A statistical model of electrostatic isopotential variation in serine protease binding cavities

This paper presents EPAC (Electrostatic isoPotential Analytical Comparative model), the first statistical model for evaluating the geometric similarity of electrostatic fields. Beginning with aligned binding cavities, EPAC measures similarity based on the overlapping volume of isopotentials inside ligand binding cavities. We tested the accuracy of our model on two subfamilies of the serine protease superfamily, demonstrating that EPAC effectively identifies binding sites that prefer differently charged substrates. For example, EPAC identified subtle electrostatic variations in proteins that might be expected to be more similar, such as the difference between typical trypsins and a trypsin with a phosphorylated tyrosine nearby the binding site. These results point to applications in the unsupervised comparison of many binding sites from a purely electrostatic perspective, in the search of subtle electrostatic variations that could influence binding specificity.

[1]  W R Taylor,et al.  SSAP: sequential structure alignment program for protein structure comparison. , 1996, Methods in enzymology.

[2]  B Honig,et al.  An integrated approach to the analysis and modeling of protein sequences and structures. I. Protein structural alignment and a quantitative measure for protein structural distance. , 2000, Journal of molecular biology.

[3]  T. N. Bhat,et al.  The Protein Data Bank , 2000, Nucleic Acids Res..

[4]  Olivier Lichtarge,et al.  Cavity-aware motifs reduce false positives in protein function prediction. , 2006, Computational systems bioinformatics. Computational Systems Bioinformatics Conference.

[5]  Lei Xie,et al.  Detecting evolutionary relationships across existing fold space, using sequence order-independent profile–profile alignments , 2008, Proceedings of the National Academy of Sciences.

[6]  Jie Liang,et al.  Predicting Protein Function and Binding Profile via Matching of Local Evolutionary and Geometric Surface Patterns , 2009 .

[7]  Kengo Kinoshita,et al.  eF-seek: prediction of the functional sites of proteins by searching for similar electrostatic potential and molecular surface shape , 2007, Nucleic Acids Res..

[8]  Soutir Bandyopadhyay,et al.  Modeling regionalized volumetric differences in protein-ligand binding cavities , 2012, Proteome Science.

[9]  L Szilágyi,et al.  Electrostatic complementarity within the substrate-binding pocket of trypsin. , 1988, Proceedings of the National Academy of Sciences of the United States of America.

[10]  B.Y. Chen,et al.  A statistical model to correct systematic bias introduced by algorithmic thresholds in protein structural comparison algorithms , 2008, 2008 IEEE International Conference on Bioinformatics and Biomeidcine Workshops.

[11]  Lydia E. Kavraki,et al.  Geometric Sieving: Automated Distributed Optimization of 3D Motifs for Protein Function Prediction , 2006, RECOMB.

[12]  Brian Yuan Chen,et al.  A statistical model of overlapping volume in ligand binding cavities , 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW).

[13]  K. Kinoshita,et al.  Identification of protein biochemical functions by similarity search using the molecular surface database eF‐site , 2003, Protein science : a publication of the Protein Society.

[14]  Barry Honig,et al.  VASP: A Volumetric Analysis of Surface Properties Yields Insights into Protein-Ligand Binding Specificity , 2010, PLoS Comput. Biol..

[15]  Andrzej Joachimiak,et al.  Protein Functional Surfaces: Global Shape Matching and Local Spatial Alignments of Ligand Binding Sites , 2008, BMC Structural Biology.

[16]  Lenore Cowen,et al.  Matt: Local Flexibility Aids Protein Multiple Structure Alignment , 2008, PLoS Comput. Biol..

[17]  J F Gibrat,et al.  Surprising similarities in structure comparison. , 1996, Current opinion in structural biology.

[18]  C Sander,et al.  Mapping the Protein Universe , 1996, Science.

[19]  Robert B Russell,et al.  A model for statistical significance of local similarities in structure. , 2003, Journal of molecular biology.

[20]  K Morihara,et al.  Comparison of the specificities of various neutral proteinases from microorganisms. , 1968, Archives of biochemistry and biophysics.

[21]  William R. Taylor,et al.  Flexible Secondary Structure Based Protein Structure Comparison Applied to the Detection of Circular Permutation , 2006, J. Comput. Biol..

[22]  Barry Honig,et al.  Extending the Applicability of the Nonlinear Poisson−Boltzmann Equation: Multiple Dielectric Constants and Multivalent Ions† , 2001 .

[23]  M. G. Stone,et al.  Face Traverses and a Volume Algorithm for Polyhedra , 1991, New Results and New Trends in Computer Science.

[24]  Brian Yuan Chen,et al.  VASP-S: A Volumetric Analysis and Statistical Model for Predicting Steric Influences on Protein-Ligand Binding Specificity , 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine.

[25]  Lydia E. Kavraki,et al.  The MASH Pipeline for Protein Function Prediction and an Algorithm for the Geometric Refinement of 3D Motifs , 2007, J. Comput. Biol..

[26]  K Morihara,et al.  Comparison of the specificities of various serine proteinases from microorganisms. , 1969, Archives of biochemistry and biophysics.

[27]  K. Kinoshita,et al.  Identification of protein functions from a molecular surface database, eF-site , 2004, Journal of Structural and Functional Genomics.

[28]  Lydia E. Kavraki,et al.  Algorithms for Structural Comparison and Statistical Analysis of 3D Protein Motifs , 2004, Pacific Symposium on Biocomputing.

[29]  P. Willett,et al.  A graph-theoretic approach to the identification of three-dimensional patterns of amino acid side-chains in protein structures. , 1994, Journal of molecular biology.

[30]  Lydia E. Kavraki,et al.  Cavity Scaling: Automated Refinement of Cavity-Aware motifs in protein Function Prediction , 2007, J. Bioinform. Comput. Biol..

[31]  Brian Yuan Chen,et al.  A Regionalizable Statistical Model of Intersecting Regions in protein-ligand binding Cavities , 2012, J. Bioinform. Comput. Biol..

[32]  Brian Y. Chen,et al.  VASP-E: Specificity Annotation with a Volumetric Analysis of Electrostatic Isopotentials , 2014, PLoS Comput. Biol..

[33]  Hermann A. Maurer,et al.  New Results and New Trends in Computer Science , 1991, Lecture Notes in Computer Science.

[34]  Philip E. Bourne,et al.  A robust and efficient algorithm for the shape description of protein structures and its application in predicting ligand binding sites , 2007, BMC Bioinformatics.

[35]  Jie Liang,et al.  Protein surface analysis for function annotation in high‐throughput structural genomics pipeline , 2005, Protein science : a publication of the Protein Society.

[36]  Vincent B. Chen,et al.  Correspondence e-mail: , 2000 .

[37]  Adam Godzik,et al.  FATCAT: a web server for flexible structure comparison and structure similarity searching , 2004, Nucleic Acids Res..