SiMMap: a web server for inferring site-moiety map to recognize interaction preferences between protein pockets and compound moieties

The protein–ligand interacting mechanism is essential to biological processes and drug discovery. The SiMMap server statistically derives site-moiety map with several anchors, which describe the relationship between the moiety preferences and physico-chemical properties of the binding site, from the interaction profiles between query target protein and its docked (or co-crystallized) compounds. Each anchor includes three basic elements: a binding pocket with conserved interacting residues, the moiety composition of query compounds and pocket–moiety interaction type (electrostatic, hydrogen bonding or van der Waals). We provide initial validation of the site-moiety map on three targets, thymidine kinase, and estrogen receptors of antagonists and agonists. Experimental results show that an anchor is often a hot spot and the site-moiety map can help to assemble potential leads by optimal steric, hydrogen bonding and electronic moieties. When a compound highly agrees with anchors of site-moiety map, this compound often activates or inhibits the target protein. We believe that the site-moiety map is useful for drug discovery and understanding biological mechanisms. The SiMMap web server is available at http://simfam.life.nctu.edu.tw/.

[1]  J. M. Dow,et al.  The cAMP receptor-like protein CLP is a novel c-di-GMP receptor linking cell-cell signaling to virulence gene expression in Xanthomonas campestris. , 2010, Journal of molecular biology.

[2]  Steven J. M. Jones,et al.  A novel small-molecule inhibitor of the avian influenza H5N1 virus determined through computational screening against the neuraminidase. , 2009, Journal of medicinal chemistry.

[3]  H. Hsieh,et al.  Aurintricarboxylic acid inhibits influenza virus neuraminidase , 2008, Antiviral Research.

[4]  S. Mao,et al.  Rational Design for Crystallization of β-Lactoglobulin and Vitamin D3 Complex: Revealing a Secondary Binding Site† , 2008 .

[5]  Gisbert Schneider,et al.  Pseudoreceptor models in drug design: bridging ligand- and receptor-based virtual screening , 2008, Nature Reviews Drug Discovery.

[6]  Jinn-Moon Yang,et al.  Combinatorial Computational Approaches to Identify Tetracycline Derivatives as Flavivirus Inhibitors , 2007, PloS one.

[7]  P. Hajduk,et al.  A decade of fragment-based drug design: strategic advances and lessons learned , 2007, Nature reviews. Drug discovery.

[8]  B. Katzenellenbogen,et al.  Structure-guided optimization of estrogen receptor binding affinity and antagonist potency of pyrazolopyrimidines with basic side chains. , 2007, Journal of medicinal chemistry.

[9]  M. Botta,et al.  Pharmacophore based receptor modeling: the case of adenosine A3 receptor antagonists. An approach to the optimization of protein models. , 2006, Journal of medicinal chemistry.

[10]  D. Frank Hsu,et al.  Consensus Scoring Criteria for Improving Enrichment in Virtual Screening , 2005, J. Chem. Inf. Model..

[11]  Tsai-Wei Shen,et al.  A pharmacophore‐based evolutionary approach for screening selective estrogen receptor modulators , 2005, Proteins.

[12]  J. Bajorath,et al.  Docking and scoring in virtual screening for drug discovery: methods and applications , 2004, Nature Reviews Drug Discovery.

[13]  Jinn-Moon Yang,et al.  GEMDOCK: A generic evolutionary method for molecular docking , 2004, Proteins.

[14]  Ruben Abagyan,et al.  Discovery of diverse thyroid hormone receptor antagonists by high-throughput docking , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[15]  Alexander D. MacKerell,et al.  Consideration of Molecular Weight during Compound Selection in Virtual Target-Based Database Screening , 2003, J. Chem. Inf. Comput. Sci..

[16]  Paul D Lyne,et al.  Structure-based virtual screening: an overview. , 2002, Drug discovery today.

[17]  Brian K. Shoichet,et al.  Structure-Based Discovery of a Novel, Noncovalent Inhibitor of AmpC β-Lactamase , 2002 .

[18]  Andrzej M. Brzozowski,et al.  Interaction of Transcriptional Intermediary Factor 2 Nuclear Receptor Box Peptides with the Coactivator Binding Site of Estrogen Receptor α* , 2002, The Journal of Biological Chemistry.

[19]  Brian K Shoichet,et al.  Structure-based discovery of a novel, noncovalent inhibitor of AmpC beta-lactamase. , 2002, Structure.

[20]  M. Maeda.  The conserved residues of the ligand-binding domains of steroid receptors are located in the core of the molecules. , 2001, Journal of molecular graphics & modelling.

[21]  Todd J. A. Ewing,et al.  DOCK 4.0: Search strategies for automated molecular docking of flexible molecule databases , 2001, J. Comput. Aided Mol. Des..

[22]  D. Rognan,et al.  Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. , 2000, Journal of medicinal chemistry.

[23]  C. Wurth,et al.  Substrate Diversity of Herpes Simplex Virus Thymidine Kinase , 1999, The Journal of Biological Chemistry.

[24]  Thomas Lengauer,et al.  Evaluation of the FLEXX incremental construction algorithm for protein–ligand docking , 1999, Proteins.

[25]  David A. Agard,et al.  The Structural Basis of Estrogen Receptor/Coactivator Recognition and the Antagonism of This Interaction by Tamoxifen , 1998, Cell.

[26]  J. Champness,et al.  Herpesviral thymidine kinases: laxity and resistance by design. , 1998, The Journal of general virology.

[27]  Frank Wien,et al.  Exploring the active site of herpes simplex virus type‐1 thymidine kinase by X‐ray crystallography of complexes with aciclovir and other ligands , 1998, Proteins.

[28]  G. Folkers,et al.  Drug resistance of herpes simplex virus type 1--structural considerations at the molecular level of the thymidine kinase. , 1998, European journal of biochemistry.

[29]  Gerd Folkers,et al.  The structures of thymidine kinase from Herpes simplex virus type 1 in complex with substrates and a substrate analogue , 1997, Protein science : a publication of the Protein Society.

[30]  P Willett,et al.  Development and validation of a genetic algorithm for flexible docking. , 1997, Journal of molecular biology.