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

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Abstract

Numerous methods are available for use as part of a virtual screening strategy but, as yet, no single method is able to guarantee both a level of confidence comparable to experimental screening and a level of computing efficiency that could drastically cut the costs of early phase drug discovery campaigns. Here, we present VSM-G (virtual screening manager for computational grids), a virtual screening platform that combines several structure-based drug design tools. VSM-G aims to be as user-friendly as possible while retaining enough flexibility to accommodate other in silico techniques as they are developed. In order to illustrate VSM-G concepts, we present a proof-of-concept study of a fast geometrical matching method based on spherical harmonics expansions surfaces. This technique is implemented in VSM-G as the first module of a multiple-step sequence tailored for high-throughput experiments. We show that, using this protocol, notable enrichment of the input molecular database can be achieved against a specific target, here the liver-X nuclear receptor. The benefits, limitations and applicability of the VSM-G approach are discussed. Possible improvements of both the geometrical matching technique and its implementation within VSM-G are suggested.

Basic principle of the virtual screening funnel process.

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Notes

  1. Redocking experiments of LXRβ reference ligands present in the X-ray structures back up this hypothesis. Using GOLD, the 1PQ6 ligand redocked in the 1PQ6 binding pocket conformation yields a significantly higher score than the 1PQ9 ligand redocked in the 1PQ9 conformation. However, according to experimental data, the 1PQ9 ligand is indeed clearly more potent on LXRβ than the 1PQ6 ligand, further indicating that the protein–ligand interaction could not be the dominant term in the free energy of binding

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Acknowledgements

We thank Yesmine Asses, Safia Kellou and Amel Maouche for their feedback. Alexandre Beautrait was supported by grants from INRIA (Institut National de Recherche en Informatique et en Automatique), Région Lorraine, and ARC (Association pour la Recherche sur le Cancer); Vincent Leroux by a post-doctoral fellowship from the INCa (Institut National du Cancer); Matthieu Chavent by a joint fellowship between CNRS (Centre National pour la Recherche Scientifique) and Région Lorraine. We thank Openeye for providing free access to OMEGA and VIDA software according to an academic license, Chemaxon for supplying MarvinBeans Java library, CCDC for the trial version of the GOLD program, and the laboratory of chemoinformatics at the Orléans University for the ScreeningAssistant program.

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Authors and Affiliations

  1. Nancy Université, LORIA, Groupe ORPAILLEUR, Campus scientifique, BP 239, 54506, Vandœuvre-lès-Nancy Cedex, France

    Alexandre Beautrait, Vincent Leroux, Matthieu Chavent, Léo Ghemtio, Marie-Dominique Devignes, Malika Smaïl-Tabbone & Bernard Maigret

  2. Department of Chemistry, Nankai University, Tianjin, 300071, People’s Republic of China

    Wensheng Cai & Xuegang Shao

  3. 330 Avenue Jean Jaurès, 94220, Charanton, France

    Gilles Moreau

  4. Interprobe Chemical Services, Gallowhill House, Larch Avenue, Lenzie Kirkintilloch, Glasgow, G66 4HX, Scotland, UK

    Peter Bladon

  5. Laboratory of Computer Chemistry and Chemoinformatics, Shanghai Institute of Organic Chemistry, 354 Fenglin Road, Shanghai, 200032, People’s Republic of China

    Jianhua Yao

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  1. Alexandre Beautrait
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Correspondence to Bernard Maigret.

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Beautrait, A., Leroux, V., Chavent, M. et al. Multiple-step virtual screening using VSM-G: overview and validation of fast geometrical matching enrichment. J Mol Model 14, 135–148 (2008). https://doi.org/10.1007/s00894-007-0257-9

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  • DOI: https://doi.org/10.1007/s00894-007-0257-9

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