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BiPPred: Combined sequence- and structure-based prediction of peptide binding to the Hsp70 chaperone BiP.
Schneider, Markus; Rosam, Mathias; Glaser, Manuel; Patronov, Atanas; Shah, Harpreet; Back, Katrin Christiane; Daake, Marina Angelika; Buchner, Johannes; Antes, Iris.
Affiliation
  • Schneider M; Department Biowissenschaftliche Grundlagen, Technische Universität München, Freising, Germany.
  • Rosam M; Department Chemie, Technische Universität München, Garching, Germany.
  • Glaser M; Department Biowissenschaftliche Grundlagen, Technische Universität München, Freising, Germany.
  • Patronov A; Department Biowissenschaftliche Grundlagen, Technische Universität München, Freising, Germany.
  • Shah H; Center for Integrated Protein Science, Departments of Bioscience, Technische Universität München, Munich, Germany.
  • Back KC; Department Biowissenschaftliche Grundlagen, Technische Universität München, Freising, Germany.
  • Daake MA; Department Chemie, Technische Universität München, Garching, Germany.
  • Buchner J; Department Chemie, Technische Universität München, Garching, Germany.
  • Antes I; Department Chemie, Technische Universität München, Garching, Germany.
Proteins ; 84(10): 1390-407, 2016 10.
Article in En | MEDLINE | ID: mdl-27287023
ABSTRACT
Substrate binding to Hsp70 chaperones is involved in many biological processes, and the identification of potential substrates is important for a comprehensive understanding of these events. We present a multi-scale pipeline for an accurate, yet efficient prediction of peptides binding to the Hsp70 chaperone BiP by combining sequence-based prediction with molecular docking and MMPBSA calculations. First, we measured the binding of 15mer peptides from known substrate proteins of BiP by peptide array (PA) experiments and performed an accuracy assessment of the PA data by fluorescence anisotropy studies. Several sequence-based prediction models were fitted using this and other peptide binding data. A structure-based position-specific scoring matrix (SB-PSSM) derived solely from structural modeling data forms the core of all models. The matrix elements are based on a combination of binding energy estimations, molecular dynamics simulations, and analysis of the BiP binding site, which led to new insights into the peptide binding specificities of the chaperone. Using this SB-PSSM, peptide binders could be predicted with high selectivity even without training of the model on experimental data. Additional training further increased the prediction accuracies. Subsequent molecular docking (DynaDock) and MMGBSA/MMPBSA-based binding affinity estimations for predicted binders allowed the identification of the correct binding mode of the peptides as well as the calculation of nearly quantitative binding affinities. The general concept behind the developed multi-scale pipeline can readily be applied to other protein-peptide complexes with linearly bound peptides, for which sufficient experimental binding data for the training of classical sequence-based prediction models is not available. Proteins 2016; 841390-1407. © 2016 Wiley Periodicals, Inc.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Peptides / Carrier Proteins / Vascular Endothelial Growth Factor A / Immunoglobulin Light Chains, Surrogate / Heat-Shock Proteins Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Proteins Journal subject: BIOQUIMICA Year: 2016 Document type: Article Affiliation country: Germany

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Peptides / Carrier Proteins / Vascular Endothelial Growth Factor A / Immunoglobulin Light Chains, Surrogate / Heat-Shock Proteins Type of study: Prognostic_studies / Risk_factors_studies Limits: Humans Language: En Journal: Proteins Journal subject: BIOQUIMICA Year: 2016 Document type: Article Affiliation country: Germany