Prediction of Protein-Protein Interaction Sites Using Only Sequence Information and Using Both Sequence and Structural Information

Kakuta Masanori, Nakamura Shugo, Shimizu Kentaro

doi:10.2197/ipsjdc.4.217

Prediction of Protein-Protein Interaction Sites Using Only Sequence Information and Using Both Sequence and Structural Information

DOI Web Site 参考文献21件オープンアクセス

Kakuta Masanori

Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo
Nakamura Shugo

Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo
Shimizu Kentaro

Department of Biotechnology, Graduate School of Agricultural and Life Sciences, The University of Tokyo

書誌事項

公開日: 2008

DOI

10.2197/ipsjdc.4.217

公開者: 一般社団法人情報処理学会

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説明

Protein-protein interactions play an important role in a number of biological activities. We developed two methods of predictingprotein-protein interaction site residues. One method uses only sequence information and the other method uses both sequence and structural information. We used support vector machine (SVM) with a position specific scoring matrix (PSSM) as sequence information and accessible surface area(ASA) of polar and non-polar atoms as structural information. SVM is used in two stages. In the first stage, an interaction residue is predicted by taking PSSMs of sequentially neighboring residues or taking PSSMs and ASAs of spatially neighboring residues as features. The second stage acts as a filter to refine the prediction results. The recall and precision of the predictor using both sequence and structural information are 73.6% and 50.5%, respectively. We found that using PSSM instead of frequency of amino acid appearance was the main factor of improvement of our methods.