Multi-parameter optimization: Identifying high quality compounds with a balance of properties

Current Pharmaceutical Design

Volumn 18, Issue 9, 2012, Pages 1292-1310

  Segall, Matthew D ^a  

^a OPTIBRIUM LTD   (United Kingdom)

Author keywords

Admet; Desirability function; Lead identification; Lead optimization; Multi dimensional optimization; Multi objective optimization; Multi parameter optimization; Pareto optimization; Probabilistic scoring

Indexed keywords

ALGORITHM; BIOLOGICAL ACTIVITY; DIGITAL FILTERING; DRUG DEVELOPMENT; DRUG IDENTIFICATION; DRUG QUALITY; DRUG SAFETY; DRUG STRUCTURE; IC 50; LIPOPHILICITY; MOLECULAR WEIGHT; MULTIPARAMETER OPTIMIZATION; PHYSICAL CHEMISTRY; PRIORITY JOURNAL; PROCESS OPTIMIZATION; PRODUCTIVITY; REVIEW;

ANIMALS; DRUG DELIVERY SYSTEMS; DRUG DESIGN; DRUG DISCOVERY; HUMANS; PHARMACEUTICAL PREPARATIONS; PHARMACOKINETICS;

EID: 84857737608     PISSN: 13816128     EISSN: 18734286     Source Type: Journal    
DOI: 10.2174/138161212799436430     Document Type: Review

References (57)

1. Paul S, Mytelka D, Dunwiddie D, Persinger C, Munos B, Lindborg S, Schacht A. How to improve R&D productivity: the pharmaceutical industry's grand challenge. Nat Rev Drug Discov 2010; 9: 203-14.
2. Chadwick AT, Segall MD. Overcoming psychological barriers to good discovery decisions. Drug Discov Today 2010; 15: 561-9.
3. Kola I, Landis J. Can the pharmaceutical industry reduce attrition rates. Nature Rev Drug Discov 2004; 3: 711-6.
4. Dimasi J, Hansen R, Grabowski H. The price of innovation: new esitmates of drug development costs. J Health Econ 2003; 22: 151-85.
5. Barnett Educational Services. PAREXEL Biopharmaceutical R&D Statistical Sourcebook 2010/2011. Waltham: Parexel International Corporation; 2010.
6. Segall MD. Why is it still Drug Discovery? European Biopharmaceutical Review 2008.
7. Segall MD, Champness E. The difference between guiding and supporting decisions: Enhancing decisions and improving success in drug discovery. Genetic Engineering News 2010 September.
8. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ. Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 1997; 23: 3-25.
9. Veber DF, Johnson SR, Cheng HY, Smith BR, Ward KW, Kopple KD. Molecular properties that influence the oral bioavailability of drug candidates. J Med Chem 2002; 45: 2615-23.
10. Lu JJ, Crimin K, Goodwin JT, et al. Influence of Molecular Flexibility and Polar Surface Area Metrics on Oral Bioavailability in the Rat. J Med Chem 2004; 47: 6104-7.
11. Johnson TW, Dress KR, Edwards M. Using the Golden Triangle to optimize clearance and oral absorption. Bioorg Med Chem Lett 2009; 19: 5560-4.
12. Lovering F, Bikker J, Humblet C. Escape from flatland: increasing saturation as an approach to improving clinical success. J Med Chem 2009; 52: 6752-6.
13. Ritchie TJ, Macdonald SJF. The impact of aromatic ring count on compound developability - are too many aromatic rings a liability in drug design? Drug Discov Today 2009; 14: 1011-20.
14. Hughes JD, Blagg J, Price DA, et al. Physiochemical drug properties associated with in vivo toxicological outcomes. Bioorg Med Chem Lett 2008; 18: 4872-5.
15. Choy YB, Prausnitz MR. The rule of five for non-oral routes of drug delivery: ophthalmic, inhalation and transdermal. Pharm Res 2011; 28: 943-8.
16. Hidalgo IJ, Raub, TJ, Borchardt RT. Characterization of the human colon carcinoma cell line (Caco-2) as a model system for intestinal epithelial permeability. Gastroenterology 1989; 96: 736-49.
17. Schoonen WG, de Roos JA, Westerink WM, Débiton E. Cytotoxic effects of 110 reference compounds on HepG2 cells and for 60 compounds on HeLa, ECC-1 and CHO cells. II mechanistic assays on NAD(P)H, ATP and DNA contents. Toxicol. In vitro 2005; 19: 491-503.
18. Hopkins AL, Groom CR, Alexander A. Ligand Efficiency: a useful metric for lead selection. Drug Discov Today 2004; 9: 430-1.
19. Carr RAE, Congreve M, Murray CW, Rees DC. Fragment-based lead discovery: leads by design. Drug Discov Today 2005; 10: 987-92.
20. Leeson PD, Springthorpe B. The influence of drug-like concepts on decision-making in medicinal chemistry. Nat Rev Drug Discov 2007; 6: 881-90.
21. Hughes JD, Blagg J, Price DA, et al. Physicochemical drug properties associated with in vivo toxicological outcomes. Bioorg Med Chem Lett 2008; 18: 4872-5.
22. Edwards MP, Price D. Role of physicochemical properties and ligand lipophilicity efficiency in addressing drug safety risks. Ann Reports Med Chem 2010; 45: 381-91.
23. Abad-Zapatero C. Ligand efficiency indices for effective drug discovery. Expert Opin Drug Discov 2007; 2: 469-88.
24. Keseru GM, Makara GM. The influence of lead discovery strategies on the properties of drug candidates. Nat Rev Drug Discov 2009; 8: 203-12.
25. Reynolds CH, Bembenek SD, Tounge BA. The role of molecular size in ligand efficiency. Bioorg Med Chem Lett 2007; 17: 4285-61.
26. Ladbury JE, Klebe G, Freire E. Adding calorimetric data to decision making in lead discovery: a hot tip. Nature Rev Drug Discov 2010; 9: 23-7.
27. Ferenczy GG, Keseru GM. Thermodynamics guided lead discovery and optimization. Drug Discov Today 2010; 15: 919-32.
28. Jaffe W. Pareto translated: A review article. J Economic Literature 1972; 10: 1190-201.
29. Kruisselbrink J, Michael E, Back T, et al. Combining aggregation with Pareto optimization: A case study in evolutionary molecular design. In: Proceedings of EMO '09: Lect. Notes Comput Sci 2009; Berlin/Heidelberg. p. 453-467.
30. Harrington EC. The desirability function. Ind Qual Control 1965; 21: 494-8.
31. Derringer G, Suich R. Simultaneous optimization of several response variables. J Quality Technology 1980; 12: 214-9.
32. Segall MD, Champness E, Obrezanova O.C.L. Guiding the decision-making process to identify high quality compounds. Drug Metab. Rev 2009; 41: 7-186 Abstract 244.
33. Segall M, Beresford A, Gola J, Hawksley D, MH T. Focus on success: using a probabilistic approach to achieve an optimal balance of properties in drug discovery. Expert Opin Drug Metab Toxicol 2006; 2: 325-37.
34. Segall M, Champness E, Obrezanova O, Leeding C. Beyond profiling: Using ADMET models to guide decisions. Chem Biodiversity 2009; 6: 2144-51.
35. Hopkins AL. The Practice of Medicinal Chemistry. London: Academic Press; 2008. p. 521-32.
36. Bohacek RS, McMartin C, Guida WC. The art and practice of structure-based drug design: a molecular modeling perspective. Med Res Rev 1996; 16: 3-50.
37. DE, editor. Evolutionary Algorithms in Computer-Aided Molecular Design. Weinheim: Wiley-VCH; 2000.
38. Brown N, McKay B, Gilardoni F, Gasteiger J. A graph-based genetic algorithm and its application to the multiobjective evolution of median molecules. J Chem Inf Comput Sci 2004; 44: 1079-87.
39. Stewart K, Shiroda M, James C. Drug Guru: a computer software program for drug design using medicinal chemistry rules. Bioorg Med Chem 2006; 14: 7011-22.
40. Segall MD, Champness, EJ, Leeding C, Lilien R, Mettu R, Stevens B. Applying medicinal chemistry transformations and multi-parameter optimization to guide the search for high-quality leads and candidates. J Chem Inf Model 2011; 51: 2967-2976.
41. Brown N, McKay B, Gasteiger J. A novel workflow for the inverse QSAR problem using multiobjective optimization. J Comp Aided Mol Design 2006; 20: 333-41.
42. Boda K, Seidel T, Gasteiger J. Structure and reaction based evaluation of synthetic accessibility. J Comp Aided Mol Des 2007; 21: 311-25.
43. Nicolaou CA, Brown NA, Pattichis CS. Molecular optimization using computational multi-objective methods. Curr Opin Drug Discov Devel 2007; 10: 316-24.
44. Rogers DJ, Tanimoto TT. A computer program for classifying plants. Science 1960; 132: 1115-8.
45. Agrafiotis DK. Diversity of chemical libraries. In: Schleyer P, Allinger NL, Clark T, Gasteiger J, Kollman PA, Schaefer III HF, P.R. S, editors. The Encyclopedia of Computational Chemistry. Vol 1. Chichester: John Wiley and Sons 1998; p. 742-61.
46. Jones G. Genetic and evolutionary algorithms. In: Schleyer P, Allinger NL, Clark T, Gasteiger J, Kollman PA, Schaefer III HF, P.R. S, editors. Encyclopedia of Computational Chemistry. Chichester: John Wiley and Sons; 1998.
47. Gillet VJ, Khatib W, Willett P, Fleming PJ, Green DVS. Combinatorial library design Using a multiobjective genetic algorithm. J Chem Inf Comput Sci 2002; 42: 375-85.
48. Fonesca CM, Fleming PJ. Genetic algorithms for multiobjective optimization: formulation, discussion and generalisation. In: Forrest S, editor. Genetic Algorithms: Proceedings of the Fifth International Conference; 1993; San Mateo, CA. p. 416-23.
49. Wager TT, Hour X, Villalobos A. Moving beyond rules: The development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of druglike properties. ACS Chem Neurosci 2010; 1: 435-49.
50. Ekins S, Honeycutt JD, Metz JT. Evolving molecules using muti-objective optimization: applying to ADME/Tox. Drug Discov Today 2010; 15: 451-60.
51. Evans BK, Rittle KE, Bock MG, et al. Methods for drug discovery: development of potent, selective, orally effective cholecystokinin antagonists. J Med Chem 1988; 31: 2235-46.
52. Rogers D, Brown RD, Hahn M. Using extended-connectivity fingerprints with Laplacian-modified Bayesian analysis in high-throughput screening follow-up. J Biomol Screen 2005; 10: 682-6.
53. Muchmore SW, Debe DA, Metz JT, Brown SP, Martin YC, Hajduk PJ. Application of belief theory to similarity data fusion for use in analog searching and lead hopping. J Chem Inf Model 2008; 48: 941-8.
54. Metz JT, Huth JR, Hajduk PJ. Enhancement of chemical rules for predicting compound reactivity towards protein thiol groups. J Comput Aided Mol Des 2007; 21: 139-44.
55. Nicolaou CA, Apostolakis J, Pattichis CS. De novo drug design using multiobjective evolutionary graphs. J Chem Inf Model 2009; 49: 295-307.
56. Optibrium. [Internet]. [cited 2011 March 3]. Available from: http: //www.optibrium.com/stardrop.
57. Lusher SJ, McGuire R, Azevedo R, Boiten JW, van Schaik RC, de Vlieg J. A molecular informatics view on best practice in multi-parameter compound optimization. Drug Discov Today 2011; 16: 555-68.