Large-scale binding ligand prediction by improved patch-based method Patch-Surfer2.0

MOTIVATION Ligand binding is a key aspect of the function of many proteins. Thus, binding ligand prediction provides important insight in understanding the biological function of proteins. Binding ligand prediction is also useful for drug design and examining potential drug side effects. RESULTS We present a computational method named Patch-Surfer2.0, which predicts binding ligands for a protein pocket. By representing and comparing pockets at the level of small local surface patches that characterize physicochemical properties of the local regions, the method can identify binding pockets of the same ligand even if they do not share globally similar shapes. Properties of local patches are represented by an efficient mathematical representation, 3D Zernike Descriptor. Patch-Surfer2.0 has significant technical improvements over our previous prototype, which includes a new feature that captures approximate patch position with a geodesic distance histogram. Moreover, we constructed a large comprehensive database of ligand binding pockets that will be searched against by a query. The benchmark shows better performance of Patch-Surfer2.0 over existing methods. AVAILABILITY AND IMPLEMENTATION http://kiharalab.org/patchsurfer2.0/ CONTACT: dkihara@purdue.edu SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

[1]  Bin Li,et al.  Characterization of local geometry of protein surfaces with the visibility criterion , 2008, Proteins.

[2]  Daisuke Kihara,et al.  Molecular surface representation using 3D Zernike descriptors for protein shape comparison and docking. , 2011, Current protein & peptide science.

[3]  Mona Singh,et al.  Predicting Protein Ligand Binding Sites by Combining Evolutionary Sequence Conservation and 3D Structure , 2009, PLoS Comput. Biol..

[4]  J. Skolnick,et al.  TM-align: a protein structure alignment algorithm based on the TM-score , 2005, Nucleic acids research.

[5]  Ming-Jing Hwang,et al.  Ligand-binding site prediction using ligand-interacting and binding site-enriched protein triangles , 2012, Bioinform..

[6]  H. Edelsbrunner,et al.  Anatomy of protein pockets and cavities: Measurement of binding site geometry and implications for ligand design , 1998, Protein science : a publication of the Protein Society.

[7]  K. Denessiouk,et al.  Adenine recognition: A motif present in ATP‐, CoA‐, NAD‐, NADP‐, and FAD‐dependent proteins , 2001, Proteins.

[8]  D. Kihara,et al.  Real‐time ligand binding pocket database search using local surface descriptors , 2010, Proteins.

[9]  Nikolaos Canterakis,et al.  3D Zernike Moments and Zernike Affine Invariants for 3D Image Analysis and Recognition , 1999 .

[10]  T. Kawabata.  Detection of multiscale pockets on protein surfaces using mathematical morphology , 2010, Proteins.

[11]  Lukasz Kurgan,et al.  Finding protein targets for small biologically relevant ligands across fold space using inverse ligand binding predictions. , 2012, Structure.

[12]  Ruth Nussinov,et al.  The Multiple Common Point Set Problem and Its Application to Molecule Binding Pattern Detection , 2006, J. Comput. Biol..

[13]  Janet M. Thornton,et al.  The Catalytic Site Atlas: a resource of catalytic sites and residues identified in enzymes using structural data , 2004, Nucleic Acids Res..

[14]  K. Kinoshita,et al.  Identification of the ligand binding sites on the molecular surface of proteins , 2005, Protein science : a publication of the Protein Society.

[15]  J. Thornton,et al.  Shape variation in protein binding pockets and their ligands. , 2007, Journal of molecular biology.

[16]  C. Orengo,et al.  One fold with many functions: the evolutionary relationships between TIM barrel families based on their sequences, structures and functions. , 2002, Journal of molecular biology.

[17]  Izhar Wallach,et al.  The protein-small-molecule database, a non-redundant structural resource for the analysis of protein-ligand binding , 2009, Bioinform..

[18]  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.

[19]  Jean-Philippe Vert,et al.  A new protein binding pocket similarity measure based on comparison of clouds of atoms in 3D: application to ligand prediction , 2010, BMC Bioinformatics.

[20]  J. Thornton,et al.  Protein recognition of adenylate: an example of a fuzzy recognition template. , 1996, Journal of molecular biology.

[21]  D. Kihara,et al.  Detecting local ligand‐binding site similarity in nonhomologous proteins by surface patch comparison , 2012, Proteins.

[22]  M. Kanehisa,et al.  Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways. , 2003, Journal of the American Chemical Society.

[23]  Chaok Seok,et al.  GalaxySite: ligand-binding-site prediction by using molecular docking , 2014, Nucleic Acids Res..

[24]  Yang Zhang,et al.  Large-scale assessment of the utility of low-resolution protein structures for biochemical function assignment , 2004, Bioinform..

[25]  Sourav Das,et al.  Rapid Comparison of Protein Binding Site Surfaces with Property Encoded Shape Distributions , 2009, J. Chem. Inf. Model..

[26]  Michal Brylinski,et al.  FINDSITELHM: A Threading-Based Approach to Ligand Homology Modeling , 2009, PLoS Comput. Biol..

[27]  Daisuke Kihara,et al.  Binding Ligand Prediction for Proteins Using Partial Matching of Local Surface Patches , 2010, International journal of molecular sciences.

[28]  N. Gold,et al.  Fold independent structural comparisons of protein-ligand binding sites for exploring functional relationships. , 2006, Journal of molecular biology.

[29]  Jeffrey Skolnick,et al.  APoc: large-scale identification of similar protein pockets , 2013, Bioinform..

[30]  D. Kihara,et al.  Energetics-based discovery of protein-ligand interactions on a proteomic scale. , 2011, Journal of molecular biology.

[31]  Yang Zhang,et al.  Protein-ligand binding site recognition using complementary binding-specific substructure comparison and sequence profile alignment , 2013, Bioinform..

[32]  Janet M. Thornton,et al.  Real spherical harmonic expansion coefficients as 3D shape descriptors for protein binding pocket and ligand comparisons , 2005, Bioinform..