| Literature DB >> 20438859 |
Sean Ekins1, J Dana Honeycutt, James T Metz.
Abstract
Modern drug discovery involves the simultaneous optimization of many physicochemical and biological properties that transcends the historical focus on bioactivity alone. The process of resolving many requirements is termed 'multi-objective optimization', and here we discuss how this can be used for drug discovery, focusing on evolutionary molecule design to incorporate optimal predicted absorption, distribution, metabolism, excretion and toxicity properties. We provide several examples of how Pareto optimization implemented in Pareto Ligand Designer can be used to make trade-offs between these different predicted or real molecular properties to result in better predicted compounds. (c) 2010 Elsevier Ltd. All rights reserved.Entities:
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Year: 2010 PMID： 20438859 DOI： 10.1016/j.drudis.2010.04.003
Source DB: PubMed Journal: Drug Discov Today ISSN： 1359-6446 Impact factor: 7.851