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Claims  |
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What is claimed is:
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.
6. The method of claim 1, wherein step (6) comprises the step of:
identifying under computer control 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.
7. The method of claim 1, wherein step (6) comprises the steps of:
(a) generating a list of potential chemical compounds to possibly
synthesize, each of said potential chemical compounds synthesized using N
of said identified reagents; and
(b) selecting from said list of potential chemical compounds a plurality of
candidate compounds that are suitable for synthesis.
8. The method of claim 7, wherein N is greater or equal to 1 and less than
500.
9. The method of claim 7, wherein N is of a magnitude such that each
compound synthesized contains three variable subunits.
10. The method of claim 7, wherein step (2) comprises the steps of:
analyzing said chemical compounds to obtain structure and composition data
pertaining thereto;
analyzing said structure and composition data to generate chemical
synthesis indicia indicating which of said chemical compounds were
adequately synthesized, and which of said chemical compounds were not
adequately synthesized; and
storing said structure and composition data and said chemical synthesis
indicia in a structure-activity database, said structure-activity database
also having stored therein structure and composition data and chemical
synthesis indicia pertaining to previously synthesized chemical compounds.
11. The method of claim 10, wherein step (b) comprises the steps of:
retrieving from said structure-activity database any chemical synthesis
indicia pertaining to said potential chemical compounds; and
selecting as candidate compounds any of said potential chemical compounds
that were previously adequately synthesized as indicated by said retrieved
chemical synthesis indicia, if any, respectively associated with said
potential chemical compounds.
12. The method of claim 10, wherein step (b) comprises the steps of:
retrieving from said structure-activity database any chemical synthesis
indicia pertaining to said potential chemical compounds; and
eliminating from consideration as candidate compounds any of said potential
chemical compounds that were previously inadequately synthesized as
indicated by said retrieved chemical synthesis indicia, if any,
respectively associated with said potential chemical compounds.
13. The method of claim 7, wherein step (7) comprises the step of:
generating, under computer control, robotic synthesis instructions that,
when executed, enable robotic synthesis of said candidate compounds.
14. The method of claim 7, further comprising the step of:
(c) 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.
15. The method of claim 14, wherein step (c) comprises the step of:
selecting said optimal set by individually ranking said candidate compounds
based on at least one of factors (i)-(v).
16. The method of claim 14, wherein step (c) comprises the step of:
selecting said optimal set by ranking combinations of said candidate
compounds based on at least one of factors (i)-(v).
17. The method of claim 14, wherein step (7) comprises the step of:
generating, under computer control, robotic synthesis instructions that,
when executed, enable robotic synthesis of said optimal set of candidate
compounds.
18. The method of claim 1, wherein step (6) is performed according to
operator input.
19. The method of claim 1, wherein step (7) comprises the steps of:
receiving operator input pertaining to the generation of said robotic
synthesis instructions; and
generating said robotic synthesis instructions based, at least in part, on
said operator input.
20. The method of claim 1, wherein said reagents include amines suitable
for synthesizing thrombin inhibitors.
21. A computer-based system for automatically generating compounds having a
prescribed set of activity/properties, comprising:
one or more chemical synthesis robots to robotically synthesize, in
accordance with robotic synthesis instructions, a directed diversity
chemical library comprising a plurality of chemical compounds;
one or more analysis robots to robotically analyze said chemical compounds
to obtain structure-activity data pertaining thereto;
a synthesis protocol generator, 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;
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
robotic synthesis instruction generating means for generating robotic
synthesis instructions that, when executed, enable said chemical synthesis
robots to robotically synthesize said set of compounds.
22. The system of claim 21, 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 robotic synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robots to robotically synthesize said
second set of compounds.
23. The system of claim 21, 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 robotic synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robots to robotically synthesize said
second set of compounds.
24. The system of claim 21, 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 robotic synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robots to robotically synthesize said
second and third set of compounds.
25. The system of claim 21, 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 robotic synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robots to robotically synthesize said
second set of compounds.
26. The system of claim 21, 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 robotic synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robots to robotically synthesize said
second set of compounds.
27. The system of claim 21, wherein said synthesis protocol generator
further comprises:
means for generating a list of potential chemical compounds to possibly
synthesize, each of said potential chemical compounds synthesized using 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.
28. The system of claim 27, wherein N is of a magnitude such that each
compound synthesized contains three variable subunits.
29. The method of claim 27, wherein N is greater or equal to 1 and less
than 500.
30. The system of claim 27, wherein said analysis robots comprise:
means for analyzing said chemical compounds to obtain structure and
composition data pertaining thereto;
means for analyzing said structure and composition data to generate
chemical synthesis indicia indicating which of said chemical compounds
were adequately synthesized, and which of said chemical compounds were not
adequately synthesized; and
means for storing said structure and composition data and said chemical
synthesis indicia in a structure-activity database, said
structure-activity database also having stored therein structure and
composition data and chemical synthesis indicia pertaining to previously
synthesized chemical compounds.
31. The system of claim 30, wherein said candidate compound identifying
means comprises:
means for retrieving from said structure-activity database any chemical
synthesis indicia pertaining to said potential chemical compounds; and
means for selecting as candidate compounds any of said potential chemical
compounds that were previously adequately synthesized as indicated by said
retrieved chemical synthesis indicia, if any, respectively associated with
said potential chemical compounds.
32. The system of claim 27, wherein said robotic synthesis instruction
generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robots to robotically synthesize said
candidate compounds.
33. The system of claim 27, 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.
34. The system of claim 33, 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).
35. The system of claim 33, 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).
36. The system of claim 33, wherein said robotic synthesis instruction
generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robots to robotically synthesize said
optimal set of candidate compounds.
37. The system of claim 21, wherein said reagent identifying means operates
according to operator input.
38. The system of claim 21, wherein said robotic synthesis instruction
generating means comprises:
means for receiving operator input pertaining to the generation of said
robotic synthesis instructions; and
means for generating said robotic synthesis instructions based, at least in
part, on said operator input.
39. The system of claim 21, wherein said reagents include amines suitable
for synthesizing thrombin inhibitors.
40. A computer based method of iteratively generating a plurality of
directed diversity chemical libraries each comprising multiple chemical
compounds, wherein chemical compounds in said directed diversity chemical
libraries more closely conform to a prescribed set of activity/properties
during each successive iteration, the method 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) analyzing, under computer control, said structure-activity data of said
compounds and historical structure-activity data pertaining to compounds
synthesized and analyzed during prior iterations to derive
structure-activity models having enhanced predictive and discriminating
capabilities;
(4) 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
activity/properties;
(5) generating, under computer control, robotic synthesis instructions
that, when executed, enable robotic synthesis of said set of compounds;
and
(6) repeating steps (1)-(5), wherein step (1) is repeated using said
generated robotic synthesis instructions.
41. The method of claim 40, wherein step (4) comprises the step of:
identifying, under computer control and 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 (5) comprises the step of generating, under computer control, robotic
synthesis instructions that, when executed, enable robotic synthesis of
said second set of compounds.
42. The method of claim 40, wherein step (4) comprises the step of:
identifying, under computer control and 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 (5) comprises the step of generating, under computer control,
robotic synthesis instructions that, when executed, enable robotic
synthesis of said second set of compounds.
43. The method of claim 40, wherein step (4) comprises the step of:
identifying, under computer control and 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 (5) 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.
44. The method of claim 40, wherein step (4) comprises the step of:
identifying, under computer control and 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 (5) comprises the step of generating, under computer control,
robotic synthesis instructions that, when executed, enable robotic
synthesis of said second set of compounds.
45. The method of claim 40, wherein step (4) comprises the step of:
identifying under computer control 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 (5) comprises the step of:
generating, under computer control, robotic synthesis instructions that,
when executed, enable robotic synthesis of said second set of compounds.
46. The method of claim 40, further comprising the following steps which
are performed between steps (4) and (5):
(a) generating a list of potential chemical compounds to possibly
synthesize, each of said potential chemical compounds synthesized using N
of said identified reagents; and
(b) selecting from said list of potential chemical compounds a plurality of
candidate compounds that are suitable for synthesis.
47. The method of claim 46, wherein step (5) comprises the step of:
generating, under computer control, robotic synthesis instructions that,
when executed, enable robotic synthesis of said candidate compounds.
48. The method of claim 46, further comprising the step of:
(c) 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.
49. The method of claim 48, wherein step (c) comprises the step of:
selecting said optimal set by individually ranking said candidate compounds
based on at least one of factors (i)-(v).
50. The method of claim 48, wherein step (c) comprises the step of:
selecting said optimal set by ranking combinations of said candidate
compounds based on at least one of factors (i)-(v).
51. The method of claim 48, wherein step (5) comprises the step of:
generating, under computer control, robotic synthesis instructions that,
when executed, enable robotic synthesis of said optimal set of candidate
compounds.
52. A synthesis protocol generator for use in a system that automatically
generates compounds having a prescribed set of activity/properties, said
system comprising at least one chemical synthesis robot to robotically
synthesize, in accordance with robotic synthesis instructions, a directed
diversity chemical library comprising a plurality of chemical compounds,
and at least one analysis robot to robotically analyze said chemical
compounds to obtain structure-activity data pertaining thereto, said
synthesis protocol generator comprising:
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
robotic synthesis instruction generating means for generating robotic
synthesis instructions that, when executed, enable said chemical synthesis
robot to robotically synthesize said set of compounds.
53. The synthesis protocol generator of claim 52, 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.
54. The synthesis protocol generator of claim 52, 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 robotic synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robot to robotically synthesize said second
set of compounds.
55. The synthesis protocol generator of claim 52, 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 robotic synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robot to robotically synthesize said second
set of compounds.
56. The synthesis protocol generator of claim 52, wherein said reagent
identifying means comprises:
means for identifying, in accordance with said structure-activity models,
reagent 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 robotic synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robot to robotically synthesize said second
and third set of compounds.
57. The synthesis protocol generator of claim 52, 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 robotic synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robot to robotically synthesize said second
set of compounds.
58. The synthesis protocol generator of claim 52, wherein said reagent
identifying means comprises:
means for identifying under computer control 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 robotic synthesis instruction generating means comprises:
means for generating, under computer control, robotic synthesis
instructions that, when executed, enable robotic synthesis of said second
set of compounds.
59. The synthesis protocol generator of claim 52, 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.
60. The synthesis protocol generator of claim 59, wherein said robotic
synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robot to robotically synthesize said
candidate compounds.
61. The synthesis protocol generator of claim 59, 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.
62. The synthesis protocol generator of claim 61, 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).
63. The synthesis protocol generator of claim 61, 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).
64. The synthesis protocol generator of claim 61, wherein said robotic
synthesis instruction generating means comprises:
means for generating robotic synthesis instructions that, when executed,
enable said chemical synthesis robot to robotically synthesize said
optimal set of candidate compounds. |
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Claims |
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Description |
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BACKGROUND OF THE INVENTION
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 am 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 div | | |
