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Pharmacophore modeling: advances, limitations, and current utility in drug discovery

Authors Qing X, Lee XY, De Raeymaecker J, Tame J, Zhang K, De Maeyer M, Voet A

Received 21 July 2014

Accepted for publication 14 August 2014

Published 11 November 2014 Volume 2014:7 Pages 81—92

DOI https://doi.org/10.2147/JRLCR.S46843

Checked for plagiarism Yes

Review by Single-blind

Peer reviewer comments 3

Editor who approved publication: Professor Trevor W. Stone


Video abstract presented by Xiaoyu Qing and Xiaoyin Lee

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Xiaoyu Qing,1,* Xiao Yin Lee,2,* Joren De Raeymaeker,1 Jeremy RH Tame,3 Kam YJ Zhang,2 Marc De Maeyer,1 Arnout RD Voet1,2
 
1Laboratory for Biomolecular Modelling, Department of Chemistry, Katholieke Universiteit Leuven, Heverlee, Belgium; 2Structural Bioinformatics Team, Center for Life Science Technologies, RIKEN, Yokohama, Kanagawa, Japan; 3Drug Design Laboratory, Yokohama City University, Yokohama, Kanagawa, Japan

*These authors contributed equally to this work

Abstract: Pharmacophore modeling is a successful yet very diverse subfield of computer-aided drug design. The concept of the pharmacophore has been widely applied to the rational design of novel drugs. In this paper, we review the computational implementation of this concept and its common usage in the drug discovery process. Pharmacophores can be used to represent and identify molecules on a 2D or 3D level by schematically depicting the key elements of molecular recognition. The most common application of pharmacophores is virtual screening, and different strategies are possible depending on the prior knowledge. However, the pharmacophore concept is also useful for ADME-tox modeling, side effect, and off-target prediction as well as target identification. Furthermore, pharmacophores are often combined with molecular docking simulations to improve virtual screening. We conclude this review by summarizing the new areas where significant progress may be expected through the application of pharmacophore modeling; these include protein–protein interaction inhibitors and protein design.

Keywords: ADME-tox, computer-aided drug design, pharmacophore fingerprint, protein design, virtual screening
 

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