TAILIEUCHUNG - Báo cáo Y học: Prediction of protein–protein interaction sites in heterocomplexes with neural networks

In this paper we address the problem of extracting features relevant for predicting protein±protein interaction sites from the three-dimensional structures of protein complexes. Our approach is based on information about evolutionary con-servation and surface disposition. We implement a neural network based system, which uses a cross validation proce-dure and allows the correct detection of 73% of the residues involved in protein interactions in a selected database comprising 226 heterodimers. | Eur. J. Biochem. 269 1356-1361 2002 FEBS 2002 Prediction of protein-protein interaction sites in heterocomplexes with neural networks Piero Fariselli1 Florencio Pazos2 Alfonso Valencia2 and Rita Casadio1 1CIRB and Department of Biology University of Bologna via Irnerio Bologna Italy 2Protein Design Group CNB-CSIC Cantoblanco Madrid Spain In this paper we address the problem of extracting features relevant for predicting protein-protein interaction sites from the three-dimensional structures of protein complexes. Our approach is based on information about evolutionary conservation and surface disposition. We implement a neural network based system which uses a cross validation procedure and allows the correct detection of 73 of the residues involved in protein interactions in a selected database comprising 226 heterodimers. Our analysis confirms that the chemico-physical properties of interacting surfaces are difficult to distinguish from those of the whole protein surface. However neural networks trained with a reduced representation of the interacting patch and sequence profile are sufficient to generalize over the different features of the contact patches and to predict whether a residue in the protein surface is or is not in contact. By using a blind test we report the prediction of the surface interacting sites of three structural components of the Dnak molecular chaperone system and fnd close agreement with previously published experimental results. We propose that the predictor can signifcantly complement results from structural and functional proteomics. Keywords protein-protein interaction protein surface neural network evolutionary information. In the post-genome era a shift of emphasis is taking place towards making genomics functional 1 2 . In this respect the systematic study of protein-protein interaction through the isolation of protein complexes is under way and cellmap proteomics adds a route to effciently study the genome at the protein level 3-6 .

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