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OMICS. 2009 Aug;13(4):325-30. doi: 10.1089/omi.2009.0045.

MetaPocket: a meta approach to improve protein ligand binding site prediction.

Author information

1
EML Research gGmbH, Schloss-Wolfsbrunnenweg 33, 69118, Heidelberg, Germany. bingding.huang@eml-r.villa-bosch.de

Abstract

The identification of ligand-binding sites is often the starting point for protein function annotation and structure-based drug design. Many computational methods for the prediction of ligand-binding sites have been developed in recent decades. Here we present a consensus method metaPocket, in which the predicted sites from four methods: LIGSITE(cs), PASS, Q-SiteFinder, and SURFNET are combined together to improve the prediction success rate. All these methods are evaluated on two datasets of 48 unbound/bound structures and 210 bound structures. The comparison results show that metaPocket improves the success rate from approximately 70 to 75% at the top 1 prediction. MetaPocket is available at http://metapocket.eml.org .

PMID:
19645590
DOI:
10.1089/omi.2009.0045
[Indexed for MEDLINE]

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