Identifying and Characterizing Binding Sites and Assessing Druggability

Identification and characterization of binding sites is key in the process of structure-based drug design. In some cases there may not be any information about the binding site for a target of interest. In other cases, a putative binding site has been identified by computational or experimental means, but the druggability of the target is not known. Even when a site for a given target is known, it may be desirable to find additional sites whose targeting could produce a desired biological response. A new program, called SiteMap, is presented for identifying and analyzing binding sites and for predicting target druggability. In a large-scale validation, SiteMap correctly identifies the known binding site as the top-ranked site in 86% of the cases, with best results (>98%) coming for sites that bind ligands with subnanomolar affinity. In addition, a modified version of the score employed for binding-site identification allows SiteMap to accurately classify the druggability of proteins as measured by their ability to bind passively absorbed small molecules tightly. In characterizing binding sites, SiteMap provides quantitative and graphical information that can help guide efforts to critically assess virtual hits in a lead-discovery application or to modify ligand structure to enhance potency or improve physical properties in a lead-optimization context.

[1]  Tom Halgren,et al.  New Method for Fast and Accurate Binding‐site Identification and Analysis , 2007, Chemical biology & drug design.

[2]  Renxiao Wang,et al.  The PDBbind database: methodologies and updates. , 2005, Journal of medicinal chemistry.

[3]  B. Honig,et al.  On the nature of cavities on protein surfaces: Application to the identification of drug‐binding sites , 2006, Proteins.

[4]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. , 2001, Advanced drug delivery reviews.

[5]  Matthew P. Repasky,et al.  Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. , 2006, Journal of medicinal chemistry.

[6]  Hege S. Beard,et al.  Glide: a new approach for rapid, accurate docking and scoring. 2. Enrichment factors in database screening. , 2004, Journal of medicinal chemistry.

[7]  R J Lynch,et al.  Design and synthesis of P2-P1'-linked macrocyclic human renin inhibitors. , 1991, Journal of medicinal chemistry.

[8]  Sandor Vajda,et al.  Improved mapping of protein binding sites , 2003, J. Comput. Aided Mol. Des..

[9]  Bruce Tidor,et al.  A computational method for the analysis and prediction of protein:phosphopeptide‐binding sites , 2005, Protein science : a publication of the Protein Society.

[10]  Jill E. Gready,et al.  Simple method for locating possible ligand binding sites on protein surfaces , 1999, J. Comput. Chem..

[11]  Pieter F. W. Stouten,et al.  Fast prediction and visualization of protein binding pockets with PASS , 2000, J. Comput. Aided Mol. Des..

[12]  Angela Smallwood,et al.  Discovery of 1-(4-methoxyphenyl)-7-oxo-6-(4-(2-oxopiperidin-1-yl)phenyl)-4,5,6,7-tetrahydro-1H-pyrazolo[3,4-c]pyridine-3-carboxamide (apixaban, BMS-562247), a highly potent, selective, efficacious, and orally bioavailable inhibitor of blood coagulation factor Xa. , 2007, Journal of medicinal chemistry.

[13]  C. Frömmel,et al.  The automatic search for ligand binding sites in proteins of known three-dimensional structure using only geometric criteria. , 1996, Journal of molecular biology.

[14]  Alan C. Cheng,et al.  Structure-Based Identification of Small Molecule Binding Sites Using a Free Energy Model , 2006, J. Chem. Inf. Model..

[15]  R. Abagyan,et al.  Pocketome via Comprehensive Identification and Classification of Ligand Binding Envelopes* , 2005, Molecular & Cellular Proteomics.

[16]  Ajay N. Jain,et al.  Automatic identification and representation of protein binding sites for molecular docking , 1997, Protein science : a publication of the Protein Society.

[17]  M Hendlich,et al.  LIGSITE: automatic and efficient detection of potential small molecule-binding sites in proteins. , 1997, Journal of molecular graphics & modelling.

[18]  Matthew P. Repasky,et al.  Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. , 2004, Journal of medicinal chemistry.

[19]  Sandor Vajda,et al.  Computational mapping identifies the binding sites of organic solvents on proteins , 2002, Proceedings of the National Academy of Sciences of the United States of America.

[20]  M. Schroeder,et al.  LIGSITEcsc: predicting ligand binding sites using the Connolly surface and degree of conservation , 2006, BMC Structural Biology.

[21]  G. Superti-Furga,et al.  Rediscovering the sweet spot in drug discovery. , 2003, Drug discovery today.

[22]  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.

[23]  P. Willett,et al.  SuperStar: improved knowledge-based interaction fields for protein binding sites. , 2001, Journal of molecular biology.

[24]  P. Goodford A computational procedure for determining energetically favorable binding sites on biologically important macromolecules. , 1985, Journal of medicinal chemistry.

[25]  Jie Liang,et al.  CASTp: Computed Atlas of Surface Topography of proteins , 2003, Nucleic Acids Res..

[26]  Daniel R McMasters,et al.  Metabolism-directed optimization of 3-aminopyrazinone acetamide thrombin inhibitors. Development of an orally bioavailable series containing P1 and P3 pyridines. , 2003, Journal of medicinal chemistry.

[27]  R. Laskowski SURFNET: a program for visualizing molecular surfaces, cavities, and intermolecular interactions. , 1995, Journal of molecular graphics.

[28]  Tudor I. Oprea,et al.  Is There a Difference Between Leads and Drugs? A Historical Perspective. , 2001 .

[29]  A. Hopkins,et al.  The druggable genome , 2002, Nature Reviews Drug Discovery.

[30]  D. Levitt,et al.  POCKET: a computer graphics method for identifying and displaying protein cavities and their surrounding amino acids. , 1992, Journal of molecular graphics.

[31]  Gernot Kieseritzky,et al.  Optimizing pKA computation in proteins with pH adapted conformations , 2008, Proteins.

[32]  Daniel R. Caffrey,et al.  Structure-based maximal affinity model predicts small-molecule druggability , 2007, Nature Biotechnology.

[33]  R. Zamboni,et al.  Synthesis of a novel peptidic photoaffinity probe for the PTP-1B enzyme. , 2004, Bioorganic & medicinal chemistry letters.

[34]  Thomas Lampe,et al.  Discovery of the novel antithrombotic agent 5-chloro-N-({(5S)-2-oxo-3- [4-(3-oxomorpholin-4-yl)phenyl]-1,3-oxazolidin-5-yl}methyl)thiophene- 2-carboxamide (BAY 59-7939): an oral, direct factor Xa inhibitor. , 2005, Journal of medicinal chemistry.