ArticleJournal of structural and functional genomics2016
Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservation.
Article in Journal of structural and functional genomics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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5 citing papers in PubMed.
- Article
- Shape Theory Applied to Molecular Docking and Automatic Localization of Ligand Binding Pockets in Large Proteins.ACS omega · 2022Article
- Applications of machine learning in computer-aided drug discovery.QRB discovery · 2022Review
- Computational methods and tools for binding site recognition between proteins and small molecules: from classical geometrical approaches to modern machine learning strategies.Journal of computer-aided molecular design · 2019Article
- Docking study of flavonoid derivatives as potent inhibitors of influenza H1N1 virus neuraminidase.Biomedical reports · 2019Article
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8 authors.
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Abstract
We present a new method for predicting protein-ligand-binding sites based on protein three-dimensional structure and amino acid conservation. This method involves calculation of the van der Waals interaction energy between a protein and many probes placed on the protein surface and subsequent clustering of the probes with low interaction energies to identify the most energetically favorable locus. In addition, it uses amino acid conservation among homologous proteins. Ligand-binding sites were predicted by combining the interaction energy and the amino acid conservation score. The performance of our prediction method was evaluated using a non-redundant dataset of 348 ligand-bound and ligand-unbound protein structure pairs, constructed by filtering entries in a ligand-binding site structure database, LigASite. Ligand-bound structure prediction (bound prediction) indicated that 74.0 % of predicted ligand-binding sites overlapped with real ligand-binding sites by over 25 % of their volume. Ligand-unbound structure prediction (unbound prediction) indicated that 73.9 % of predicted ligand-binding residues overlapped with real ligand-binding residues. The amino acid conservation score improved the average prediction accuracy by 17.0 and 17.6 points for the bound and unbound predictions, respectively. These results demonstrate the effectiveness of the combined use of the interaction energy and amino acid conservation in the ligand-binding site prediction.
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