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

  • Huang B
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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 .

Author-supplied keywords

  • Algorithms; Binding Sites; Computational Biology
  • Molecular; Protein Binding; Protein Interaction M
  • Protein
  • Protein; Ligands; Models
  • chemistry; Sequence Analysis
  • methods; Databases
  • methods; Proteins
  • methods; Software

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  • Bingding Huang

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