Abstract
Half a century ago, the term “drug discovery” conjured images of adventures into the jungle, beneath the sea, and atop mountains in search of frogs, sponges, lichens, or any unstudied life form that, ground up, might exhibit inhibitory effects toward a major human disease. More romantic and exciting science cannot be, to those of us too young to have participated in the “old” drug discovery paradigm, and perhaps also not more laborious, unpredictable, and frightening when included in a business plan. Combinatorial chemistry and high-throughput screening evolved to fill the need for a more systematic approach to discovery, in which miniaturization and automation were applied, as in traditional manufacturing processes, to reduce costs and cycle times. But to the contrary, the cost associated with producing clinical candidates seems to have actually risen with the application of these technologies (1–3).
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References
Prentis R. A., Lis, Y. and Walker S. R. (1988) Pharmaceutical innovation by the seven UK-owned pharmaceutical companies (1964−1985). Br. J. Clin. Pharmac. 25, 387–396.
DiMasi J. A. (1995) Success rates for new drugs entering clinical testing in the United States. Clinical Pharmacology and Therapeutics 58, 1–14.
Venkatesh S. and Lipper R. A. (2000) Role of the development scientist in compound lead selection and optimization. J. Pharm. Sci. 89, 145–154.
Martin Y. C. (1997) Challenges and prospects for computational aids to molecular diversity. Perspectives in Drug Discovery and Design 7/8, 159–172.
Kennedy T. (1997) Managing the drug discovery/development interface. Drug Discovery Today 2, 436–444.
Lipinski C. A., Lombardo F., Dominy B. W., and Feeney P. J. (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv. Drug Deliv. Rev. 23, 3–25.
Ekins S., Bravi G., Binkley S., et al. (2000) Three-and four-dimensionalquantitative structure activity relationship (3D/4D-QSAR) analyses of CYP2C9 inhibitors. Drug Metabolism and Disposition 28, 994–1002.
Ekins S., Bravi G., Wikel J. H., and Wrigthon S. A. (1999) Three-dimensionalduantitative structure activity relationship analysis of cytochrome P450 3A4 substrates. J. Pharm. Exp. Therap. 291, 424–433.
Ekins S., Bravi G., Ring B. J., et al. (1999) Three-dimensional quantitative structure activity relationship analyses of substrates for CYP2B6. J. Pharm. Exp. Therap. 288, 21–29.
deGroot M. J., Ackland M. J., Horne V. A., Alex A. A., and Jones B. C. (1999) A novel approach to predicting P450 mediated drug metabolism. CYP2D6 catalyzed N-dealkylation reactions and qualitative metabolite predictions using a combined protein and pharmacophore model for CYP2D6. J. Med. Chem. 42, 4062–4070.
Hardman J. G., Limbird L. E., Molinoff P. B., Ruddon R. W., and Gilman A. G. (eds.) (1996) Goodman & Gilman’s The Pharmacological Basis of Therapeutics, 9th ed. McGraw-Hill New York
Korzekwa K. R., Jones J. P., and Gillette J. R. (1990) Theoretical studies on cytochrome P450 mediated hydroxylation: a predictive model for hydrogen atom abstractions. J. Am. Chem. Soc. 112, 7042–7046.
Korzekwa K. R. and Jones J. P. (1993) Predicting the cytochrome P450 mediated metabolism of xenobiotics. Pharmacogenetics 3, 1–18.
Korzekwa K. R., Grogan J., DeVito S., and Jones J. P. (1996) Electronic models for cytochrome P450 oxidations. Advances in Experimental Medicine & Biology 387, 361–396.
MDL Information Systems, I. (1999) Available Chemicals Directory, 99.2 ed., San Leandro, CA
Powers D. G., Casebier D. S., Fokas D., Ryan W. J., Troth J. R., and Coffen D. L. (1998) Automated parallel synthesis of chalcone-based screening libraries. Tetrahedron Lett. 54, 4085.
Gillet V. J., Willett P., and Bradshaw J. (1997) The effectiveness of reactant pools for generating structurally-diverse combinatorial libraries. J. Chem. Inf. Comput. Sci. 37, 731–740.
Agrafiotis D. K. and Lobanov V. S. (2000) Ultrafast algorithm for designing focused combinatorial arrays. J. Chem. Inf. Comput. Sci. 40, 1030–1038.
Bravi G., Green D. V.S., Hann M. M., and Leach A. R. (2000) PLUMS: a program for the rapid optimization of focused libraries. J. Chem. Inf. Comput. Sci. 40, 1441–1448.
Breneman C. M. and Rhem M. (1997) QSPR analysis of HPLC column capacity factors for a set of high-energy materials using electronic van der Waals surface property descriptors computed by transferable atom equivalent method. J. Comp. Chem. 18, 182–197.
Pearlman R. S. and Smith K. M. (1999) Metric validation and the receptorrelevant subspace concept. J. Chem. Inf. Comput. Sci. 39, 28–35.
Warr W. A. (1997) Commercial software systems for diversity analysis. Perspectives in Drug Discovery and Design 7/8, 115–130.
Martin E. J., Blaney J. M., Siani M. A., Spellmeyer D. C., Wong A. K., and Moos W. H. (1995) Measuring diversity: experimental design of combinatorial libraries for drug discovery. J. Med. Chem. 38, 1431–1436.
Higgs R. E., Bemis K. G., Watson I. A., and Wikel J. H. (1997) Experimental designs for selecting molecules from large chemical databases. J. Chem. Inf. Comput. Sci. 37, 861–870.
Martin E. J. and Critchlow R. E. (1999) Beyond mere diversity: tailoring combinatorial libraries for drug discovery. J. Comb. Chem. 1, 32–45.
Linusson A., Wold S., and Norden B. (1999) Statistical moelcular design of peptoid libraries. Molecular Diversity 4, 103–114.
Linusson A., Gottfries J., Lindgren F., and Wold S. (2000) Statistical molecular design of building blocks for combinatorial chemistry. J. Med. Chem. 43, 1320–1328.
Mount J., Ruppert J., Welch W., and Jain A. N. (1999) IcePick: A flexible surface-based system for molecular diversity. J. Med. Chem. 42, 60–66.
Pickett S. D., Luttmann C., Guerin V., Laoui A., and James E. (1998) DIVSEL and COMPLIB—strategies for the design and comparison of combinatorial libraries using pharmacophoric descriptors. J. Chem. Inf. Comput. Sci. 38, 144–150.
Clark R. D. (1997) OptiSim: An extended dissimilarity selection method for finding diverse representative subsets. J. Chem. Inf. Comput. Sci. 37, 1181–1188.
Gillet V. J., Willett P., Bradshaw J., and Green D. V.S. (1999) Selecting combinatorial libraries to optimize diversity and physical properties. J. Chem. Inf. Comput. Sci. 39, 169–177.
Zheng W., Cho S. H., Waller C. L., and Tropsha A. (1999) Rational combinatorial library deisgn. 3. Simulated annealing guided evaluation (SAGE) of molecular diversity: A novel computational tool for universal library design and database mining. J. Chem. Inf. Comput. Sci. 39, 738–746.
Good A. C. and Lewis R. A. (1997) New methodology for profiling combinatorial libraries and screening sets: cleaning up the design process with HARPick. J. Med. Chem. 40, 3926–3936.
Sheridan R. P., SanFeliciano S. G., and Kearsley S. K. (2000) Designing targeted libraries with genetic algorithms. J. Molecular Graphics and Modelling 18, 320–334.
Mason J. S. and Beno B. R. (2000) Library design using BCUT chemistry-space descriptors and multiple four-point pharmacophore fingerprints: simultaneous optimization and structure-based diversity. J. Molecular Graphics and Modelling 18, 438–451.
Hassan M., Bielawski J. P., Hempel J. C., and Waldman M. (1996) Optimization and visualization of molecular diversity of combinatorial libraries. Molecular Diversity 2, 64–74.
Borda J. C. D. (1781) Memoire sur les elections au scrutin Histoire de l’Academie Royale des Sciences, Paris
Arrow K. J. (1963) Social choice and individual values, 2nd ed. Wiley New York.
Czerminski R. (2001) Evaluating different approaches to consensus scoring, in preparation.
Saari D. G. (1995) Basic geometry of voting. Springer-Verlag New York.
Meylan W. M., Howard P. H., and Boethling R. S. (1996) Improved method for estimating water solubility from octanol/water partition coefficient. Environmental Toxicology and Chemistry 15, 100–106.
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Manchester, J.I., Hartsough, D.S. (2002). Designing Combinatorial Libraries for Efficient Screening. In: English, L.B. (eds) Combinatorial Library. Methods in Molecular Biology™, vol 201. Springer, Totowa, NJ. https://doi.org/10.1385/1-59259-285-6:307
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DOI: https://doi.org/10.1385/1-59259-285-6:307
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