Method of generating chemical compounds having desired properties

• US 6,434,490 B1
• Filed: 12/17/1998
• Issued: 08/13/2002
• Est. Priority Date: 09/16/1994
• Status: Expired due to Term

• Current Assignee: 3-Dimensional Pharmaceuticals, Inc. (Johnson & Johnson)
• Original Assignee: 3-Dimensional Pharmaceuticals, Inc. (Johnson & Johnson)
• Inventors: Salemme, Francis R., Agrafiotis, Dimitris K., Soll, Richard M., Bone, Roger F.
• Primary Examiner(s): Borin, Michael
• Assistant Examiner(s): Zhou, Shubo
• Application Number:
  US09/213,156
• Time in Patent Office: 1,335 Days
• Field of Search: 702/27, 702/19, 435/7.24, 435/91.2, 364/496, 364/500
• US Class Current: 702/27
• CPC Class Codes: A61P 7/02 Antithrombotic agents; Anticoagulants; Platelet aggregation inhibitors
• CPC Class Codes: B01J 19/0046 Sequential or parallel reactions, e.g. for the synthesis of polypeptides or polynucleotides; Apparatus and devices for combinatorial chemistry or for making molecular arrays synthesis methods per se C40B50/00
• CPC Class Codes: B01J 2219/0059 Sequential processes
• CPC Class Codes: B01J 2219/00592 Split-and-pool, mix-and-divide processes
• CPC Class Codes: B01J 2219/00596 Solid-phase processes
• CPC Class Codes: B01J 2219/00599 Solution-phase processes
• CPC Class Codes: B01J 2219/00689 using computers
• CPC Class Codes: B01J 2219/00691 using robots
• CPC Class Codes: B01J 2219/00695 Synthesis control routines, e.g. using computer programs
• CPC Class Codes: B01J 2219/00698 Measurement and control of process parameters
• CPC Class Codes: B01J 2219/007 Simulation or vitual synthesis
• CPC Class Codes: B01J 2219/0072 Organic compounds
• CPC Class Codes: B01J 2219/00725 Peptides
• CPC Class Codes: C07K 1/047 Simultaneous synthesis of different peptide species; Peptide libraries
• CPC Class Codes: C40B 40/10 Libraries containing peptides or polypeptides, or derivatives thereof
• CPC Class Codes: C40B 50/08 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
• CPC Class Codes: G16B 15/30 Drug targeting using structural data; Docking or binding prediction
• CPC Class Codes: G16B 35/00 ICT specially adapted for in silico combinatorial libraries of nucleic acids, proteins or peptides
• CPC Class Codes: G16C 20/10 Analysis or design of chemical reactions, syntheses or processes
• CPC Class Codes: G16C 20/30 Prediction of properties of chemical compounds, compositions or mixtures
• CPC Class Codes: G16C 20/60 : In silico combinatorial chemistry
• CPC Class Codes: G16C 20/62 : Design of libraries
• CPC Class Codes: G16C 20/70 : Machine learning, data mining or chemometrics
• CPC Class Codes: Y10T 436/11 : 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.

Claims

1. A method for at least partially automatically generating compounds having at least a prescribed set of properties, comprising the steps of:

(1) robotically synthesizing a directed diversity chemical library comprising a plurality of chemical compounds;

(2) analyzing said chemical compounds to obtain structure-activity data pertaining thereto;

(3) comparing said structure-activity data of said chemical compounds against said prescribed set of properties to identify any of said chemical compounds conforming to said prescribed set of properties;

(4) classifying said identified chemical compounds as lead compounds;

(5) analyzing said structure-activity data of said lead compounds and historical structure-activity data pertaining to compounds synthesized and analyzed in the past to derive structure-activity models having predictive and discriminating capabilities;

(6) identifying, in accordance with said structure-activity models, reagents that, when combined, will produce a first set of compounds predicted to exhibit activity/properties more closely matching said prescribed set of properties;

(7) generating robotic synthesis instructions that, when performed, enable robotic synthesis of said first set of compounds; and

(8) robotically synthesizing a new directed diversity chemical library comprising a plurality of chemical compounds using said generated synthesis instructions and repeating steps (2) through (7).

2. The method of claim 1, wherein step (6) comprises the step of:

identifying reagents 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 synthesis instructions that, when performed, enable synthesis of said second set of compounds.

3. The method of claim 1, wherein step (6) comprises the step of:

identifying reagents 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 synthesis instructions that, when performed, enable synthesis of said second set of compounds.

4. The method of claim 1, wherein step (6) comprises the step of:

identifying reagents 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 synthesis instructions that, when performed, enable synthesis of said second and third set of compounds.

5. The method of claim 1, wherein step (6) comprises the step of:

identifying reagents 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 synthesis instructions that, when performed, enable synthesis of said second set of compounds.