Document Detail


Multi-Objective Particle Swarm Optimization: Automated Identification of SAR-Informative Compounds with Favorable Physicochemical Property Distributions.
MedLine Citation:
PMID:  23039232     Owner:  NLM     Status:  Publisher    
Abstract/OtherAbstract:
The selection of active compounds for chemical optimization efforts typically requires the consideration of multiple properties beyond potency. Herein we introduce a multi-objective particle swarm optimization approach to automatically extract compound subsets from large data sets that reveal structure-activity relationship (SAR) information and display physicochemical property distributions that are indicative of favorable absorption, distribution, metabolism, and excretion (ADME) characteristics. The approach is based on Pareto optimization of multiple objectives and does not require subjective intervention. It is automated and can be easily modified. We have applied the method to screen 10 compound data sets of different composition and global SAR phenotypes. In five of these data sets, between one and more than hundred compound subsets were identified that represented discontinuous local SARs and had desirable property distributions.
Authors:
Vigneshwaran Namasivayam; Jürgen Bajorath
Publication Detail:
Type:  JOURNAL ARTICLE     Date:  2012-10-7
Journal Detail:
Title:  Journal of chemical information and modeling     Volume:  -     ISSN:  1549-960X     ISO Abbreviation:  J Chem Inf Model     Publication Date:  2012 Oct 
Date Detail:
Created Date:  2012-10-8     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101230060     Medline TA:  J Chem Inf Model     Country:  -    
Other Details:
Languages:  ENG     Pagination:  -     Citation Subset:  -    
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