title: Development of a protein-ligand-binding site prediction method based on interaction energy and sequence conservation.
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.
authors.affiliation: Department of Biotechnology, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-8657, Japan.
authors.forename: Hiroto
authors.initials: H
authors.lastname: Tsujikawa
authors.affiliation: Department of Biotechnology, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-8657, Japan.
authors.forename: Kenta
authors.initials: K
authors.lastname: Sato
authors.affiliation: Department of Biotechnology, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-8657, Japan.
authors.forename: Cao
authors.initials: C
authors.lastname: Wei
authors.affiliation: Department of Biotechnology, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-8657, Japan.
authors.forename: Gul
authors.initials: G
authors.lastname: Saad
authors.affiliation: Department of Biotechnology, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-8657, Japan.
authors.forename: Kazuya
authors.initials: K
authors.lastname: Sumikoshi
authors.affiliation: Department of Biotechnology, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-8657, Japan.
authors.forename: Shugo
authors.initials: S
authors.lastname: Nakamura
authors.affiliation: Department of Biotechnology, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-8657, Japan.
authors.forename: Tohru
authors.initials: T
authors.lastname: Terada
authors.affiliation: Department of Biotechnology, The University of Tokyo, 1-1-1 Yayoi, Bunkyo-Ku, Tokyo, 113-8657, Japan. shimizu@bi.a.u-tokyo.ac.jp.
authors.forename: Kentaro
authors.identifier: http://orcid.org/0000-0002-3245-0052
authors.initials: K
authors.lastname: Shimizu
mesh_terms: D001665:Binding Sites; D030562:Databases, Protein; D008958:Models, Molecular; D020539:Sequence Analysis, Protein; D012984:Software; D019809:Streptavidin / Q000737:chemistry / Q000235:genetics
chemical_list: D019809:Streptavidin
keywords: Binding site prediction; Interaction energy; Protein structure; Protein–ligand binding; Sequence conservation