Comparison of three preprocessing filters efficiency in virtual screening: identification of new putative LXRbeta regulators as a test case
Identifieur interne : 002D61 ( Main/Merge ); précédent : 002D60; suivant : 002D62Comparison of three preprocessing filters efficiency in virtual screening: identification of new putative LXRbeta regulators as a test case
Auteurs : Leo Ghemtio [France] ; Marie-Dominique Devignes [France] ; Malika Smaïl-Tabbone [France] ; Michel Souchet [France] ; Vincent Leroux [France] ; Bernard Maigret [France]Source :
- Journal of Chemical Information and Modeling [ 1549-9596 ] ; 2010-05-24.
Abstract
In silico screening methodologies are widely recognized as efficient approaches in early steps of drug discovery. However, in the virtual high-throughput screening (VHTS) context, where hit compounds are searched among millions of candidates, three-dimensional comparison techniques and knowledge discovery from databases should offer a better efficiency to finding novel drug leads than those of computationally expensive molecular dockings. Therefore, the present study aims at developing a filtering methodology to efficiently eliminate unsuitable compounds in VHTS process. Several filters are evaluated in this paper. The first two are structure-based and rely on either geometrical docking or pharmacophore depiction. The third filter is ligand-based and uses knowledge-based and fingerprint similarity techniques. These filtering methods were tested with the Liver X Receptor (LXR) as a target of therapeutic interest, as LXR is a key regulator in maintaining cholesterol homeostasis. The results show that the three considered filters are complementary so that their combination should generate consistent compound lists of potential hits.
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<series><title level="j">Journal of Chemical Information and Modeling</title>
<idno type="ISSN">1549-9596</idno>
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<front><div type="abstract" xml:lang="en">In silico screening methodologies are widely recognized as efficient approaches in early steps of drug discovery. However, in the virtual high-throughput screening (VHTS) context, where hit compounds are searched among millions of candidates, three-dimensional comparison techniques and knowledge discovery from databases should offer a better efficiency to finding novel drug leads than those of computationally expensive molecular dockings. Therefore, the present study aims at developing a filtering methodology to efficiently eliminate unsuitable compounds in VHTS process. Several filters are evaluated in this paper. The first two are structure-based and rely on either geometrical docking or pharmacophore depiction. The third filter is ligand-based and uses knowledge-based and fingerprint similarity techniques. These filtering methods were tested with the Liver X Receptor (LXR) as a target of therapeutic interest, as LXR is a key regulator in maintaining cholesterol homeostasis. The results show that the three considered filters are complementary so that their combination should generate consistent compound lists of potential hits.</div>
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