in chemical process research and development |
US20030004653A1 (en) * | 1996-05-24 | 2003-01-02 | Michael Flavin | Automated technology of screening of stationary phases |
US6175816B1 (en) | 1997-05-23 | 2001-01-16 | Advanced Life Sciences, Inc. | Use of automated technology in chemical process research and development |
US5989835A (en) | 1997-02-27 | 1999-11-23 | Cellomics, Inc. | System for cell-based screening |
EP0818744A3 (en) * | 1996-07-08 | 1998-07-08 | Proteus Molecular Design Limited | Process for selecting candidate drug compounds |
US5804436A (en) * | 1996-08-02 | 1998-09-08 | Axiom Biotechnologies, Inc. | Apparatus and method for real-time measurement of cellular response |
US6280967B1 (en) | 1996-08-02 | 2001-08-28 | Axiom Biotechnologies, Inc. | Cell flow apparatus and method for real-time of cellular responses |
US6558916B2 (en) | 1996-08-02 | 2003-05-06 | Axiom Biotechnologies, Inc. | Cell flow apparatus and method for real-time measurements of patient cellular responses |
US5751605A (en) * | 1996-08-15 | 1998-05-12 | Tripos, Inc. | Molecular hologram QSAR |
US7094609B2 (en) | 1996-09-20 | 2006-08-22 | Burstein Technologies, Inc. | Spatially addressable combinatorial chemical arrays in encoded optical disk format |
US6025371A (en) * | 1996-10-28 | 2000-02-15 | Versicor, Inc. | Solid phase and combinatorial library syntheses of fused 2,4-pyrimidinediones |
US6413724B1 (en) | 1996-10-28 | 2002-07-02 | Versicor, Inc. | Solid phase and combinatorial library syntheses of fused 2,4-pyrimidinediones |
KR100454611B1 (en) | 1996-10-30 | 2005-06-10 | 스미또모 가가꾸 고오교오 가부시끼가이샤 | Synthesis experiment automating system, liquid separating treating apparatus and reaction vessel |
CA2270527A1 (en) * | 1996-11-04 | 1998-05-14 | 3-Dimensional Pharmaceuticals, Inc. | System, method, and computer program product for the visualization and interactive processing and analysis of chemical data |
US6453246B1 (en) | 1996-11-04 | 2002-09-17 | 3-Dimensional Pharmaceuticals, Inc. | System, method, and computer program product for representing proximity data in a multi-dimensional space |
US6571227B1 (en) * | 1996-11-04 | 2003-05-27 | 3-Dimensional Pharmaceuticals, Inc. | Method, system and computer program product for non-linear mapping of multi-dimensional data |
AU7624298A (en) * | 1996-12-03 | 1998-06-29 | Graybill, Todd L. | Aminobenzenedicarboxylic acid-based combinatorial libraries |
WO1998024464A1 (en) * | 1996-12-03 | 1998-06-11 | Trustees Of Boston University | Specific antagonists for glucose-dependent insulinotropic polypeptide (gip) |
US5859191A (en) * | 1996-12-05 | 1999-01-12 | The Regents Of The University Of California | Method for the site-specific modification of peptide alpha amines |
US5862514A (en) * | 1996-12-06 | 1999-01-19 | Ixsys, Inc. | Method and means for synthesis-based simulation of chemicals having biological functions |
US6274094B1 (en) | 1997-01-13 | 2001-08-14 | Weller, Iii Harold Norris | Nestable, modular apparatus for synthesis of multiple organic compounds |
US5798526A (en) * | 1997-01-24 | 1998-08-25 | Infrasoft International Llc | Calibration system for spectrographic analyzing instruments |
WO1998046551A1 (en) * | 1997-04-16 | 1998-10-22 | Arqule, Inc. | Synthesis and use of biased arrays |
US6528271B1 (en) * | 1997-06-05 | 2003-03-04 | Duke University | Inhibition of βarrestin mediated effects prolongs and potentiates opioid receptor-mediated analgesia |
US7541151B2 (en) | 1997-06-05 | 2009-06-02 | Duke University | Single-cell biosensor for the measurement of GPCR ligands in a test sample |
US5891646A (en) * | 1997-06-05 | 1999-04-06 | Duke University | Methods of assaying receptor activity and constructs useful in such methods |
US6182016B1 (en) * | 1997-08-22 | 2001-01-30 | Jie Liang | Molecular classification for property prediction |
US5961925A (en) | 1997-09-22 | 1999-10-05 | Bristol-Myers Squibb Company | Apparatus for synthesis of multiple organic compounds with pinch valve block |
US6051029A (en) * | 1997-10-31 | 2000-04-18 | Entelos, Inc. | Method of generating a display for a dynamic simulation model utilizing node and link representations |
EP0918296A1 (en) * | 1997-11-04 | 1999-05-26 | Cerep | Method of virtual retrieval of analogs of lead compounds by constituting potential libraries |
US6068393A (en) * | 1997-11-05 | 2000-05-30 | Zymark Corporation | Robotic system for processing chemical products |
US6073055A (en) * | 1997-11-10 | 2000-06-06 | Basf Corporation | Computerized virtual paint manufacturing and application system |
NZ504483A (en) | 1997-11-12 | 2002-11-26 | Dimensional Pharm Inc | High throughput method for functionally classifying proteins by contacting the protein with different molecules and determining the effect on the proteins stability |
GB9724784D0 (en) * | 1997-11-24 | 1998-01-21 | Biofocus Plc | Method of designing chemical substances |
US6069629A (en) * | 1997-11-25 | 2000-05-30 | Entelos, Inc. | Method of providing access to object parameters within a simulation model |
US6078739A (en) * | 1997-11-25 | 2000-06-20 | Entelos, Inc. | Method of managing objects and parameter values associated with the objects within a simulation model |
JP3571201B2 (en) * | 1997-12-12 | 2004-09-29 | 富士通株式会社 | Database search device and computer-readable recording medium storing database search program |
DE19755516A1 (en) * | 1997-12-13 | 1999-06-17 | Conducta Endress & Hauser | Measuring device for liquid and / or gas analysis and / or for measuring moisture in liquids and / or gases |
FR2773240B1 (en) * | 1997-12-30 | 2002-11-29 | Synt Em | PROCESS FOR PREDICTING, IDENTIFYING AND DESCRIBING MOLECULES LIKELY TO PRESENT RESEARCH BEHAVIOR, ESPECIALLY IN THE FIELD OF PHARMACY AND MOLECULES OBTAINED BY THIS PROCESS |
CA2318969A1 (en) | 1998-01-23 | 1999-07-29 | Mikhail F. Gordeev | Oxazolidinone combinatorial libraries, compositions and methods of preparation |
GB9803466D0 (en) | 1998-02-19 | 1998-04-15 | Chemical Computing Group Inc | Discrete QSAR:a machine to determine structure activity and relationships for high throughput screening |
DE19812210C1 (en) | 1998-03-19 | 1999-05-06 | Siemens Ag | Motor vehicle unauthorised usage prevention device |
US6537504B1 (en) | 1998-04-06 | 2003-03-25 | Li Young | Method and apparatus for concurrent and sequential multi-step reactions for producing a plurality of different chemical compounds |
US20040186071A1 (en) * | 1998-04-13 | 2004-09-23 | Bennett C. Frank | Antisense modulation of CD40 expression |
US20030228597A1 (en) * | 1998-04-13 | 2003-12-11 | Cowsert Lex M. | Identification of genetic targets for modulation by oligonucleotides and generation of oligonucleotides for gene modulation |
US7321828B2 (en) * | 1998-04-13 | 2008-01-22 | Isis Pharmaceuticals, Inc. | System of components for preparing oligonucleotides |
US6253168B1 (en) * | 1998-05-12 | 2001-06-26 | Isis Pharmaceuticals, Inc. | Generation of virtual combinatorial libraries of compounds |
ATE357516T1 (en) * | 1998-05-12 | 2007-04-15 | Isis Pharmaceuticals Inc | MODULATION OF MOLECULAR INTERACTION POSITIONS IN RNA AND OTHER BIOMOLECULES |
EP1077993A4 (en) * | 1998-05-12 | 2004-09-08 | Isis Pharmaceuticals Inc | Generation of combinatorial libraries of compounds corresponding to virtual libraries of compounds |
US6872535B2 (en) | 1998-05-20 | 2005-03-29 | Aventis Pharmaceuticals Inc. | Three-dimensional array of supports for solid-phase parallel synthesis and method of use |
US6541211B1 (en) * | 1998-05-20 | 2003-04-01 | Selectide Corporation | Apparatus and method for synthesizing combinational libraries |
US6713651B1 (en) | 1999-06-07 | 2004-03-30 | Theravance, Inc. | β2-adrenergic receptor agonists |
US6541669B1 (en) | 1998-06-08 | 2003-04-01 | Theravance, Inc. | β2-adrenergic receptor agonists |
WO1999064036A1 (en) * | 1998-06-08 | 1999-12-16 | Advanced Medicine, Inc. | Novel therapeutic agents for macromolecular structures |
CA2319495A1 (en) * | 1998-06-08 | 1999-12-16 | Advanced Medicine, Inc. | Multibinding inhibitors of microsomal triglyceride transferase protein |
JP2002517423A (en) | 1998-06-08 | 2002-06-18 | アドバンスド メディスン インコーポレーテッド | Multiple binding inhibitors of cyclooxygenase-2 |
WO1999064045A1 (en) * | 1998-06-08 | 1999-12-16 | Advanced Medicine, Inc. | Novel therapeutic agents for membrane transporters |
EP1083894A1 (en) | 1998-06-08 | 2001-03-21 | Advanced Medicine, Inc. | MULTIBINDING INHIBITORS OF HMG-CoA REDUCTASE |
US6897305B2 (en) | 1998-06-08 | 2005-05-24 | Theravance, Inc. | Calcium channel drugs and uses |
US6608671B2 (en) * | 1998-07-17 | 2003-08-19 | Vertex Pharmaceuticals (San Diego) Llc | Detector and screening device for ion channels |
US6349160B2 (en) | 1998-07-24 | 2002-02-19 | Aurora Biosciences Corporation | Detector and screening device for ion channels |
WO2000009527A1 (en) * | 1998-08-10 | 2000-02-24 | The Scripps Research Institute | Programmable one-pot oligosaccharide synthesis |
US5993662A (en) * | 1998-08-28 | 1999-11-30 | Thetagen, Inc. | Method of purifying and identifying a large multiplicity of chemical reaction products simultaneously |
WO2000015847A2 (en) * | 1998-09-11 | 2000-03-23 | Gene Logic, Inc. | Genomic knowledge discovery |
DE19843242A1 (en) * | 1998-09-11 | 2000-03-23 | Inst Angewandte Chemie Berlin | Active and/or selective catalysts made from inorganic or organometallic solids used for partial oxidation of propane are manufactured using multistep development process |
BR9803848A (en) * | 1998-10-08 | 2000-10-31 | Opp Petroquimica S A | Inline system for inference of physical and chemical properties, inline system for inference of process variables, and inline control system |
US7101909B2 (en) * | 1998-10-12 | 2006-09-05 | Theravance, Inc. | Calcium channel drugs and uses |
US7199809B1 (en) | 1998-10-19 | 2007-04-03 | Symyx Technologies, Inc. | Graphic design of combinatorial material libraries |
AU1331700A (en) * | 1998-10-28 | 2000-05-15 | Glaxo Group Limited | Pharmacophore fingerprinting in qsar and primary library design |
US6569631B1 (en) | 1998-11-12 | 2003-05-27 | 3-Dimensional Pharmaceuticals, Inc. | Microplate thermal shift assay for ligand development using 5-(4″dimethylaminophenyl)-2-(4′-phenyl)oxazole derivative fluorescent dyes |
ATE292822T1 (en) | 1998-11-13 | 2005-04-15 | Cellomics Inc | METHOD AND SYSTEM FOR EFFICIENTLY OBTAINING AND STORING EXPERIMENTAL DATA |
US6395511B1 (en) | 1998-11-27 | 2002-05-28 | Darwin Discovery, Ltd. | Nucleic acids encoding a novel family of TGF-β binding proteins from humans |
US20040009535A1 (en) | 1998-11-27 | 2004-01-15 | Celltech R&D, Inc. | Compositions and methods for increasing bone mineralization |
AU2368900A (en) * | 1998-12-18 | 2000-07-03 | Symyx Technologies, Inc. | Apparatus and method for characterizing libraries of different materials using x-ray scattering |
DE19902378A1 (en) * | 1999-01-21 | 2000-08-03 | Morphochem Gmbh | Process for the discovery and production of biologically active chemical compounds |
US6720139B1 (en) | 1999-01-27 | 2004-04-13 | Elitra Pharmaceuticals, Inc. | Genes identified as required for proliferation in Escherichia coli |
US6500609B1 (en) | 1999-02-11 | 2002-12-31 | Scynexis Chemistry & Automation, Inc. | Method and apparatus for synthesizing characterizing and assaying combinatorial libraries |
US6693202B1 (en) | 1999-02-16 | 2004-02-17 | Theravance, Inc. | Muscarinic receptor antagonists |
US6904423B1 (en) | 1999-02-19 | 2005-06-07 | Bioreason, Inc. | Method and system for artificial intelligence directed lead discovery through multi-domain clustering |
US6864235B1 (en) | 1999-04-01 | 2005-03-08 | Eva A. Turley | Compositions and methods for treating cellular response to injury and other proliferating cell disorders regulated by hyaladherin and hyaluronans |
US6911429B2 (en) * | 1999-04-01 | 2005-06-28 | Transition Therapeutics Inc. | Compositions and methods for treating cellular response to injury and other proliferating cell disorders regulated by hyaladherin and hyaluronans |
WO2000062251A1 (en) * | 1999-04-09 | 2000-10-19 | Merck & Co., Inc. | Chemical structure similarity ranking system and computer-implemented method for same |
US7219020B1 (en) | 1999-04-09 | 2007-05-15 | Axontologic, Inc. | Chemical structure similarity ranking system and computer-implemented method for same |
CA2370283C (en) * | 1999-04-16 | 2012-07-17 | Entelos, Inc. | Method and apparatus for conducting linked simulation operations utilizing a computer-based system model |
WO2000065421A2 (en) * | 1999-04-26 | 2000-11-02 | Novascreen Biosciences Corporation | Receptor selectivity mapping |
US20040117125A1 (en) * | 1999-04-26 | 2004-06-17 | Hao Chen | Drug discovery method and apparatus |
US20030138372A1 (en) * | 1999-04-28 | 2003-07-24 | The Research Foundation Of State University Of New York | Method for identifying and synthesizing high dielectric constant perovskites |
US20030083483A1 (en) * | 1999-05-12 | 2003-05-01 | Ecker David J. | Molecular interaction sites of vimentin RNA and methods of modulating the same |
US6969763B1 (en) | 1999-05-12 | 2005-11-29 | Isis Pharmaceuticals, Inc. | Molecular interaction sites of interleukin-2 RNA and methods of modulating the same |
US6485690B1 (en) | 1999-05-27 | 2002-11-26 | Orchid Biosciences, Inc. | Multiple fluid sample processor and system |
US6683115B2 (en) | 1999-06-02 | 2004-01-27 | Theravance, Inc. | β2-adrenergic receptor agonists |
US6593497B1 (en) | 1999-06-02 | 2003-07-15 | Theravance, Inc. | β2-adrenergic receptor agonists |
US6479498B1 (en) | 1999-06-04 | 2002-11-12 | Theravance, Inc. | Sodium channel drugs and uses |
US6420560B1 (en) | 1999-06-07 | 2002-07-16 | Theravance, Inc. | H1—histamine receptor antagonists |
US6524863B1 (en) | 1999-08-04 | 2003-02-25 | Scynexis Chemistry & Automation, Inc. | High throughput HPLC method for determining Log P values |
US6413431B1 (en) | 1999-08-10 | 2002-07-02 | Scynexis Chemistry & Automation, Inc. | HPLC method for purifying organic compounds |
US6387273B1 (en) | 1999-08-27 | 2002-05-14 | Scynexis Chemistry & Automation, Inc. | Sample preparation for high throughput purification |
WO2001027622A1 (en) | 1999-10-14 | 2001-04-19 | Bristol-Myers Squibb Company | Crystallographic structure of the androgen receptor ligand binding domain |
WO2001034291A2 (en) | 1999-11-09 | 2001-05-17 | Sri International | High-throughput synthesis, screening and characterization of combinatorial libraries |
US7033840B1 (en) | 1999-11-09 | 2006-04-25 | Sri International | Reaction calorimeter and differential scanning calorimeter for the high-throughput synthesis, screening and characterization of combinatorial libraries |
AU2041901A (en) | 1999-11-09 | 2001-06-06 | Elitra Pharmaceuticals, Inc. | Genes essential for microbial proliferation and antisense thereto |
UA73965C2 (en) | 1999-12-08 | 2005-10-17 | Theravance Inc | b2 ADRENERGIC RECEPTOR ANTAGONISTS |
KR20030003221A (en) * | 1999-12-23 | 2003-01-09 | 엘리트라 파마슈티컬즈, 인코포레이티드 | Genes Identified as Required for Proliferation of E. coli |
US6728641B1 (en) | 2000-01-21 | 2004-04-27 | General Electric Company | Method and system for selecting a best case set of factors for a chemical reaction |
WO2001055951A2 (en) | 2000-01-25 | 2001-08-02 | Cellomics, Inc. | Method and system for automated inference of physico-chemical interaction knowl edge |
WO2001056603A1 (en) * | 2000-02-01 | 2001-08-09 | Tanox, Inc. | Cd40-binding apc-activating molecules |
AU2001234779A1 (en) * | 2000-02-03 | 2001-08-14 | Nanoscale Combinatorial Synthesis, Inc. | Structure identification methods using mass measurements |
US7056477B1 (en) * | 2000-02-03 | 2006-06-06 | Cellular Process Chemistry, Inc. | Modular chemical production system incorporating a microreactor |
US7435392B2 (en) * | 2000-02-03 | 2008-10-14 | Acclavis, Llc | Scalable continuous production system |
US6625585B1 (en) | 2000-02-18 | 2003-09-23 | Bioreason, Inc. | Method and system for artificial intelligence directed lead discovery though multi-domain agglomerative clustering |
US7416524B1 (en) | 2000-02-18 | 2008-08-26 | Johnson & Johnson Pharmaceutical Research & Development, L.L.C. | System, method and computer program product for fast and efficient searching of large chemical libraries |
AU2001241800A1 (en) | 2000-02-29 | 2001-09-12 | 3-Dimensional Pharmaceuticals, Inc. | Method and computer program product for designing combinatorial arrays |
US6907350B2 (en) * | 2000-03-13 | 2005-06-14 | Chugai Seiyaku Kabushiki Kaisha | Method, system and apparatus for handling information on chemical substances |
US7039621B2 (en) | 2000-03-22 | 2006-05-02 | Johnson & Johnson Pharmaceutical Research & Development, L.L.C. | System, method, and computer program product for representing object relationships in a multidimensional space |
US7216113B1 (en) * | 2000-03-24 | 2007-05-08 | Symyx Technologies, Inc. | Remote Execution of Materials Library Designs |
WO2001075790A2 (en) | 2000-04-03 | 2001-10-11 | 3-Dimensional Pharmaceuticals, Inc. | Method, system, and computer program product for representing object relationships in a multidimensional space |
DE10028875A1 (en) * | 2000-06-10 | 2001-12-20 | Hte Gmbh | Automatic formation and iterative optimization of substance library, employs integrated process embracing manufacture, performance testing, and test result analysis |
US7065453B1 (en) | 2000-06-15 | 2006-06-20 | Accelrys Software, Inc. | Molecular docking technique for screening of combinatorial libraries |
CA2415103A1 (en) * | 2000-06-30 | 2002-01-10 | The Regents Of The University Of California | Methods and compounds for modulating nuclear receptor coactivator binding |
US7413714B1 (en) | 2000-07-16 | 2008-08-19 | Ymc Co. Ltd. | Sequential reaction system |
US6584411B1 (en) | 2000-07-26 | 2003-06-24 | Smithkline Beecham Corporation | Methods to facilitate the calculation of yields of reaction products |
US6576472B1 (en) | 2000-07-26 | 2003-06-10 | Smithkline Beecham Corporation | Chemical constructs for solution phase chemistry |
DE10036602A1 (en) * | 2000-07-27 | 2002-02-14 | Cpc Cellular Process Chemistry | Microreactor for reactions between gases and liquids |
JP2004507821A (en) * | 2000-08-22 | 2004-03-11 | 3−ディメンショナル ファーマシューティカルズ, インコーポレイテッド | Methods, systems and computer program products for determining characteristics of combinatorial library products from features of library building blocks |
US20030027286A1 (en) * | 2000-09-06 | 2003-02-06 | Robert Haselbeck | Bacterial promoters and methods of use |
DE10043853A1 (en) * | 2000-09-06 | 2002-03-14 | Merck Patent Gmbh | Process for creating synthetic paths |
US6813615B1 (en) | 2000-09-06 | 2004-11-02 | Cellomics, Inc. | Method and system for interpreting and validating experimental data with automated reasoning |
US6678619B2 (en) * | 2000-09-20 | 2004-01-13 | Victor S. Lobanov | Method, system, and computer program product for encoding and building products of a virtual combinatorial library |
EP1191312A3 (en) * | 2000-09-21 | 2004-12-22 | Tecan Trading AG | System and method for optimization of parameters of liquid-handling instruments |
EP2281840A3 (en) | 2000-10-10 | 2012-05-23 | Genentech, Inc. | Inhibition of complement C5 activation for the treatment and prevention of delayed xenograft or acute vascular rejection |
ZA200302395B (en) * | 2000-10-17 | 2004-03-29 | Applied Research Systems | Method of operating a computer system to perform a discrete substructural analysis. |
US6826487B1 (en) * | 2000-10-25 | 2004-11-30 | General Electric Company | Method for defining an experimental space and method and system for conducting combinatorial high throughput screening of mixtures |
US7319945B1 (en) * | 2000-11-10 | 2008-01-15 | California Institute Of Technology | Automated methods for simulating a biological network |
US6973148B2 (en) * | 2000-11-30 | 2005-12-06 | Adc Telecommunications, Inc. | Clock recovery mechanism |
US6996550B2 (en) * | 2000-12-15 | 2006-02-07 | Symyx Technologies, Inc. | Methods and apparatus for preparing high-dimensional combinatorial experiments |
EP1363736B1 (en) * | 2000-12-18 | 2011-03-02 | Protedyne Corporation | Extruding gel material for gel electrophoresis |
US7085773B2 (en) * | 2001-01-05 | 2006-08-01 | Symyx Technologies, Inc. | Laboratory database system and methods for combinatorial materials research |
US6658429B2 (en) | 2001-01-05 | 2003-12-02 | Symyx Technologies, Inc. | Laboratory database system and methods for combinatorial materials research |
US20020127597A1 (en) * | 2001-01-10 | 2002-09-12 | General Electric Company | Method and apparatus for exploring an experimental space |
US20020143725A1 (en) * | 2001-01-29 | 2002-10-03 | Smith Robin Young | Systems, methods and computer program products for determining parameters for chemical synthesis and for supplying the reagents, equipment and/or chemicals synthesized thereby |
US7250950B2 (en) * | 2001-01-29 | 2007-07-31 | Symyx Technologies, Inc. | Systems, methods and computer program products for determining parameters for chemical synthesis |
US7054757B2 (en) * | 2001-01-29 | 2006-05-30 | Johnson & Johnson Pharmaceutical Research & Development, L.L.C. | Method, system, and computer program product for analyzing combinatorial libraries |
EP1239351A3 (en) * | 2001-02-22 | 2003-04-16 | SmithKline Beecham Corporation | Methods and computer program products for automated experimental design |
DE10108590A1 (en) * | 2001-02-22 | 2002-09-05 | Merck Patent Gmbh | Method for determining pharmaceutically active substances |
EP1386251A4 (en) * | 2001-03-02 | 2005-11-23 | Euro Celtique Sa | Method and apparatus for compounding individualized dosage forms |
US20030013137A1 (en) * | 2001-03-13 | 2003-01-16 | Barak Larry S. | Automated methods of detecting receptor activity |
WO2002075608A1 (en) * | 2001-03-16 | 2002-09-26 | General Electric Company | Method and system for selecting a best case set of factors for a chemical reaction |
JP4071476B2 (en) * | 2001-03-21 | 2008-04-02 | 株式会社東芝 | Semiconductor wafer and method for manufacturing semiconductor wafer |
US7514263B2 (en) | 2001-04-02 | 2009-04-07 | 3M Innovative Properties Company | Continuous process for the production of combinatorial libraries of materials |
CA2442654A1 (en) * | 2001-04-10 | 2002-10-10 | Transtech Pharma, Inc. | Probes, systems, and methods for drug discovery |
ATE405586T1 (en) | 2001-05-08 | 2008-09-15 | Darwin Molecular Corp | METHOD FOR REGULATING IMMUNE FUNCTION IN PRIMATES USING THE FOXP3 PROTEIN |
WO2002093439A1 (en) * | 2001-05-15 | 2002-11-21 | Akzo Nobel N.V. | Method of product specification for a processing chemical |
US20020193979A1 (en) | 2001-05-17 | 2002-12-19 | Paterson Thomas S. | Apparatus and method for validating a computer model |
EP1399475A2 (en) * | 2001-06-07 | 2004-03-24 | F. Hoffmann-La Roche Ag | Mutants of igf binding proteins and methods of production of antagonists thereof |
JP2004537047A (en) * | 2001-06-14 | 2004-12-09 | アナディーズ ファーマスーティカルズ,アイエヌシー. | Methods for screening ligands for target molecules |
JP2004534226A (en) | 2001-06-29 | 2004-11-11 | メソ スケイル テクノロジーズ,エルエルシー | Assay plate, reader system and method for luminescence test measurement |
US20040073380A1 (en) * | 2001-07-10 | 2004-04-15 | Puglisi Joseph D. | Structural targets in hepatittis c virus ires element |
US20030036619A1 (en) * | 2001-07-26 | 2003-02-20 | Chrisman Ray W. | Method for optimizing material transformation |
DK1412487T3 (en) | 2001-07-30 | 2010-08-30 | Meso Scale Technologies Llc | Assay electrodes having immobilized lipid / protein layers and methods for preparing and using these |
US20030216871A1 (en) * | 2001-07-31 | 2003-11-20 | Artem Tcherkassov | Calculating a characteristic property of a molecule by correlation analysis |
EP1878441B1 (en) | 2001-08-17 | 2018-01-24 | Genentech, Inc. | Complement pathway inhibitors binding to C5 and C5a without preventing the formation of C5b |
US20030083824A1 (en) * | 2001-08-31 | 2003-05-01 | General Electric Company | Method and system for selecting a best case set of factors for a chemical reaction |
US7858321B2 (en) * | 2001-09-10 | 2010-12-28 | Meso Scale Technologies, Llc | Methods and apparatus for conducting multiple measurements on a sample |
KR20050034603A (en) * | 2001-10-09 | 2005-04-14 | 3-디멘져널 파마슈티칼즈 인코오포레이티드 | Substituted diphenyloxazoles, the synthesis thereof, and the use thereof as fluorescence probes |
US20040029129A1 (en) * | 2001-10-25 | 2004-02-12 | Liangsu Wang | Identification of essential genes in microorganisms |
DE10156245A1 (en) * | 2001-11-15 | 2003-06-05 | Bayer Ag | Methods for the identification of pharmacophores |
US20030170694A1 (en) * | 2001-12-21 | 2003-09-11 | Daniel Wall | Stabilized nucleic acids in gene and drug discovery and methods of use |
US20040137518A1 (en) * | 2002-01-31 | 2004-07-15 | Lambert Millard Hurst | CRYSTALLIZED PPARa LIGAND BINDING DOMAIN POLYPEPTIDE AND SCREENING METHODS EMPLOYING SAME |
US20030149933A1 (en) * | 2002-02-01 | 2003-08-07 | Marco Falcioni | Graphical design of chemical discovery processes |
FI20020197A0 (en) * | 2002-02-01 | 2002-02-01 | Orion Corp | A combination treatment method for acute myocardial infarction |
US20030182669A1 (en) * | 2002-03-19 | 2003-09-25 | Rockman Howard A. | Phosphoinositide 3-kinase mediated inhibition of GPCRs |
WO2003083609A2 (en) * | 2002-03-25 | 2003-10-09 | Synthematix, Inc. | Systems, methods and computer program products for determining parameters for chemical synthesis |
US20040019432A1 (en) * | 2002-04-10 | 2004-01-29 | Sawafta Reyad I. | System and method for integrated computer-aided molecular discovery |
US20030232369A1 (en) * | 2002-04-17 | 2003-12-18 | Bushnell David A. | Molecular structure of RNA polymerase II |
US20030222905A1 (en) * | 2002-06-04 | 2003-12-04 | Argonaut Technologies, Inc. | Recipe recorder for automated chemistry |
HUP0202551A2 (en) * | 2002-08-01 | 2004-03-29 | Comgenex, Inc. | Chemical biochemical and biological process with chip for minimise and thereof use |
US7632916B2 (en) | 2002-08-02 | 2009-12-15 | 3M Innovative Properties Company | Process to modify polymeric materials and resulting compositions |
US20040082783A1 (en) * | 2002-08-06 | 2004-04-29 | Schafmeister Christian E. | Bis (amino acid) molecular scaffolds |
US20030125548A1 (en) * | 2002-09-13 | 2003-07-03 | Dorit Arad | Molecules derived from mechanism based drug design |
DE60334246D1 (en) | 2002-11-21 | 2010-10-28 | Celltech R & D Inc | MODULATE IMMUNE RESPONSES |
US20040122641A1 (en) * | 2002-12-20 | 2004-06-24 | Lab2Plant, Inc. (An Indiana Corporation) | System and method for chemical process scale-up and preliminary design and analysis |
US7213034B2 (en) * | 2003-01-24 | 2007-05-01 | Symyx Technologies, Inc. | User-configurable generic experiment class for combinatorial materials research |
WO2004074429A2 (en) * | 2003-02-21 | 2004-09-02 | Nuevolution A/S | Method for producing second-generation library |
CA2523961A1 (en) * | 2003-03-24 | 2004-11-11 | Novascreen Biosciences Corporation | Drug discovery method and apparatus |
EP1618372A2 (en) * | 2003-04-14 | 2006-01-25 | Cellular Process Chemistry, Inc. | System and method for determining optimal reaction parameters using continuously running process |
US20050010462A1 (en) * | 2003-07-07 | 2005-01-13 | Mark Dausch | Knowledge management system and methods for crude oil refining |
US7966331B2 (en) * | 2003-08-18 | 2011-06-21 | General Electric Company | Method and system for assessing and optimizing crude selection |
US20050089936A1 (en) * | 2003-10-23 | 2005-04-28 | Jianping Cai | Combinatorial library of 3-aryl-1H-indole-2-carboxylic acid amides |
US7396940B2 (en) * | 2003-10-23 | 2008-07-08 | Hoffmann-La Roche Inc. | Combinatorial library of 3-aryl-1H-indole-2-carboxylic acid |
US20050130229A1 (en) * | 2003-12-16 | 2005-06-16 | Symyx Technologies, Inc. | Indexing scheme for formulation workflows |
CA2563413A1 (en) * | 2004-04-15 | 2005-10-27 | Thermo Crs Ltd. | Method and system for drug screening |
US20050278308A1 (en) * | 2004-06-01 | 2005-12-15 | Barstow James F | Methods and systems for data integration |
GB2414834A (en) * | 2004-06-03 | 2005-12-07 | Mdl Information Systems Inc | Visual programming with automated features |
CN102680440A (en) | 2004-06-07 | 2012-09-19 | 先锋生物科技股份有限公司 | Optical lens system and method for microfluidic devices |
US7702467B2 (en) * | 2004-06-29 | 2010-04-20 | Numerate, Inc. | Molecular property modeling using ranking |
EP1810008A4 (en) * | 2004-10-15 | 2008-09-10 | Signal Pharm Llc | P27 ubiquitination assay and methods of use |
US7977119B2 (en) * | 2004-12-08 | 2011-07-12 | Agilent Technologies, Inc. | Chemical arrays and methods of using the same |
US7818666B2 (en) * | 2005-01-27 | 2010-10-19 | Symyx Solutions, Inc. | Parsing, evaluating leaf, and branch nodes, and navigating the nodes based on the evaluation |
US20060218107A1 (en) * | 2005-03-24 | 2006-09-28 | The University Of Tennessee Research Foundation | Method for controlling a product production process |
EP2392258B1 (en) | 2005-04-28 | 2014-10-08 | Proteus Digital Health, Inc. | Pharma-informatics system |
US7475050B2 (en) * | 2005-06-02 | 2009-01-06 | Agilent Technologies, Inc. | Systems for developing analytical device methods |
WO2007022110A2 (en) * | 2005-08-12 | 2007-02-22 | Symyx Technologies, Inc. | Event-based library process design |
WO2007020658A2 (en) * | 2005-08-17 | 2007-02-22 | Jubilant Biosys Ltd | 'a novel homology model of the glycogen synthase kinase 3 alpha and its uses thereof' |
US9550162B2 (en) * | 2005-09-19 | 2017-01-24 | Intematix Corporation | Printing liquid solution arrays for inorganic combinatorial libraries |
US7711674B2 (en) * | 2005-11-01 | 2010-05-04 | Fuji Xerox Co., Ltd. | System and method for automatic design of components in libraries |
WO2007056889A1 (en) * | 2005-11-15 | 2007-05-24 | Chaoh Shinn Enterprise Co., Ltd | Computer-aided colored paint formula adjusting system and method thereof |
GB0605584D0 (en) * | 2006-03-20 | 2006-04-26 | Olink Ab | Method for analyte detection using proximity probes |
GB0612114D0 (en) * | 2006-06-19 | 2006-07-26 | Cresset Biomolecular Discovery | Method and system for automated iterative drug discovery |
US20100173381A1 (en) * | 2006-12-18 | 2010-07-08 | University Of Massachusetts | Crystal structures of hiv-1 protease inhibitors bound to hiv-1 protease |
US8685666B2 (en) * | 2007-02-16 | 2014-04-01 | The Board Of Trustees Of Southern Illinois University | ARL-1 specific antibodies and uses thereof |
US8114606B2 (en) * | 2007-02-16 | 2012-02-14 | The Board Of Trustees Of Southern Illinois University | ARL-1 specific antibodies |
US20090171592A1 (en) * | 2007-06-12 | 2009-07-02 | Brookhaven Science Associates, Llc | Homology Models of Mammalian Zinc Transporters and Methods of Using Same |
US20100168114A1 (en) * | 2007-06-18 | 2010-07-01 | Yuan-Ping Pang | Invertebrate acetylcholinesterase inhibitors |
DK2192946T3 (en) | 2007-09-25 | 2022-11-21 | Otsuka Pharma Co Ltd | In-body device with virtual dipole signal amplification |
ES2641290T3 (en) | 2007-11-20 | 2017-11-08 | Ionis Pharmaceuticals, Inc | CD40 expression modulation |
US9282927B2 (en) | 2008-04-24 | 2016-03-15 | Invention Science Fund I, Llc | Methods and systems for modifying bioactive agent use |
US9026369B2 (en) | 2008-04-24 | 2015-05-05 | The Invention Science Fund I, Llc | Methods and systems for presenting a combination treatment |
US20100280332A1 (en) * | 2008-04-24 | 2010-11-04 | Searete Llc, A Limited Liability Corporation Of The State Of Delaware | Methods and systems for monitoring bioactive agent use |
US8930208B2 (en) | 2008-04-24 | 2015-01-06 | The Invention Science Fund I, Llc | Methods and systems for detecting a bioactive agent effect |
US9649469B2 (en) * | 2008-04-24 | 2017-05-16 | The Invention Science Fund I Llc | Methods and systems for presenting a combination treatment |
US20100063368A1 (en) * | 2008-04-24 | 2010-03-11 | Searete Llc, A Limited Liability Corporation | Computational system and method for memory modification |
US8606592B2 (en) | 2008-04-24 | 2013-12-10 | The Invention Science Fund I, Llc | Methods and systems for monitoring bioactive agent use |
US8876688B2 (en) | 2008-04-24 | 2014-11-04 | The Invention Science Fund I, Llc | Combination treatment modification methods and systems |
US8682687B2 (en) | 2008-04-24 | 2014-03-25 | The Invention Science Fund I, Llc | Methods and systems for presenting a combination treatment |
US20100130811A1 (en) * | 2008-04-24 | 2010-05-27 | Searete Llc | Computational system and method for memory modification |
US8615407B2 (en) * | 2008-04-24 | 2013-12-24 | The Invention Science Fund I, Llc | Methods and systems for detecting a bioactive agent effect |
US9239906B2 (en) | 2008-04-24 | 2016-01-19 | The Invention Science Fund I, Llc | Combination treatment selection methods and systems |
US9449150B2 (en) | 2008-04-24 | 2016-09-20 | The Invention Science Fund I, Llc | Combination treatment selection methods and systems |
US9662391B2 (en) * | 2008-04-24 | 2017-05-30 | The Invention Science Fund I Llc | Side effect ameliorating combination therapeutic products and systems |
US20100069724A1 (en) * | 2008-04-24 | 2010-03-18 | Searete Llc | Computational system and method for memory modification |
US9064036B2 (en) | 2008-04-24 | 2015-06-23 | The Invention Science Fund I, Llc | Methods and systems for monitoring bioactive agent use |
US9560967B2 (en) | 2008-04-24 | 2017-02-07 | The Invention Science Fund I Llc | Systems and apparatus for measuring a bioactive agent effect |
GB0900425D0 (en) * | 2009-01-12 | 2009-02-11 | Ucb Pharma Sa | Biological products |
CN102458236B (en) | 2009-04-28 | 2016-01-27 | 普罗秋斯数字健康公司 | The Ingestible event marker of high reliability and using method thereof |
WO2011083147A1 (en) | 2010-01-08 | 2011-07-14 | Cemm-Forschungsinstitut Für Molekulare Medizin Gmbh | Wave1 inhibition in the medical intervention of inflammatory diseases and/or infections caused by a pathogen |
GB201004292D0 (en) * | 2010-03-15 | 2010-04-28 | Olink Ab | Assay for localised detection of analytes |
US20130116304A1 (en) | 2010-04-19 | 2013-05-09 | Ernst R. Werner | Tmem195 encodes for tetrahydrobiopterin-dependent alkylglycerol monooxygenase activity |
US8639486B2 (en) * | 2010-06-07 | 2014-01-28 | Indian Institute Of Science | Method for identifying inhibitors of Staphylococcus aureus |
US8538983B2 (en) * | 2010-09-21 | 2013-09-17 | Cambridgesoft Corporation | Systems, methods, and apparatus for facilitating chemical analyses |
US20130224116A1 (en) | 2010-11-05 | 2013-08-29 | TransBio Ltd. | Markers of Endothelial Progenitor Cells and Uses Thereof |
GB201101621D0 (en) | 2011-01-31 | 2011-03-16 | Olink Ab | Method and product |
JP6133789B2 (en) * | 2011-02-14 | 2017-05-24 | カーネギー メロン ユニバーシティ | Machine learning based method, machine readable medium and electronic system for predicting the effect of a compound on an object |
US9447156B2 (en) | 2011-05-17 | 2016-09-20 | St. Jude Children's Research Hospital | Methods and compositions for inhibiting neddylation of proteins |
GB201116092D0 (en) | 2011-09-16 | 2011-11-02 | Bioceros B V | Antibodies and uses thereof |
US9265817B2 (en) | 2011-10-28 | 2016-02-23 | Patrys Limited | PAT-LM1 epitopes and methods for using same |
GB201201547D0 (en) | 2012-01-30 | 2012-03-14 | Olink Ab | Method and product |
US9977876B2 (en) | 2012-02-24 | 2018-05-22 | Perkinelmer Informatics, Inc. | Systems, methods, and apparatus for drawing chemical structures using touch and gestures |
US9603897B2 (en) | 2012-03-12 | 2017-03-28 | Massachusetts Institute Of Technology | Methods for treating tissue damage associated with ischemia with apolipoprotein D |
GB201209239D0 (en) | 2012-05-25 | 2012-07-04 | Univ Glasgow | Methods of evolutionary synthesis including embodied chemical synthesis |
US9446039B2 (en) | 2012-08-27 | 2016-09-20 | Cemm Forschungszentrum Für Molekulare Medizin Gmbh | Aminoheteroaryl compounds as MTH1 inhibitors |
US9535583B2 (en) | 2012-12-13 | 2017-01-03 | Perkinelmer Informatics, Inc. | Draw-ahead feature for chemical structure drawing applications |
US8854361B1 (en) | 2013-03-13 | 2014-10-07 | Cambridgesoft Corporation | Visually augmenting a graphical rendering of a chemical structure representation or biological sequence representation with multi-dimensional information |
WO2014163749A1 (en) | 2013-03-13 | 2014-10-09 | Cambridgesoft Corporation | Systems and methods for gesture-based sharing of data between separate electronic devices |
RS57840B1 (en) | 2013-03-18 | 2018-12-31 | Biocerox Prod Bv | Humanized anti-cd134 (ox40) antibodies and uses thereof |
US9430127B2 (en) * | 2013-05-08 | 2016-08-30 | Cambridgesoft Corporation | Systems and methods for providing feedback cues for touch screen interface interaction with chemical and biological structure drawing applications |
US9751294B2 (en) | 2013-05-09 | 2017-09-05 | Perkinelmer Informatics, Inc. | Systems and methods for translating three dimensional graphic molecular models to computer aided design format |
WO2015020523A1 (en) | 2013-08-07 | 2015-02-12 | Stichting Vu-Vumc | Biomarkers for early diagnosis of alzheimer's disease |
WO2015152724A2 (en) | 2014-04-02 | 2015-10-08 | Stichting Vu-Vumc | Biomarkers for the detection of frontotemporal dementia |
CN104504152B (en) * | 2015-01-09 | 2017-08-29 | 常州三泰科技有限公司 | Improve chemical technology efficiency and the apparatus and method for promoting chemical information to share |
US20160279878A1 (en) * | 2015-03-27 | 2016-09-29 | John AMBIELLI | Rapid synthetic material prototyping process |
US10776712B2 (en) | 2015-12-02 | 2020-09-15 | Preferred Networks, Inc. | Generative machine learning systems for drug design |
US10832800B2 (en) | 2017-01-03 | 2020-11-10 | International Business Machines Corporation | Synthetic pathway engine |
US10430395B2 (en) | 2017-03-01 | 2019-10-01 | International Business Machines Corporation | Iterative widening search for designing chemical compounds |
CA3055172C (en) | 2017-03-03 | 2022-03-01 | Perkinelmer Informatics, Inc. | Systems and methods for searching and indexing documents comprising chemical information |
AR111842A1 (en) | 2017-06-02 | 2019-08-21 | Amgen Inc | PAC1 PEPTIDE ANTAGONISTS |
US11885822B2 (en) * | 2017-06-30 | 2024-01-30 | Sri International | Apparatuses for reaction screening and optimization, and methods thereof |
US11466073B2 (en) | 2017-10-18 | 2022-10-11 | Csl Limited | Human serum albumin variants and uses thereof |
MA51155A (en) | 2017-12-15 | 2020-10-21 | Flagship Pioneering Innovations Vi Llc | COMPOSITIONS CONSISTING OF CIRCULAR POLYRIBONUCLEOTIDES AND THEIR USES |
GB201810944D0 (en) * | 2018-07-04 | 2018-08-15 | Univ Court Univ Of Glasgow | Machine learning |
RU2726899C2 (en) * | 2018-09-10 | 2020-07-16 | Автономная некоммерческая образовательная организация высшего образования "Сколковский институт науки и технологий" | Method of generating random crystal structure using periodic grids database |
AU2020231349A1 (en) | 2019-03-01 | 2021-09-23 | Flagship Pioneering Innovations Vi, Llc | Compositions, methods, and kits for delivery of polyribonucleotides |
KR20210142678A (en) | 2019-03-25 | 2021-11-25 | 플래그쉽 파이어니어링 이노베이션스 브이아이, 엘엘씨 | Compositions comprising modified circular polyribonucleotides and uses thereof |
AU2020292427A1 (en) | 2019-06-14 | 2022-01-06 | Flagship Pioneering Innovations Vi, Llc | Circular RNAs for cellular therapy |
CN114096674A (en) | 2019-06-19 | 2022-02-25 | 旗舰创业创新第六有限责任公司 | Method for administering cyclic polyribonucleotides |
US10515715B1 (en) * | 2019-06-25 | 2019-12-24 | Colgate-Palmolive Company | Systems and methods for evaluating compositions |
WO2021155171A1 (en) | 2020-01-29 | 2021-08-05 | Flagship Pioneering Innovations Vi, Llc | Delivery of compositions comprising circular polyribonucleotides |
WO2022235929A1 (en) | 2021-05-05 | 2022-11-10 | Radius Pharmaceuticals, Inc. | Animal model having homologous recombination of mouse pth1 receptor |
WO2023131726A1 (en) | 2022-01-10 | 2023-07-13 | The University Court Of The University Of Glasgow | Autonomous exploration for the synthesis of chemical libraries |
GB202209476D0 (en) | 2022-06-28 | 2022-08-10 | Univ Court Univ Of Glasgow | Chemical synthesis platform |
Citations (54)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4773099A (en) * | 1985-10-10 | 1988-09-20 | The Palantir Corporation | Pattern classification means for use in a pattern recognition system |
US4811217A (en) * | 1985-03-29 | 1989-03-07 | Japan Association For International Chemical Information | Method of storing and searching chemical structure data |
US4859736A (en) * | 1987-03-30 | 1989-08-22 | Ciba-Geigy Corporation | Synthetic polystyrene resin and its use in solid phase peptide synthesis |
US4908773A (en) * | 1987-04-06 | 1990-03-13 | Genex Corporation | Computer designed stabilized proteins and method for producing same |
US4935875A (en) * | 1987-12-02 | 1990-06-19 | Data Chem, Inc. | Chemical analyzer |
US4939666A (en) * | 1987-09-02 | 1990-07-03 | Genex Corporation | Incremental macromolecule construction methods |
US5010175A (en) * | 1988-05-02 | 1991-04-23 | The Regents Of The University Of California | General method for producing and selecting peptides with specific properties |
US5025388A (en) * | 1988-08-26 | 1991-06-18 | Cramer Richard D Iii | Comparative molecular field analysis (CoMFA) |
US5095443A (en) * | 1988-10-07 | 1992-03-10 | Ricoh Company, Ltd. | Plural neural network system having a successive approximation learning method |
US5155801A (en) * | 1990-10-09 | 1992-10-13 | Hughes Aircraft Company | Clustered neural networks |
US5167009A (en) * | 1990-08-03 | 1992-11-24 | E. I. Du Pont De Nemours & Co. (Inc.) | On-line process control neural network using data pointers |
US5181259A (en) * | 1990-09-25 | 1993-01-19 | The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration | General method of pattern classification using the two domain theory |
US5240680A (en) * | 1991-12-19 | 1993-08-31 | Chiron Corporation | Automated apparatus for use in peptide synthesis |
US5260882A (en) * | 1991-01-02 | 1993-11-09 | Rohm And Haas Company | Process for the estimation of physical and chemical properties of a proposed polymeric or copolymeric substance or material |
US5265030A (en) * | 1990-04-24 | 1993-11-23 | Scripps Clinic And Research Foundation | System and method for determining three-dimensional structures of proteins |
US5270170A (en) * | 1991-10-16 | 1993-12-14 | Affymax Technologies N.V. | Peptide library and screening method |
US5288514A (en) * | 1992-09-14 | 1994-02-22 | The Regents Of The University Of California | Solid phase and combinatorial synthesis of benzodiazepine compounds on a solid support |
US5323471A (en) * | 1991-09-12 | 1994-06-21 | Atr Auditory And Visual Perception Research Laboratories | Pattern recognition apparatus and pattern learning apparatus employing neural net including excitatory element-inhibitory element pair couplings |
US5331573A (en) * | 1990-12-14 | 1994-07-19 | Balaji Vitukudi N | Method of design of compounds that mimic conformational features of selected peptides |
US5434796A (en) * | 1993-06-30 | 1995-07-18 | Daylight Chemical Information Systems, Inc. | Method and apparatus for designing molecules with desired properties by evolving successive populations |
US5436850A (en) * | 1991-07-11 | 1995-07-25 | The Regents Of The University Of California | Method to identify protein sequences that fold into a known three-dimensional structure |
US5442122A (en) * | 1992-11-09 | 1995-08-15 | Shimadzu Corporation | Dibenzosuberyl and dibenzosuberenyl derivatives |
US5463564A (en) * | 1994-09-16 | 1995-10-31 | 3-Dimensional Pharmaceuticals, Inc. | System and method of automatically generating chemical compounds with desired properties |
US5499193A (en) * | 1991-04-17 | 1996-03-12 | Takeda Chemical Industries, Ltd. | Automated synthesis apparatus and method of controlling the apparatus |
US5519635A (en) * | 1993-09-20 | 1996-05-21 | Hitachi Ltd. | Apparatus for chemical analysis with detachable analytical units |
US5524065A (en) * | 1992-02-07 | 1996-06-04 | Canon Kabushiki Kaisha | Method and apparatus for pattern recognition |
US5526281A (en) * | 1993-05-21 | 1996-06-11 | Arris Pharmaceutical Corporation | Machine-learning approach to modeling biological activity for molecular design and to modeling other characteristics |
US5549974A (en) * | 1994-06-23 | 1996-08-27 | Affymax Technologies Nv | Methods for the solid phase synthesis of thiazolidinones, metathiazanones, and derivatives thereof |
US5553225A (en) * | 1994-10-25 | 1996-09-03 | International Business Machines Corporation | Method and apparatus for combining a zoom function in scroll bar sliders |
US5565325A (en) * | 1992-10-30 | 1996-10-15 | Bristol-Myers Squibb Company | Iterative methods for screening peptide libraries |
US5585277A (en) * | 1993-06-21 | 1996-12-17 | Scriptgen Pharmaceuticals, Inc. | Screening method for identifying ligands for target proteins |
US5598510A (en) * | 1993-10-18 | 1997-01-28 | Loma Linda University Medical Center | Self organizing adaptive replicate (SOAR) |
US5602938A (en) * | 1994-05-20 | 1997-02-11 | Nippon Telegraph And Telephone Corporation | Method of generating dictionary for pattern recognition and pattern recognition method using the same |
US5602755A (en) * | 1995-06-23 | 1997-02-11 | Exxon Research And Engineering Company | Method for predicting chemical or physical properties of complex mixtures |
US5621861A (en) * | 1993-07-27 | 1997-04-15 | Matsushita Electric Industrial Co., Ltd. | Method of reducing amount of data required to achieve neural network learning |
US5634017A (en) * | 1994-09-22 | 1997-05-27 | International Business Machines Corporation | Computer system and method for processing atomic data to calculate and exhibit the properties and structure of matter based on relativistic models |
US5635598A (en) * | 1993-06-21 | 1997-06-03 | Selectide Corporation | Selectively cleavabe linners based on iminodiacetic acid esters for solid phase peptide synthesis |
US5670326A (en) * | 1994-04-05 | 1997-09-23 | Pharmagenics, Inc. | Reiterative method for screening combinatorial libraries |
US5679582A (en) * | 1993-06-21 | 1997-10-21 | Scriptgen Pharmaceuticals, Inc. | Screening method for identifying ligands for target proteins |
US5703792A (en) * | 1993-05-21 | 1997-12-30 | Arris Pharmaceutical Corporation | Three dimensional measurement of molecular diversity |
US5712171A (en) * | 1995-01-20 | 1998-01-27 | Arqule, Inc. | Method of generating a plurality of chemical compounds in a spatially arranged array |
US5712564A (en) * | 1995-12-29 | 1998-01-27 | Unisys Corporation | Magnetic ink recorder calibration apparatus and method |
US5734796A (en) * | 1995-09-29 | 1998-03-31 | Ai Ware, Inc. | Self-organization of pattern data with dimension reduction through learning of non-linear variance-constrained mapping |
US5740326A (en) * | 1994-07-28 | 1998-04-14 | International Business Machines Corporation | Circuit for searching/sorting data in neural networks |
US5789160A (en) * | 1990-06-11 | 1998-08-04 | Nexstar Pharmaceuticals, Inc. | Parallel selex |
US5807754A (en) * | 1995-05-11 | 1998-09-15 | Arqule, Inc. | Combinatorial synthesis and high-throughput screening of a Rev-inhibiting arylidenediamide array |
US5811241A (en) * | 1995-09-13 | 1998-09-22 | Cortech, Inc. | Method for preparing and identifying N-substitued 1,4-piperazines and N-substituted 1,4-piperazinediones |
US5832494A (en) * | 1993-06-14 | 1998-11-03 | Libertech, Inc. | Method and apparatus for indexing, searching and displaying data |
US5861532A (en) * | 1997-03-04 | 1999-01-19 | Chiron Corporation | Solid-phase synthesis of N-alkyl amides |
US5908960A (en) * | 1997-05-07 | 1999-06-01 | Smithkline Beecham Corporation | Compounds |
US5933819A (en) * | 1997-05-23 | 1999-08-03 | The Scripps Research Institute | Prediction of relative binding motifs of biologically active peptides and peptide mimetics |
US6014661A (en) * | 1996-05-06 | 2000-01-11 | Ivee Development Ab | System and method for automatic analysis of data bases and for user-controlled dynamic querying |
US6037135A (en) * | 1992-08-07 | 2000-03-14 | Epimmune Inc. | Methods for making HLA binding peptides and their uses |
US6049797A (en) * | 1998-04-07 | 2000-04-11 | Lucent Technologies, Inc. | Method, apparatus and programmed medium for clustering databases with categorical attributes |
Family Cites Families (9)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JP2708456B2 (en) * | 1988-03-31 | 1998-02-04 | 武田薬品工業株式会社 | Automatic synthesis device |
US5147608A (en) * | 1988-04-29 | 1992-09-15 | Millipore Corporation | Apparatus and process for performing repetitive chemical processing |
EP0355628B1 (en) * | 1988-08-24 | 1993-11-10 | Siemens Aktiengesellschaft | Process for chemically decontaminating the surface of a metallic construction element of a nuclear power plant |
IE66205B1 (en) * | 1990-06-14 | 1995-12-13 | Paul A Bartlett | Polypeptide analogs |
US5650489A (en) * | 1990-07-02 | 1997-07-22 | The Arizona Board Of Regents | Random bio-oligomer library, a method of synthesis thereof, and a method of use thereof |
US5573905A (en) * | 1992-03-30 | 1996-11-12 | The Scripps Research Institute | Encoded combinatorial chemical libraries |
EP0892963A1 (en) | 1996-01-26 | 1999-01-27 | David E. Patterson | Method of creating and searching a molecular virtual library using validated molecular structure descriptors |
EP0818744A3 (en) | 1996-07-08 | 1998-07-08 | Proteus Molecular Design Limited | Process for selecting candidate drug compounds |
CA2270527A1 (en) | 1996-11-04 | 1998-05-14 | 3-Dimensional Pharmaceuticals, Inc. | System, method, and computer program product for the visualization and interactive processing and analysis of chemical data |
-
1994
- 1994-09-16 US US08/306,915 patent/US5463564A/en not_active Expired - Lifetime
-
1995
- 1995-09-11 JP JP8510247A patent/JPH10505832A/en active Pending
- 1995-09-11 HU HU9801578A patent/HUT77914A/en unknown
- 1995-09-11 WO PCT/US1995/011365 patent/WO1996008781A1/en not_active Application Discontinuation
- 1995-09-11 CA CA002199264A patent/CA2199264A1/en not_active Abandoned
- 1995-09-11 EP EP95933748A patent/EP0781436A4/en not_active Withdrawn
- 1995-09-11 AU AU36280/95A patent/AU688598B2/en not_active Ceased
- 1995-09-14 IL IL11529295A patent/IL115292A/en active IP Right Grant
- 1995-09-26 TW TW084109873A patent/TW420779B/en not_active IP Right Cessation
- 1995-09-28 US US08/535,822 patent/US5574656A/en not_active Expired - Lifetime
-
1996
- 1996-08-15 US US08/698,246 patent/US5684711A/en not_active Expired - Lifetime
-
1997
- 1997-08-01 US US08/904,737 patent/US5901069A/en not_active Expired - Lifetime
-
1998
- 1998-12-17 US US09/213,156 patent/US6434490B1/en not_active Expired - Lifetime
-
2002
- 2002-07-05 US US10/188,801 patent/US20030033088A1/en not_active Abandoned
Patent Citations (64)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4811217A (en) * | 1985-03-29 | 1989-03-07 | Japan Association For International Chemical Information | Method of storing and searching chemical structure data |
US4773099A (en) * | 1985-10-10 | 1988-09-20 | The Palantir Corporation | Pattern classification means for use in a pattern recognition system |
US4859736A (en) * | 1987-03-30 | 1989-08-22 | Ciba-Geigy Corporation | Synthetic polystyrene resin and its use in solid phase peptide synthesis |
US4908773A (en) * | 1987-04-06 | 1990-03-13 | Genex Corporation | Computer designed stabilized proteins and method for producing same |
US4939666A (en) * | 1987-09-02 | 1990-07-03 | Genex Corporation | Incremental macromolecule construction methods |
US4935875A (en) * | 1987-12-02 | 1990-06-19 | Data Chem, Inc. | Chemical analyzer |
US5010175A (en) * | 1988-05-02 | 1991-04-23 | The Regents Of The University Of California | General method for producing and selecting peptides with specific properties |
US5025388A (en) * | 1988-08-26 | 1991-06-18 | Cramer Richard D Iii | Comparative molecular field analysis (CoMFA) |
US5307287A (en) * | 1988-08-26 | 1994-04-26 | Tripos Associates, Inc. | Comparative molecular field analysis (COMFA) |
US5095443A (en) * | 1988-10-07 | 1992-03-10 | Ricoh Company, Ltd. | Plural neural network system having a successive approximation learning method |
US5265030A (en) * | 1990-04-24 | 1993-11-23 | Scripps Clinic And Research Foundation | System and method for determining three-dimensional structures of proteins |
US5789160A (en) * | 1990-06-11 | 1998-08-04 | Nexstar Pharmaceuticals, Inc. | Parallel selex |
US5167009A (en) * | 1990-08-03 | 1992-11-24 | E. I. Du Pont De Nemours & Co. (Inc.) | On-line process control neural network using data pointers |
US5181259A (en) * | 1990-09-25 | 1993-01-19 | The United States Of America As Represented By The Administrator Of The National Aeronautics And Space Administration | General method of pattern classification using the two domain theory |
US5155801A (en) * | 1990-10-09 | 1992-10-13 | Hughes Aircraft Company | Clustered neural networks |
US5612895A (en) * | 1990-12-14 | 1997-03-18 | Balaji; Vitukudi N. | Method of rational drug design based on ab initio computer simulation of conformational features of peptides |
US5331573A (en) * | 1990-12-14 | 1994-07-19 | Balaji Vitukudi N | Method of design of compounds that mimic conformational features of selected peptides |
US5260882A (en) * | 1991-01-02 | 1993-11-09 | Rohm And Haas Company | Process for the estimation of physical and chemical properties of a proposed polymeric or copolymeric substance or material |
US5499193A (en) * | 1991-04-17 | 1996-03-12 | Takeda Chemical Industries, Ltd. | Automated synthesis apparatus and method of controlling the apparatus |
US5436850A (en) * | 1991-07-11 | 1995-07-25 | The Regents Of The University Of California | Method to identify protein sequences that fold into a known three-dimensional structure |
US5323471A (en) * | 1991-09-12 | 1994-06-21 | Atr Auditory And Visual Perception Research Laboratories | Pattern recognition apparatus and pattern learning apparatus employing neural net including excitatory element-inhibitory element pair couplings |
US5270170A (en) * | 1991-10-16 | 1993-12-14 | Affymax Technologies N.V. | Peptide library and screening method |
US5240680A (en) * | 1991-12-19 | 1993-08-31 | Chiron Corporation | Automated apparatus for use in peptide synthesis |
US5524065A (en) * | 1992-02-07 | 1996-06-04 | Canon Kabushiki Kaisha | Method and apparatus for pattern recognition |
US6037135A (en) * | 1992-08-07 | 2000-03-14 | Epimmune Inc. | Methods for making HLA binding peptides and their uses |
US5545568A (en) * | 1992-09-14 | 1996-08-13 | The Regents Of The University Of California | Solid phase and combinatorial synthesis of compounds on a solid support |
US5288514A (en) * | 1992-09-14 | 1994-02-22 | The Regents Of The University Of California | Solid phase and combinatorial synthesis of benzodiazepine compounds on a solid support |
US5565325A (en) * | 1992-10-30 | 1996-10-15 | Bristol-Myers Squibb Company | Iterative methods for screening peptide libraries |
US5442122A (en) * | 1992-11-09 | 1995-08-15 | Shimadzu Corporation | Dibenzosuberyl and dibenzosuberenyl derivatives |
US5526281A (en) * | 1993-05-21 | 1996-06-11 | Arris Pharmaceutical Corporation | Machine-learning approach to modeling biological activity for molecular design and to modeling other characteristics |
US5703792A (en) * | 1993-05-21 | 1997-12-30 | Arris Pharmaceutical Corporation | Three dimensional measurement of molecular diversity |
US5832494A (en) * | 1993-06-14 | 1998-11-03 | Libertech, Inc. | Method and apparatus for indexing, searching and displaying data |
US5585277A (en) * | 1993-06-21 | 1996-12-17 | Scriptgen Pharmaceuticals, Inc. | Screening method for identifying ligands for target proteins |
US5635598A (en) * | 1993-06-21 | 1997-06-03 | Selectide Corporation | Selectively cleavabe linners based on iminodiacetic acid esters for solid phase peptide synthesis |
US5679582A (en) * | 1993-06-21 | 1997-10-21 | Scriptgen Pharmaceuticals, Inc. | Screening method for identifying ligands for target proteins |
US5434796A (en) * | 1993-06-30 | 1995-07-18 | Daylight Chemical Information Systems, Inc. | Method and apparatus for designing molecules with desired properties by evolving successive populations |
US5621861A (en) * | 1993-07-27 | 1997-04-15 | Matsushita Electric Industrial Co., Ltd. | Method of reducing amount of data required to achieve neural network learning |
US5519635A (en) * | 1993-09-20 | 1996-05-21 | Hitachi Ltd. | Apparatus for chemical analysis with detachable analytical units |
US5598510A (en) * | 1993-10-18 | 1997-01-28 | Loma Linda University Medical Center | Self organizing adaptive replicate (SOAR) |
US5866334A (en) * | 1994-04-05 | 1999-02-02 | Genzyme Corporation | Determination and identification of active compounds in a compound library |
US5670326A (en) * | 1994-04-05 | 1997-09-23 | Pharmagenics, Inc. | Reiterative method for screening combinatorial libraries |
US5602938A (en) * | 1994-05-20 | 1997-02-11 | Nippon Telegraph And Telephone Corporation | Method of generating dictionary for pattern recognition and pattern recognition method using the same |
US5549974A (en) * | 1994-06-23 | 1996-08-27 | Affymax Technologies Nv | Methods for the solid phase synthesis of thiazolidinones, metathiazanones, and derivatives thereof |
US5740326A (en) * | 1994-07-28 | 1998-04-14 | International Business Machines Corporation | Circuit for searching/sorting data in neural networks |
US5901069A (en) * | 1994-09-16 | 1999-05-04 | 3-Dimensional Pharmaceuticals, Inc. | System, method, and computer program product for at least partially automatically generating chemical compounds with desired properties from a list of potential chemical compounds to synthesize |
US5684711A (en) * | 1994-09-16 | 1997-11-04 | 3-Dimensional Pharmaceuticals, Inc. | System, method, and computer program for at least partially automatically generating chemical compounds having desired properties |
US5574656A (en) * | 1994-09-16 | 1996-11-12 | 3-Dimensional Pharmaceuticals, Inc. | System and method of automatically generating chemical compounds with desired properties |
US5463564A (en) * | 1994-09-16 | 1995-10-31 | 3-Dimensional Pharmaceuticals, Inc. | System and method of automatically generating chemical compounds with desired properties |
US5858660A (en) * | 1994-09-20 | 1999-01-12 | Nexstar Pharmaceuticlas, Inc. | Parallel selex |
US5634017A (en) * | 1994-09-22 | 1997-05-27 | International Business Machines Corporation | Computer system and method for processing atomic data to calculate and exhibit the properties and structure of matter based on relativistic models |
US5553225A (en) * | 1994-10-25 | 1996-09-03 | International Business Machines Corporation | Method and apparatus for combining a zoom function in scroll bar sliders |
US5712171A (en) * | 1995-01-20 | 1998-01-27 | Arqule, Inc. | Method of generating a plurality of chemical compounds in a spatially arranged array |
US5736412A (en) * | 1995-01-20 | 1998-04-07 | Arqule, Inc. | Method of generating a plurality of chemical compounds in a spatially arranged array |
US5807754A (en) * | 1995-05-11 | 1998-09-15 | Arqule, Inc. | Combinatorial synthesis and high-throughput screening of a Rev-inhibiting arylidenediamide array |
US5602755A (en) * | 1995-06-23 | 1997-02-11 | Exxon Research And Engineering Company | Method for predicting chemical or physical properties of complex mixtures |
US5811241A (en) * | 1995-09-13 | 1998-09-22 | Cortech, Inc. | Method for preparing and identifying N-substitued 1,4-piperazines and N-substituted 1,4-piperazinediones |
US5734796A (en) * | 1995-09-29 | 1998-03-31 | Ai Ware, Inc. | Self-organization of pattern data with dimension reduction through learning of non-linear variance-constrained mapping |
US5712564A (en) * | 1995-12-29 | 1998-01-27 | Unisys Corporation | Magnetic ink recorder calibration apparatus and method |
US6014661A (en) * | 1996-05-06 | 2000-01-11 | Ivee Development Ab | System and method for automatic analysis of data bases and for user-controlled dynamic querying |
US5861532A (en) * | 1997-03-04 | 1999-01-19 | Chiron Corporation | Solid-phase synthesis of N-alkyl amides |
US5908960A (en) * | 1997-05-07 | 1999-06-01 | Smithkline Beecham Corporation | Compounds |
US5933819A (en) * | 1997-05-23 | 1999-08-03 | The Scripps Research Institute | Prediction of relative binding motifs of biologically active peptides and peptide mimetics |
US5933819C1 (en) * | 1997-05-23 | 2001-11-13 | Scripps Research Inst | Prediction of relative binding motifs of biologically active peptides and peptide mimetics |
US6049797A (en) * | 1998-04-07 | 2000-04-11 | Lucent Technologies, Inc. | Method, apparatus and programmed medium for clustering databases with categorical attributes |
Cited By (33)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20020048610A1 (en) * | 2000-01-07 | 2002-04-25 | Cima Michael J. | High-throughput formation, identification, and analysis of diverse solid-forms |
US20030138940A1 (en) * | 2000-01-07 | 2003-07-24 | Lemmo Anthony V. | Apparatus and method for high-throughput preparation and characterization of compositions |
US20020177167A1 (en) * | 2000-01-07 | 2002-11-28 | Levinson Douglas A. | Method and system for planning, performing, and assessing high-throughput screening of multicomponent chemical compositions and solid forms of compounds |
US20070021929A1 (en) * | 2000-01-07 | 2007-01-25 | Transform Pharmaceuticals, Inc. | Computing methods for control of high-throughput experimental processing, digital analysis, and re-arraying comparative samples in computer-designed arrays |
US7061605B2 (en) | 2000-01-07 | 2006-06-13 | Transform Pharmaceuticals, Inc. | Apparatus and method for high-throughput preparation and spectroscopic classification and characterization of compositions |
US7108970B2 (en) | 2000-01-07 | 2006-09-19 | Transform Pharmaceuticals, Inc. | Rapid identification of conditions, compounds, or compositions that inhibit, prevent, induce, modify, or reverse transitions of physical state |
US20020098518A1 (en) * | 2000-01-07 | 2002-07-25 | Douglas Levinson | Rapid identification of conditions, compounds, or compositions that inhibit, prevent, induce, modify, or reverse transitions of physical state |
US20030162226A1 (en) * | 2000-01-07 | 2003-08-28 | Cima Michael J. | High-throughput formation, identification, and analysis of diverse solid-forms |
US20030059837A1 (en) * | 2000-01-07 | 2003-03-27 | Levinson Douglas A. | Method and system for planning, performing, and assessing high-throughput screening of multicomponent chemical compositions and solid forms of compounds |
US20050089923A9 (en) * | 2000-01-07 | 2005-04-28 | Levinson Douglas A. | Method and system for planning, performing, and assessing high-throughput screening of multicomponent chemical compositions and solid forms of compounds |
US20050095696A9 (en) * | 2000-01-07 | 2005-05-05 | Lemmo Anthony V. | Apparatus and method for high-throughput preparation and characterization of compositions |
US20050118637A9 (en) * | 2000-01-07 | 2005-06-02 | Levinson Douglas A. | Method and system for planning, performing, and assessing high-throughput screening of multicomponent chemical compositions and solid forms of compounds |
US20050118636A9 (en) * | 2000-01-07 | 2005-06-02 | Douglas Levinson | Rapid identification of conditions, compounds, or compositions that inhibit, prevent, induce, modify, or reverse transitions of physical state |
US20050130220A1 (en) * | 2000-01-07 | 2005-06-16 | Transform Pharmaceuticals, Inc. | Apparatus and method for high-throughput preparation and spectroscopic classification and characterization of compositions |
US20050191614A1 (en) * | 2000-01-07 | 2005-09-01 | Millenium Pharmaceuticals, Inc. | High-throughput formation, identification and analysis of diverse solid forms |
US20070020662A1 (en) * | 2000-01-07 | 2007-01-25 | Transform Pharmaceuticals, Inc. | Computerized control of high-throughput experimental processing and digital analysis of comparative samples for a compound of interest |
US6965832B2 (en) | 2000-04-07 | 2005-11-15 | Millennium Pharmaceuticals, Inc. | Investigating different physical and/or chemical forms of materials |
US20060025934A1 (en) * | 2000-04-07 | 2006-02-02 | Kobylecki Ryszard J | Investigating different physical and/or chemical forms of materials |
US20020183938A1 (en) * | 2000-04-07 | 2002-12-05 | Kobylecki Ryszard Jurek | Investigating different physical and/or chemical forms of materials |
US20060129329A1 (en) * | 2001-04-09 | 2006-06-15 | Kobylecki Ryszard J | Investigating different physical and/or chemical forms of materials |
US20030106492A1 (en) * | 2001-09-07 | 2003-06-12 | Douglas Levinson | Apparatus and method for high-throughput preparation, visualization and screening of compositions |
US20040105817A1 (en) * | 2002-10-30 | 2004-06-03 | Sylvain Gilat | Identifying therapeutic compounds based on their physical-chemical properties |
US7491312B2 (en) | 2002-10-30 | 2009-02-17 | Edison Pharmaceuticals, Inc. | Identifying therapeutic compounds based on their physical-chemical properties |
US20090163529A1 (en) * | 2002-10-30 | 2009-06-25 | Edison Pharmaceuticals, Inc. | Identifying therapeutic compounds based on their physical-chemical properties |
US10957419B2 (en) | 2016-08-01 | 2021-03-23 | Samsung Electronics Co., Ltd. | Method and apparatus for new material discovery using machine learning on targeted physical property |
US10998087B2 (en) * | 2016-08-25 | 2021-05-04 | The Government of the United States of Amercia as represented by the Secretary of Homeland Security | Systems and methodologies for desigining simulant compounds |
US11114183B2 (en) | 2016-08-25 | 2021-09-07 | The Government of the United States of America, as represented by the Secretary of Homeland Security | System and method for designing simulant composition |
US11581067B2 (en) | 2018-01-17 | 2023-02-14 | Samsung Electronics Co., Ltd. | Method and apparatus for generating a chemical structure using a neural network |
CN110277144A (en) * | 2018-03-15 | 2019-09-24 | 国际商业机器公司 | Have the new chemical compound of desirable properties to construct the new chemical structure for synthesis using the chemical data creation of accumulation |
US11087861B2 (en) * | 2018-03-15 | 2021-08-10 | International Business Machines Corporation | Creation of new chemical compounds having desired properties using accumulated chemical data to construct a new chemical structure for synthesis |
WO2019236761A1 (en) * | 2018-06-06 | 2019-12-12 | Syngulon Sa | Engineering antimicrobial peptides |
WO2020236314A1 (en) * | 2019-05-21 | 2020-11-26 | The Regents Of The University Of Michigan | Property modulation with chemical transformations |
WO2023165898A1 (en) * | 2022-03-03 | 2023-09-07 | Cytiva Sweden Ab | Method and device for synthesizing molecules |
Also Published As
Publication number | Publication date |
---|---|
US5463564A (en) | 1995-10-31 |
EP0781436A1 (en) | 1997-07-02 |
IL115292A0 (en) | 1995-12-31 |
US5684711A (en) | 1997-11-04 |
AU3628095A (en) | 1996-03-29 |
HUT77914A (en) | 1998-10-28 |
US6434490B1 (en) | 2002-08-13 |
US5901069A (en) | 1999-05-04 |
US5574656A (en) | 1996-11-12 |
JPH10505832A (en) | 1998-06-09 |
CA2199264A1 (en) | 1996-03-21 |
EP0781436A4 (en) | 1999-08-25 |
IL115292A (en) | 1999-06-20 |
AU688598B2 (en) | 1998-03-12 |
WO1996008781A1 (en) | 1996-03-21 |
TW420779B (en) | 2001-02-01 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US6434490B1 (en) | Method of generating chemical compounds having desired properties | |
AU732397B2 (en) | System, method and computer program product for identifying chemical compounds having desired properties | |
US7184893B2 (en) | Method for selecting an optimally diverse library of small molecules based on validated molecular structural descriptors | |
Korb et al. | PLANTS: Application of ant colony optimization to structure-based drug design | |
Salemme et al. | Serendipity meets precision: the integration of structure-based drug design and combinatorial chemistry for efficient drug discovery | |
EP0818744A2 (en) | Process for selecting candidate drug compounds | |
AU2002215028B2 (en) | Method of operating a computer system to perform a discrete substructural analysis | |
US20050177280A1 (en) | Methods and systems for discovery of chemical compounds and their syntheses | |
AU2002215028A1 (en) | Method of operating a computer system to perform a discrete substructural analysis | |
Zhu et al. | Designing DNA encoded libraries of diverse products in a focused property space | |
Parrill | Evolutionary and genetic methods in drug design | |
Taha et al. | Ligand-based assessment of factor Xa binding site flexibility via elaborate pharmacophore exploration and genetic algorithm-based QSAR modeling | |
Young et al. | Optimization of focused chemical libraries using recursive partitioning | |
AU710152B2 (en) | System and method of automatically generating chemical compounds with desired properties | |
Beroza et al. | Designing chiral libraries for drug discovery | |
Humblet et al. | 3D Database searching and docking strategles | |
WO2000065421A2 (en) | Receptor selectivity mapping | |
Schüller et al. | Identification of hits and lead structure candidates with limited resources by adaptive optimization | |
US6671627B2 (en) | Method and computer program product for designing combinatorial arrays | |
Gillet | Applications of evolutionary computation in drug design | |
Unger | The building block approach to protein structure prediction | |
Manchester et al. | Designing Combinatorial Libraries for Efficient Screening | |
Kaiser et al. | Extensive study of the serine proteases catalytic triad in structural biology |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
STCB | Information on status: application discontinuation |
Free format text: ABANDONED -- FAILURE TO RESPOND TO AN OFFICE ACTION |