Unbiased Protein Interface Prediction Based on Ligand Diversity Quantification

Esmaielbeiki, R. and Nebel, J.C. (2012) Unbiased Protein Interface Prediction Based on Ligand Diversity Quantification. In: German Conference on Bioinformatics; 19-22 Sep 2012, Jena, Germany. (OASICS, no. Vol. 26) ISSN (print) 2190-6807 ISBN 9783939897446

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Abstract

Proteins interact with each other to perform essential functions in cells. Consequently, identification of their binding interfaces can provide key information for drug design. Here, we introduce Weighted Protein Interface Prediction (WePIP), an original framework which predicts protein interfaces from homologous complexes. WePIP takes advantage of a novel weighted score which is not only based on structural neighbours' information but, unlike current state-of-the-art methods, also takes into consideration the nature of their interaction partners. Experimental validation demonstrates that our weighted schema significantly improves prediction performance. In particular, we have established a major contribution to ligand diversity quantification. Moreover, application of our framework on a standard dataset shows WePIP performance compares favourably with other state of the art methods.

Item Type: Conference or Workshop Item (Paper)
Event Title: German Conference on Bioinformatics
Additional Information: This paper was published in: Esmaielbeiki, R and Nebel, J-C. (2012) Unbiased protein interface prediction based on ligand diversity quantification In Bocker, S; Hufsky, F; Scheubert, K; Schleicher, J and Schuster, S (eds), German conference on bioinformatics 2012. Dagstuhl Publishing, Saarbrucken, pp. 119-130.
Uncontrolled Keywords: Protein-protein interaction, protein interface prediction, homology modeling
Research Area: Computer science and informatics
Faculty, School or Research Centre: Faculty of Science, Engineering and Computing
Faculty of Science, Engineering and Computing > School of Computing and Information Systems
Depositing User: Automatic Import Agent
Date Deposited: 05 Feb 2015 17:40
Last Modified: 05 Feb 2015 17:40
URI: http://eprints.kingston.ac.uk/id/eprint/23649

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