Literature DB >> 15338948

Virtual screening in lead discovery and optimization.

Ajay N Jain1.   

Abstract

Virtual screening by molecular docking, using a protein with an experimentally determined structure as a target, has become an established method for lead discovery and for enhancing efficiency in lead optimization. Generalizations of the quantitative structure-activity relationship concept have led to approaches for virtual screening in the absence of a protein target structure, instead relying upon ligand-based models as surrogates of protein active sites. Recently reported methods for ligand-based virtual screening can achieve similar enrichment rates to those obtained using molecular docking. This review will discuss recent advances in both domains of virtual screening, including theoretical and practical advances and the implications for their application.

Mesh:

Year:  2004        PMID: 15338948

Source DB:  PubMed          Journal:  Curr Opin Drug Discov Devel        ISSN: 1367-6733


  39 in total

Review 1.  Computer-aided drug discovery and development (CADDD): in silico-chemico-biological approach.

Authors:  I M Kapetanovic
Journal:  Chem Biol Interact       Date:  2006-12-16       Impact factor: 5.192

Review 2.  Structural biology and bioinformatics in drug design: opportunities and challenges for target identification and lead discovery.

Authors:  Tom L Blundell; Bancinyane L Sibanda; Rinaldo Wander Montalvão; Suzanne Brewerton; Vijayalakshmi Chelliah; Catherine L Worth; Nicholas J Harmer; Owen Davies; David Burke
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2006-03-29       Impact factor: 6.237

3.  Design of protein membrane interaction inhibitors by virtual ligand screening, proof of concept with the C2 domain of factor V.

Authors:  Kenneth Segers; Olivier Sperandio; Markus Sack; Rainer Fischer; Maria A Miteva; Jan Rosing; Gerry A F Nicolaes; Bruno O Villoutreix
Journal:  Proc Natl Acad Sci U S A       Date:  2007-07-23       Impact factor: 11.205

4.  Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment.

Authors:  Alexandre Beautrait; Vincent Leroux; Matthieu Chavent; Léo Ghemtio; Marie-Dominique Devignes; Malika Smaïl-Tabbone; Wensheng Cai; Xuegang Shao; Gilles Moreau; Peter Bladon; Jianhua Yao; Bernard Maigret
Journal:  J Mol Model       Date:  2008-01-03       Impact factor: 1.810

5.  Bias, reporting, and sharing: computational evaluations of docking methods.

Authors:  Ajay N Jain
Journal:  J Comput Aided Mol Des       Date:  2007-12-13       Impact factor: 3.686

6.  A small-molecule dengue virus entry inhibitor.

Authors:  Qing-Yin Wang; Sejal J Patel; Eric Vangrevelinghe; Hao Ying Xu; Ranga Rao; Deana Jaber; Wouter Schul; Feng Gu; Olivier Heudi; Ngai Ling Ma; Mee Kian Poh; Wai Yee Phong; Thomas H Keller; Edgar Jacoby; Subhash G Vasudevan
Journal:  Antimicrob Agents Chemother       Date:  2009-02-17       Impact factor: 5.191

Review 7.  Docking Screens for Novel Ligands Conferring New Biology.

Authors:  John J Irwin; Brian K Shoichet
Journal:  J Med Chem       Date:  2016-03-15       Impact factor: 7.446

8.  Structural conservation in band 4.1, ezrin, radixin, moesin (FERM) domains as a guide to identify inhibitors of the proline-rich tyrosine kinase 2.

Authors:  Nathalie Meurice; Lei Wang; Christopher A Lipinski; Zhongbo Yang; Christopher Hulme; Joseph C Loftus
Journal:  J Med Chem       Date:  2010-01-28       Impact factor: 7.446

9.  Total synthesis and evaluation of C26-hydroxyepothilone D derivatives for photoaffinity labeling of beta-tubulin.

Authors:  Emily A Reiff; Sajiv K Nair; John T Henri; Jack F Greiner; Bollu S Reddy; Ramappa Chakrasali; Sunil A David; Ting-Lan Chiu; Elizabeth A Amin; Richard H Himes; David G Vander Velde; Gunda I Georg
Journal:  J Org Chem       Date:  2010-01-01       Impact factor: 4.354

10.  A statistical framework to evaluate virtual screening.

Authors:  Wei Zhao; Kirk E Hevener; Stephen W White; Richard E Lee; James M Boyett
Journal:  BMC Bioinformatics       Date:  2009-07-20       Impact factor: 3.169

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