Specificity and affinity quantification of protein-protein interactions

MOTIVATION Most biological processes are mediated by the protein-protein interactions. Determination of the protein-protein structures and insight into their interactions are vital to understand the mechanisms of protein functions. Currently, compared with the isolated protein structures, only a small fraction of protein-protein structures are experimentally solved. Therefore, the computational docking methods play an increasing role in predicting the structures and interactions of protein-protein complexes. The scoring function of protein-protein interactions is the key responsible for the accuracy of the computational docking. Previous scoring functions were mostly developed by optimizing the binding affinity which determines the stability of the protein-protein complex, but they are often lack of the consideration of specificity which determines the discrimination of native protein-protein complex against competitive ones. RESULTS We developed a scoring function (named as SPA-PP, specificity and affinity of the protein-protein interactions) by incorporating both the specificity and affinity into the optimization strategy. The testing results and comparisons with other scoring functions show that SPA-PP performs remarkably on both predictions of binding pose and binding affinity. Thus, SPA-PP is a promising quantification of protein-protein interactions, which can be implemented into the protein docking tools and applied for the predictions of protein-protein structure and affinity. AVAILABILITY The algorithm is implemented in C language, and the code can be downloaded from http://dl.dropbox.com/u/1865642/Optimization.cpp.

[1]  J. Janin,et al.  Principles of protein-protein recognition from structure to thermodynamics. , 1995, Biochimie.

[2]  Z. Weng,et al.  A structure‐based benchmark for protein–protein binding affinity , 2011, Protein science : a publication of the Protein Society.

[3]  T. Earnest,et al.  From words to literature in structural proteomics , 2003, Nature.

[4]  J. Onuchic,et al.  Funnels, pathways, and the energy landscape of protein folding: A synthesis , 1994, Proteins.

[5]  Dominique Douguet,et al.  DOCKGROUND resource for studying protein-protein interfaces , 2006, Bioinform..

[6]  Eugene I Shakhnovich,et al.  Native atom types for knowledge-based potentials: application to binding energy prediction. , 2004, Journal of medicinal chemistry.

[7]  Brian D. Weitzner,et al.  Benchmarking and Analysis of Protein Docking Performance in Rosetta v3.2 , 2011, PloS one.

[8]  J. Janin,et al.  Quantifying biological specificity: the statistical mechanics of molecular recognition. , 1996, Proteins.

[9]  Peter G Wolynes,et al.  Protein topology determines binding mechanism. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[10]  Hongyi Zhou,et al.  A physical reference state unifies the structure‐derived potential of mean force for protein folding and binding , 2004, Proteins.

[11]  Tim J. P. Hubbard,et al.  Data growth and its impact on the SCOP database: new developments , 2007, Nucleic Acids Res..

[12]  Xiaoqin Zou,et al.  An iterative knowledge‐based scoring function for protein–protein recognition , 2008, Proteins.

[13]  Gevorg Grigoryan,et al.  Design of protein-interaction specificity affords selective bZIP-binding peptides , 2009, Nature.

[14]  Martin Zacharias,et al.  Accounting for conformational changes during protein-protein docking. , 2010, Current opinion in structural biology.

[15]  Fenglou Mao,et al.  Potential of mean force for protein–protein interaction studies , 2002, Proteins.

[16]  W A Koppensteiner,et al.  Knowledge-based potentials--back to the roots. , 1998, Biochemistry. Biokhimiia.

[17]  D. Baker,et al.  Computational Design of Self-Assembling Protein Nanomaterials with Atomic Level Accuracy , 2012, Science.

[18]  S. Wodak,et al.  Docking and scoring protein complexes: CAPRI 3rd Edition , 2007, Proteins.

[19]  R. Nussinov,et al.  Folding funnels, binding funnels, and protein function , 1999, Protein science : a publication of the Protein Society.

[20]  Frédéric Cazals,et al.  Characterizing the morphology of protein binding patches , 2012, Proteins.

[21]  Wolfgang Baumeister,et al.  The future is hybrid. , 2008, Journal of structural biology.

[22]  Zhiqiang Yan,et al.  Specificity quantification of biomolecular recognition and its implication for drug discovery , 2012, Scientific Reports.

[23]  Y. Martin,et al.  A general and fast scoring function for protein-ligand interactions: a simplified potential approach. , 1999, Journal of medicinal chemistry.

[24]  Iain H. Moal,et al.  Protein-protein binding affinity prediction on a diverse set of structures , 2011, Bioinform..

[25]  S. Jones,et al.  Principles of protein-protein interactions. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[26]  Philip M. Kim,et al.  Relating Three-Dimensional Structures to Protein Networks Provides Evolutionary Insights , 2006, Science.

[27]  Baldomero Oliva,et al.  How different from random are docking predictions when ranked by scoring functions? , 2010, Proteins.

[28]  Jeffrey J. Gray,et al.  Protein-protein docking with simultaneous optimization of rigid-body displacement and side-chain conformations. , 2003, Journal of molecular biology.

[29]  Giorgio Palù,et al.  Disruption of protein–protein interactions: Towards new targets for chemotherapy , 2005, Journal of cellular physiology.

[30]  Alexandre M J J Bonvin,et al.  Are scoring functions in protein-protein docking ready to predict interactomes? Clues from a novel binding affinity benchmark. , 2010, Journal of proteome research.

[31]  Ruth Nussinov,et al.  Principles of docking: An overview of search algorithms and a guide to scoring functions , 2002, Proteins.

[32]  Xiliang Zheng,et al.  Quantifying intrinsic specificity: a potential complement to affinity in drug screening. , 2007, Physical review letters.

[33]  P. Wolynes,et al.  Optimal protein-folding codes from spin-glass theory. , 1992, Proceedings of the National Academy of Sciences of the United States of America.

[34]  K. Dill,et al.  An iterative method for extracting energy-like quantities from protein structures. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[35]  Pedro Alexandrino Fernandes,et al.  Protein–protein docking dealing with the unknown , 2009, J. Comput. Chem..

[36]  O. Schueler‐Furman,et al.  Progress in Modeling of Protein Structures and Interactions , 2005, Science.

[37]  P. Harbury,et al.  Automated design of specificity in molecular recognition , 2003, Nature Structural Biology.

[38]  D. Baker,et al.  Computational redesign of protein-protein interaction specificity , 2004, Nature Structural &Molecular Biology.

[39]  Joël Janin,et al.  Welcome to CAPRI: A Critical Assessment of PRedicted Interactions , 2002 .

[40]  Egon L. Willighagen,et al.  The Blue Obelisk—Interoperability in Chemical Informatics , 2006, J. Chem. Inf. Model..

[41]  Song Liu,et al.  A knowledge-based energy function for protein-ligand, protein-protein, and protein-DNA complexes. , 2005, Journal of medicinal chemistry.

[42]  Dominique Douguet,et al.  DOCKGROUND system of databases for protein recognition studies: Unbound structures for docking , 2007, Proteins.

[43]  Marc F Lensink,et al.  Docking and scoring protein interactions: CAPRI 2009 , 2010, Proteins.

[44]  Zhiping Weng,et al.  Protein–protein docking benchmark version 4.0 , 2010, Proteins.

[45]  Eugene I Shakhnovich,et al.  Structural mining: self-consistent design on flexible protein-peptide docking and transferable binding affinity potential. , 2004, Journal of the American Chemical Society.

[46]  K. Dill,et al.  Statistical potentials extracted from protein structures: how accurate are they? , 1996, Journal of molecular biology.

[47]  Zhirong Sun,et al.  Quantitative prediction of protein–protein binding affinity with a potential of mean force considering volume correction , 2009, Protein science : a publication of the Protein Society.

[48]  Gennady M Verkhivker,et al.  Unraveling principles of lead discovery: from unfrustrated energy landscapes to novel molecular anchors. , 1996, Proceedings of the National Academy of Sciences of the United States of America.

[49]  Stefano Alcaro,et al.  GBPM: GRID-based pharmacophore model: concept and application studies to protein-protein recognition , 2006, Bioinform..

[50]  Helen M Berman,et al.  Large macromolecular complexes in the Protein Data Bank: a status report. , 2005, Structure.

[51]  M. Baker,et al.  Structural biology of cellular machines. , 2006, Trends in cell biology.

[52]  Julia M. Shifman,et al.  Exploring the origins of binding specificity through the computational redesign of calmodulin , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[53]  Gennady M Verkhivker,et al.  Energy landscape theory, funnels, specificity, and optimal criterion of biomolecular binding. , 2003, Physical review letters.

[54]  M. Sippl Calculation of conformational ensembles from potentials of mean force. An approach to the knowledge-based prediction of local structures in globular proteins. , 1990, Journal of molecular biology.

[55]  T. Baker,et al.  Specificity versus stability in computational protein design. , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[56]  K A Dill,et al.  Ligand binding to proteins: The binding landscape model , 1997, Protein science : a publication of the Protein Society.

[57]  R. Cramer,et al.  Validation of the general purpose tripos 5.2 force field , 1989 .