A consensus approach for identification of protein-protein interaction sites in Homo sapiens

Brijesh K. Sriwastava , Subhadip Basu , Ujjwal Maulik , Dariusz Plewczyński

Abstract

The physico-chemical properties of interaction interfaces have a crucial role in characterization of protein-protein interactions. Given the unbound structure of a protein and the fact that it forms a complex with another known protein, the objective of this work is to identify the residues that are involved in the interaction. We attempt to predict interaction sites in protein complexes using local composition of amino acids together with their physico-chemical characteristics. The local sequence segments are dissected from the protein sequences using sliding window of 21 amino acids. The list of LSSs is passed to the support vector machine (SVM) predictor, which identifies interacting residue pairs considering their inter-atom distances. Three different SVM predictors are designed that generate area under ROC curve (AUC), Recall and Precision optimized results. Finally a 3-star consensus strategy is designed to analyze 33 hetero-complexes of the Homo sapiens organism. The consensus approach generates the AUC score of 0.7376, which is superior to the individual SVM classification results. © Springer-Verlag 2013.

Author Brijesh K. Sriwastava - [Government College of Engineering and Leather Technology, Govt. of West Bengal]
Brijesh K. Sriwastava,,
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, Subhadip Basu - [Jadavpur University]
Subhadip Basu,,
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, Ujjwal Maulik - [Jadavpur University]
Ujjwal Maulik,,
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, Dariusz Plewczyński (FMIS / DIPS)
Dariusz Plewczyński,,
- Department of Information Processing Systems
Pages674-679
Book Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2013, ISBN 9783642450617, 674-679 p.
DOIDOI:10.1007/978-3-642-45062-4_95
Languageen angielski
Score (nominal)0
ScoreMinisterial score = 0.0, 04-06-2020, MonographChapterAuthor
Publication indicators Scopus Citations = 0
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