Analyzing compound and project progress through multi-objective-based compound quality assessment

Future Medicinal Chemistry

Volumn 5, Issue 7, 2013, Pages 753-767

  Nissink, J Willem M ^a   Degorce, Sébastien ^a  

^a ASTRAZENECA   (United Kingdom)

Author keywords

[No Author keywords available]

Indexed keywords

AZAURACIL;

ANALYTIC METHOD; ARTICLE; COMPOUND QUALITY SCORING METHOD; DRUG BIOAVAILABILITY; DRUG CLEARANCE; DRUG DESIGN; DRUG QUALITY; DRUG SOLUBILITY; DRUG SYNTHESIS; IC 50; NONHUMAN; PRIORITY JOURNAL; QUALITY CONTROL; RAT; RESOURCE MANAGEMENT;

ALGORITHMS; CYTOCHROME P-450 ENZYME SYSTEM; DRUG DESIGN; HUMANS; MICROSOMES, LIVER; MODELS, THEORETICAL; PHARMACEUTICAL PREPARATIONS; PROTEIN BINDING; RECEPTORS, PURINERGIC P2X; SOLUBILITY;

EID: 84877586386     PISSN: 17568919     EISSN: 17568927     Source Type: Journal    
DOI: 10.4155/fmc.13.45     Document Type: Article

References (25)

1. Kuntz ID, Chen K, Sharp KA, Kollman PA. The maximal affinity of ligands. Proc. Natl Acad. Sci. USA 96, 9997-10002 (1999).
2. Nissink JW. Simple size-independent measure of ligand efficiency. J. Chem. Inf. Model. 49(6), 1617-1622 (2009).
3. Reynolds CH, Tounge BA, Bembenek SD. Ligand binding efficiency: trends, physical bias, and implications. J. Med. Chem. 51, 2432-2438 (2008).
4. Lajiness MS, Maggiora GM, Shanmugasundaram V. Assessment of the consistency of medicinal chemists in reviewing sets of compounds. J. Med. Chem. 47(20), 4891-4896 (2004).
5. Takaoka Y, Endo Y, Yamanobe S, et al. Development of a method for evaluating drug-likeness and ease of synthesis using a data set in which compounds are assigned scores based on chemists' intuition. J. Chem. Inf. Comput. Sci. 43, 1269-1275 (2003).
6. Segall M, Chadwick A. The risks of subconscious biases in drug-discovery decision making. Future Med. Chem. 3, 771-774 (2011).
7. Harrington J. The desirability function. Industrial Quality Control 21, 494-498 (1965).
8. Derringer G, Suich R. Simultaneous optimization of several response variables. J. Qual. Technol. 12(4), 214-219 (1980).
9. Wager TT, Hour XVPR., Villalobos A. Moving beyond rules: the development of a central nervous system multiparameter optimization (CNS MPO) approach to enable alignment of drug-like properties. ACS Chem. Neurosci. 1, 435-449 (2010).
10. Bickerton GR, Paolini GV, Besnard J, Muresan S, Hopkins AL. Quantifying the chemical beauty of drugs. Nat. Chem. 4, 90-98 (2012).
11. 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. 44(3), 1079-1087 (2004).
12. Nicolaou CA, Brown N, Pattichis CS. Molecular optimization using computational multi-objective methods. Curr. Opin. Drug Discov. Devel. 10(3), 316-324 (2007).
13. Ekins S, Honeycutt JD, Metz JT. Evolving molecules using multi-objective optimization: applying to ADME/Tox. Drug Discov. Today 15(11-12), 451-460 (2010).
14. 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 16(13-14), 555-568 (2011).
15. Nicolotti O, Giangreco I, Introcaso A, Leonetti F, Stefanachi A, Carotti A. Strategies of multi-objective optimization in drug discovery and development. Expert Opin. Drug Discov. 6(9), 871-884 (2011).
16. Gillet VJ, Willett P, Fleming PJ, Green DV. Designing focussed libraries using MoSELECT. J. Mol. Graph. Model. 20, 491-498 (2002).
17. Cruz-Monteagudo M, PhamThe H, Cordeiro NMDS, Borge F. Prioritizing hits with appropriate trade-offs between HIV-1 reverse transcriptase inhibitory efficacy and MT4 blood cells toxicity through desirability-based multiobjective optimization and ranking. Mol. Inform. 12, 303-321 (2010).
18. Segall M, Champness E, Leeding C, Lilien R, Mettu R, Stevens B. applying medicinal chemistry transformations and multiparameter optimization to guide the search for high-quality leads and candidates. J. Chem. Inf. Model. 51(11), 2967-2976 (2011).
19. Segall MD. multi-parameter optimization: identifying high quality compounds with a balance of properties. Curr. Pharm. Des. 18, 1292-1310 (2012).
20. Plowright AT, Johnston C, Kihlberg J, Petterson J, Robb G, Thompson RA. Hypothesis driven drug design: improving quality and effectiveness of the design-make- test-analyse cycle. Drug Discov. Today 17, 56-62 (2012).
21. Baxter A, Bent J, Bowers K, et al. Hit-to-lead studies: the discovery of potent adamantane Amide P2X7 receptor antagonists Bioorg. Med. Chem. Lett. 13, 4047-4050 (2003).
22. Furber M, Alcaraz L, Bent JE, et al. Discovery of potent and selective adamantane-based small-molecule P2X7 receptor antagonists/interleukin-1b inhibitors. J. Med. Chem. 50, 5882-5885 (2007).
23. Guile SD, Alcaraz L, Birkinshaw TN, et al. Antagonists of the P2X7 receptor from lead identification to drug development J. Med. Chem. 52, 3123-3141 (2009).
24. Gum RJ, Wakefield B, Jarvis MF: P2X receptor antagonists for pain management: examination of binding and physicochemical properties. Purinergic Signal. 8(Suppl. 1), S41-S56 (2012).
25. Besnard J, Ruda JF, Setola V, et al. Automated design of ligands to polypharmacological profiles. Nature 492, 215-220 (2012).