Application of QSAR and shape pharmacophore modeling approaches for targeted chemical library design.
Optimization of chemical library composition affords more efficient identification of hits from biological screening experiments. The optimization could be achieved through rational selection of reagents used in combinatorial library synthesis. However, with a rapid advent of parallel synthesis methods and availability of millions of compounds synthesized by many vendors, it may be more efficient to design targeted libraries by means of virtual screening of commercial compound collections. This chapter reviews the application of advanced cheminformatics approaches such as quantitative structure-activity relationships (QSAR) and pharmacophore modeling (both ligand and structure based) for virtual screening. Both approaches rely on empirical SAR data to build models; thus, the emphasis is placed on achieving models of the highest rigor and external predictive power. We present several examples of successful applications of both approaches for virtual screening to illustrate their utility. We suggest that the expert use of both QSAR and pharmacophore models, either independently or in combination, enables users to achieve targeted libraries enriched with experimentally confirmed hit compounds.
Ebalunode
Jerry O
JO
Department of Pharmaceutical Sciences, BRITE Institute, North Carolina Center University, Durham, NC, USA. jebalunode@nccu.edu
Zheng
Weifan
W
Tropsha
Alexander
A
D004353:Drug Evaluation, Preclinical / Q000379:methods*; D008958:Models, Molecular; D021281:Quantitative Structure-Activity Relationship; D054852:Small Molecule Libraries / Q000737:chemistry* / Q000494:pharmacology*; D014584:User-Computer Interface
D054852:Small Molecule Libraries