QSAR Modeling of GPCR Ligands: Methodologies and Examples of Applications
GPCR ligands represent not only one of the major classes of current drugs but the major continuing source of novel potent pharmaceutical agents. Because 3D structures of GPCRs as determined by experimental techniques are still unavailable, ligand-based drug discovery methods remain the major computational molecular modeling approaches to the analysis of growing data sets of tested GPCR ligands. This paper presents an overview of modern Quantitative Structure Activity Relationship (QSAR) modeling. We discuss the critical issue of model validation and the strategy for applying the successfully validated QSAR models to virtual screening of available chemical databases. We present several examples of applications of validated QSAR modeling approaches to GPCR ligands. We conclude with the comments on exciting developments in the QSAR modeling of GPCR ligands that focus on the study of emerging data sets of compounds with dual or even multiple activities against two or more of GPCRs.
KeywordsPartial Little Square Quantitative Structure Activity Relationship Virtual Screening Target Property Quantitative Structure Activity Relationship Model
This work was supported in part by the NIH research grant GM066940 and by Berlex Biosciences. We appreciate fruitful discussions with Drs. R. Horuk and Sabine Schlyer.
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