System, method, and computer program for at least partially automatically generating chemical compounds having desired properties

• US 5,684,711 A
• Filed: 08/15/1996
• Issued: 11/04/1997
• 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: Soll, Richard M., Bone, Roger F., Salemme, Francis R., Agrafiotis, Dimitris K.
• Primary Examiner(s): Voeltz, Emanuel T.
• Assistant Examiner(s): CHOI, KYLE JAEHUN
• Application Number:
  US08/698,246
• Time in Patent Office: 446 Days
• Field of Search: 364/496, 364/497, 364/500, 364/578, 436/43, 436/50, 436/55, 423/659, 424/2
• US Class Current: 506/1
• 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 system for generating compounds having a prescribed set of activity/properties, comprising:

chemical synthesis means for synthesizing, in accordance with synthesis instructions, a directed diversity chemical library comprising a plurality of chemical compounds;

analysis means for analyzing said chemical compounds to obtain structure-activity data pertaining thereto;

comparing means for comparing said structure-activity data of said chemical compounds against said prescribed set of activity/properties to identify any of said chemical compounds substantially conforming to said prescribed set of activity/properties;

classifying means for classifying said identified chemical compounds as lead compounds;

structure-activity model derivation means for analyzing 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;

reagent identifying means for identifying, 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 activity/properties; and

synthesis instruction generating means for generating synthesis instructions that, when executed, enable said chemical synthesis means to synthesize said set of compounds.

2. The system of claim 1, wherein said analysis means comprises at least one of an assay module, a chemical synthesis indicia generator, a structure and composition analysis module, a physical and electronic property analysis module, and a three dimensional receptor mapping module.

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

(1) synthesizing, in accordance with synthesis instructions, 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, under the assistance of a computer, 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 said identified chemical compounds as lead compounds;

(5) analyzing, under the assistance of a computer, 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, 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 synthesis instructions that, when executed, enable synthesis of said set of compounds; and

(8) repeating steps (1)-(7), wherein step (1) is repeated using said generated synthesis instructions.

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

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

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

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

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

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

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

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

8. The method of claim 3, wherein step (6) is performed according to operator input.

9. The method of claim 3, wherein step (7) comprises the steps of:

receiving operator input pertaining to the generation of said synthesis instructions; and

generating said synthesis instructions based, at least in part, on said operator input.

10. A synthesis protocol generator for use in a system that endeavors to generate compounds having a prescribed set of activity/properties, said synthesis protocol generator comprising:

structure-activity model derivation means for analyzing structure-activity data of compounds contained in a directed diversity chemical library 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;

reagent identifying means for identifying, 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 activity/properties; and

synthesis instruction generating means for generating synthesis instructions that, when executed, enable synthesis by said system of said set of compounds.

11. The synthesis protocol generator of claim 10, further comprising:

comparing means for comparing said structure-activity data of said chemical compounds against said prescribed set of activity/properties to identify any of said chemical compounds substantially conforming to said prescribed set of activity/properties; and

classifying means for classifying said identified chemical compounds as lead compounds.

12. The synthesis protocol generator of claim 10, wherein said reagent identifying means comprises:

means for identifying, in accordance with said structure-activity models, reagents from said 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 said synthesis instruction generating means comprises;

means for generating synthesis instructions that, when executed, enable synthesis of said second set of compounds.

13. The synthesis protocol generator of claim 10, wherein said reagent identifying means comprises:

means for identifying, in accordance with said structure-activity models, reagents from said 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 said synthesis instruction generating means comprises;

means for generating synthesis instructions that, when executed, enable synthesis of said second set of compounds.

14. The synthesis protocol generator of claim 10, wherein said reagent identifying means comprises:

means for identifying, in accordance with said structure-activity models, reagents from said 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 said synthesis instruction generating means comprises;

means for generating synthesis instructions that, when executed, enable synthesis of said second and third set of compounds.

15. The synthesis protocol generator of claim 10, wherein said reagent identifying means comprises:

means for identifying, in accordance with said structure-activity models, reagents from said 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 said synthesis instruction generating means comprises;

means for generating synthesis instructions that, when executed, enable synthesis of said second set of compounds.

16. The synthesis protocol generator of claim 10, wherein said reagent identifying means comprises:

means for identifying reagents from said reagent database that, when combined, will produce a second set of compounds with structural, physical, or chemical characteristics similar to characteristics of compounds in a structure-activity database whose activity/properties most closely conform to said prescribed set of activity/properties, wherein said first and second sets of compounds are not mutually exclusive;

wherein said synthesis instruction generating means comprises;

means for generating synthesis instructions that, when executed, enable synthesis of said second set of compounds.

17. The synthesis protocol generator of claim 10, further comprising:

means for generating a list of potential chemical compounds to possibly synthesize, each of said potential chemical compounds comprising N of said reagents identified by said reagent identifying means; and

candidate compound identifying means for selecting from said list of potential chemical compounds a plurality of candidate compounds that are suitable for synthesis.

18. The synthesis protocol generator of claim 17, wherein said synthesis protocol generator further comprises:

optimal set selecting means for selecting an optimal set of said candidate compounds to synthesize based on at least one of the following factors;

(I) their respective predicted abilities to exhibit activity/properties more closely matching said prescribed set of activity/properties as indicated by said structure-activity models;

(ii) their respective predicted abilities to validate said structure-activity models;

(iii) their respective predicted abilities to discriminate between said structure-activity models;

(iv) their respective predicted abilities to have superior three-dimensional receptor fit; and

(v) similarity between their respective structural, physical, or chemical characteristics and characteristics of compounds in a structure-activity database whose activity/properties most closely conform to said prescribed set of activity/properties.

19. The synthesis protocol generator of claim 18, wherein said optimal set selecting means comprises:

means for selecting said optimal set by individually ranking said candidate compounds based on at least one of factors (I)-(v).

20. The synthesis protocol generator of claim 18, wherein said optimal set selecting means comprises:

means for selecting said optimal set by ranking combinations of said candidate compounds based on at least one of factors (I)-(v).

21. A computer assisted method for aiding in generating compounds having a prescribed set of activity/properties, said method comprising the steps of:

(1) analyzing structure-activity data of compounds contained in a directed diversity chemical library 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;

(2) identifying, 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 activity/properties; and

(3) generating synthesis instructions that, when executed, enable synthesis of said set of compounds.

22. The method of claim 21, further comprising the steps of:

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

(5) classifying said identified chemical compounds as lead compounds.

23. The method of claim 21, wherein step (2) comprises the steps of:

identifying, in accordance with said structure activity models, reagents from said 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 (3) comprises the step of;

generating synthesis instructions that, when executed, enable synthesis of said second set of compounds.

24. The method of claim 21, wherein step (2) comprises the steps of:

identifying, in accordance with said structure-activity models, reagents from said 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 (3) comprises the step of;

generating synthesis instructions that, when executed, enable synthesis of said second set of compounds.

25. The method of claim 21, wherein step (2) comprises the steps of:

identifying, in accordance with said structure-activity models, reagents from said 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 (3) comprises the step of;

generating synthesis instructions that, when executed, enable synthesis of said second and third set of compounds.

26. The method of claim 21, wherein step (2) comprises the steps of:

identifying, in accordance with said structure-activity models, reagents from said 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 (3) comprises the step of;

generating synthesis instructions that, when executed, enable synthesis of said second set of compounds.

27. The method of claim 21, wherein step (2) comprises the steps of:

identifying reagents from said reagent database that, when combined, will produce a second set of compounds with structural, physical, or chemical characteristics similar to characteristics of compounds in a structure-activity database whose activity/properties most closely conform to said prescribed set of activity/properties, wherein said first and second sets of compounds are not mutually exclusive;

wherein step (3) comprises the step of;

generating synthesis instructions that, when executed, enable synthesis of said second set of compounds.

28. The method of claim 21, further comprising the steps of:

generating a list of potential chemical compounds to possibly synthesize, each of said potential chemical compounds comprising N of said reagents identified by said reagent identifying means; and

selecting from said list of potential chemical compounds a plurality of candidate compounds that are suitable for synthesis.

29. The method of claim 28, further comprising the steps of:

selecting an optimal set of said candidate compounds to synthesize based on at least one of the following factors;

(I) their respective predicted abilities to exhibit activity/properties more closely matching said prescribed set of activity/properties as indicated by said structure-activity models;

(ii) their respective predicted abilities to validate said structure-activity models;

(iii) their respective predicted abilities to discriminate between said structure-activity models;

(iv) their respective predicted abilities to have superior three-dimensional receptor fit; and

(v) similarity between their respective structural, physical, or chemical characteristics and characteristics of compounds in a structure-activity database whose activity/properties most closely conform to said prescribed set of activity/properties.

30. A computer program product comprising a computer useable medium having computer program logic recorded thereon for enabling a processor to assist in generating compounds having a prescribed set of activity/properties, said computer program logic comprising:

structure-activity model derivation means for enabling the processor to analyze structure-activity data of compounds in a directed diversity chemical library 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;

reagent identifying means for enabling the processor to identify, 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 activity/properties; and

synthesis instruction generating means for enabling the processor to generate synthesis instructions that, when executed, enable synthesis of said set of compounds.

31. The computer program product of claim 30, wherein said computer program logic further comprises:

comparing means for enabling the processor to compare said structure-activity data of said chemical compounds against said prescribed set of activity/properties to identify any of said chemical compounds conforming to said prescribed set of activity/properties; and

classifying means for enabling the processor to classify said identified chemical compounds as chemical compounds of potential interest.

32. The computer program product of claim 30, wherein said reagent identifying means comprises:

means for enabling the processor to identify, in accordance with said structure-activity models, reagents from said 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 said synthesis instruction generating means comprises;

means for enabling the processor to generate synthesis instructions that, when executed, enable synthesis of said second set of compounds.

33. The computer program product of claim 30, wherein said reagent identifying means comprises:

means for enabling the processor to identify, in accordance with said structure-activity models, reagents from said 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 said synthesis instruction generating means comprises;

means for enabling the processor to generate synthesis instructions that, when executed, enable synthesis of said second set of compounds.

34. The computer program product of claim 30, wherein said reagent identifying means comprises:

means for enabling the processor to identify, in accordance with said structure-activity models, reagents from said 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 said synthesis instruction generating means comprises;

means for enabling the processor to generate synthesis instructions that, when executed, enable synthesis of said second and third set of compounds.

35. The computer program product of claim 30, wherein said reagent identifying means comprises:

means for enabling the processor to identify, in accordance with said structure-activity models, reagents from said 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 said synthesis instruction generating means comprises;

means for enabling the processor to generate synthesis instructions that, when executed, enable synthesis of said second set of compounds.

36. The computer program product of claim 30, wherein said reagent identifying means comprises:

means for enabling the processor to identify reagents from said reagent database that, when combined, will produce a second set of compounds with structural, physical, or chemical characteristics similar to characteristics of compounds in a structure-activity database whose activity/properties most closely conform to said prescribed set of activity/properties, wherein said first and second sets of compounds are not mutually exclusive;

wherein said synthesis instruction generating means comprises;

means for enabling the processor to generate synthesis instructions that, when executed, enable synthesis of said second set of compounds.

37. The computer program product of claim 30, wherein said computer program logic further comprises:

means for enabling the processor to generate a list of potential chemical compounds to possibly synthesize, each of said potential chemical compounds comprising N of said reagents identified by said reagent identifying means; and

candidate compound identifying means for enabling the processor to select from said list of potential chemical compounds a plurality of candidate compounds that are suitable for synthesis.

38. The computer program product of claim 37, wherein said computer program logic further comprises:

optimal set selecting means for enabling the processor to select an optimal set of said candidate compounds to synthesize based on at least one of the following factors;

(I) their respective predicted abilities to exhibit activity/properties more closely matching said prescribed set of activity/properties as indicated by said structure-activity models;

(II) their respective predicted abilities to validate said structure-activity models;

(III) their respective predicted abilities to discriminate between said structure-activity models;

(IV) their respective predicted abilities to have superior three-dimensional receptor fit; and

(V) similarity between their respective structural, physical, or chemical characteristics and characteristics of compounds in a structure-activity database whose activity/properties most closely conform to said prescribed set of activity/properties.

39. The computer program product of claim 38, wherein said optimal set selecting means comprises:

means for enabling the processor to select said optimal set by individually ranking said candidate compounds based on at least one of factors (I)-(V).

40. The computer program product of claim 38, wherein said optimal set selecting means comprises:

means for enabling the processor to select said optimal set by ranking combinations of said candidate compounds based on at least one of factors (I)-(V).

41. A computer assisted system for at least partially automatically generating compounds having a prescribed set of properties, comprising:

synthesizing means for synthesizing, in accordance with synthesis instructions, a directed diversity chemical library comprising a plurality of chemical compounds;

chemical compound analyzing means for analyzing said chemical compounds to obtain structure-activity data pertaining thereto;

comparing means for 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;

structure-activity analyzing means for analyzing 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;

reagent identifying means for identifying, 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; and

synthesis instructions generating means for generating synthesis instructions that, when performed, enable synthesis of said set of compounds.

42. The system of claim 41, wherein said reagent identifying means comprises:

means for identifying 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 said synthesis instructions generating means comprises means for generating synthesis instructions that, when performed, enable synthesis of said second set of compounds.

43. The system of claim 41, wherein said reagent identifying means comprises:

means for identifying 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 said synthesis instructions generating means comprises means for generating synthesis instructions that, when performed, enable synthesis of said second set of compounds.

44. The system of claim 41, wherein said reagent identifying means comprises:

means for identifying 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 said synthesis instructions generating means comprises means for generating synthesis instructions that, when performed, enable synthesis of said second and third set of compounds.

45. The system of claim 41, wherein said reagent identifying means comprises:

means for identifying 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 said synthesis instructions generating means comprises means for generating synthesis instructions that, when performed, enable synthesis of said second set of compounds.

46. The system of claim 41, wherein said reagent identifying means operates according to operator input.

47. The system of claim 41, wherein said synthesis instructions generating means comprises:

means for receiving operator input pertaining to the generation of said synthesis instructions; and

means for generating said synthesis instructions based, at least in part, on said operator input.

48. A computer program product comprising a computer useable medium having computer program logic recorded thereon for enabling a processor in a computer to at least partially automatically generate compounds having a prescribed set of properties, said computer program logic comprising:

synthesizing means for enabling the processor to synthesize, in accordance with synthesis instructions, a directed diversity chemical library comprising a plurality of chemical compounds;

chemical compound analyzing means for enabling the processor to analyze said chemical compounds to obtain structure-activity data pertaining thereto;

comparing means for enabling the processor to compare 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;

structure-activity analyzing means for enabling the processor to analyze 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;

reagent identifying means for enabling the processor to identify, 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; and

synthesis instructions generating means for enabling the processor to generate synthesis instructions that, when performed, enable synthesis of said set of compounds.

49. The computer program product of claim 48, wherein said reagent identifying means comprises:

means for enabling the processor to identify 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 said synthesis instructions generating means comprises means for enabling the processor to generate synthesis instructions that, when performed, enable synthesis of said second set of compounds.

50. The computer program product of claim 48, wherein said reagent identifying means comprises:

means for enabling the processor to identify 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 said synthesis instructions generating means comprises means for enabling the processor to generate synthesis instructions that, when performed, enable synthesis of said second set of compounds.

51. The computer program product of claim 48, wherein said reagent identifying means comprises;

means for enabling the processor to identify 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 said synthesis instructions generating means comprises means for enabling the processor to generate synthesis instructions that, when performed, enable synthesis of said second and third set of compounds.

52. The computer program product of claim 48, wherein said reagent identifying means comprises:

means for enabling the processor to identify 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 said synthesis instructions generating means comprises means for enabling the processor to generate synthesis instructions that, when performed, enable synthesis of said second set of compounds.

53. The computer program product of claim 48, wherein said reagent identifying means operates according to operator input.

54. The computer program product of claim 48, wherein said synthesis instructions generating means comprises:

means for enabling the processor to receive operator input pertaining to the generation of said synthesis instructions; and

means for enabling the processor to generate said synthesis instructions based, at least in part, on said operator input.