Literature DB >> 18452211

Highly accurate method for ligand-binding site prediction in unbound state (apo) protein structures.

Mizuki Morita1, Shugo Nakamura, Kentaro Shimizu.   

Abstract

This article describes a new method for predicting ligand-binding sites of proteins. The method involves calculating the van der Waals interaction energy between a protein and probes placed on the protein surface, and then clustering the probes with attractive interaction to find the energetically most favorable locus. In 80% (28/35) of the test cases, the ligand-binding site was successfully predicted on a ligand-bound protein structure, and in 77% (27/35) was successfully predicted on an unbound structure. Our method was used to successfully predict ligand-binding sites unaffected by induced-fit as long as its scales were not very large, and it contributed to a significant improvement in prediction with unbound state protein structures. This represents a significant advance over conventional methods in detecting ligand-binding sites on uncharacterized proteins. Moreover, our method can predict ligand-binding sites with a narrower locus than those achieved using conventional methods.

Mesh:

Substances:

Year:  2008        PMID: 18452211     DOI: 10.1002/prot.22067

Source DB:  PubMed          Journal:  Proteins        ISSN: 0887-3585


  13 in total

1.  Automated identification of binding sites for phosphorylated ligands in protein structures.

Authors:  Dario Ghersi; Roberto Sanchez
Journal:  Proteins       Date:  2012-07-07

2.  BUDDY-system: A web site for constructing a dataset of protein pairs between ligand-bound and unbound states.

Authors:  Mizuki Morita; Tohru Terada; Shugo Nakamura; Kentaro Shimizu
Journal:  BMC Res Notes       Date:  2011-05-22

Review 3.  Beyond structural genomics: computational approaches for the identification of ligand binding sites in protein structures.

Authors:  Dario Ghersi; Roberto Sanchez
Journal:  J Struct Funct Genomics       Date:  2011-05-03

4.  Accuracy of functional surfaces on comparatively modeled protein structures.

Authors:  Jieling Zhao; Joe Dundas; Sema Kachalo; Zheng Ouyang; Jie Liang
Journal:  J Struct Funct Genomics       Date:  2011-05-04

5.  Prediction of calcium-binding sites by combining loop-modeling with machine learning.

Authors:  Tianyun Liu; Russ B Altman
Journal:  BMC Struct Biol       Date:  2009-12-11

6.  Ligand-binding site prediction of proteins based on known fragment-fragment interactions.

Authors:  Kota Kasahara; Kengo Kinoshita; Toshihisa Takagi
Journal:  Bioinformatics       Date:  2010-05-13       Impact factor: 6.937

7.  webPDBinder: a server for the identification of ligand binding sites on protein structures.

Authors:  Valerio Bianchi; Iolanda Mangone; Fabrizio Ferrè; Manuela Helmer-Citterich; Gabriele Ausiello
Journal:  Nucleic Acids Res       Date:  2013-06-03       Impact factor: 16.971

8.  Identification of binding pockets in protein structures using a knowledge-based potential derived from local structural similarities.

Authors:  Valerio Bianchi; Pier Federico Gherardini; Manuela Helmer-Citterich; Gabriele Ausiello
Journal:  BMC Bioinformatics       Date:  2012-03-28       Impact factor: 3.169

9.  Improving protein-ligand binding site prediction accuracy by classification of inner pocket points using local features.

Authors:  Radoslav Krivák; David Hoksza
Journal:  J Cheminform       Date:  2015-04-01       Impact factor: 5.514

Review 10.  Structure-based Methods for Computational Protein Functional Site Prediction.

Authors:  B Kc Dukka
Journal:  Comput Struct Biotechnol J       Date:  2013-11-11       Impact factor: 7.271

View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.