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QSAR Modeling of GPCR Ligands: Methodologies and Examples of Applications

  • A. Tropsha
  • S. X. Wang
Conference paper
Part of the Ernst Schering Foundation Symposium Proceedings book series (SCHERING FOUND, volume 2006/2)

Abstract

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.

Keywords

Partial Little Square Quantitative Structure Activity Relationship Virtual Screening Target Property Quantitative Structure Activity Relationship Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

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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Copyright information

© Springer-Verlag 2007

Authors and Affiliations

  1. 1.The Laboratory for Molecular Modeling, CB#7360Beard Hall, School of PharmacyNorth CarolinaUSA

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