Using Protein Homology Models for Structure-Based Studies: Approaches to Model Refinement

Homology modeling is a computational methodology to assign a 3-D structure to a target protein when experimental data are not available. The methodology uses another protein with a known structure that shares some sequence identity with the target as a template. The crudest approach is to thread the target protein backbone atoms over the backbone atoms of the template protein, but necessary refinement methods are needed to produce realistic models. In this mini-review anchored within the scope of drug design, we show the validity of using homology models of proteins in the discovery of binders for potential therapeutic targets. We also report several different approaches to homology model refinement, going from very simple to the most elaborate. Results show that refinement approaches are system dependent and that more elaborate methodologies do not always correlate with better performances from built homology models.

[1]  J. Åqvist,et al.  Computational prediction of structure, substrate binding mode, mechanism, and rate for a malaria protease with a novel type of active site. , 2004, Biochemistry.

[2]  Ceslovas Venclovas,et al.  Progress over the first decade of CASP experiments , 2005, Proteins.

[3]  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.

[4]  Richard D. Taylor,et al.  Improved protein–ligand docking using GOLD , 2003, Proteins.

[5]  Prashant V Desai,et al.  Probing the structure of falcipain‐3, a cysteine protease from Plasmodium falciparum: Comparative protein modeling and docking studies , 2003, Protein science : a publication of the Protein Society.

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

[7]  S. Diekmann,et al.  Molecular Basis of the Interaction Specificity between the Human Glucocorticoid Receptor and Its Endogenous Steroid Ligand Cortisol , 2005, Chembiochem : a European journal of chemical biology.

[8]  Andreas Evers,et al.  Virtual screening of biogenic amine-binding G-protein coupled receptors: comparative evaluation of protein- and ligand-based virtual screening protocols. , 2005, Journal of medicinal chemistry.

[9]  O. Wiest,et al.  Inhibition studies with rationally designed inhibitors of the human low molecular weight protein tyrosine phosphatase. , 2004, Bioorganic & medicinal chemistry.

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

[11]  R Abagyan,et al.  High-throughput docking for lead generation. , 2001, Current opinion in chemical biology.

[12]  Mark Whittaker,et al.  The selection and design of GPCR ligands: from concept to the clinic. , 2004, Combinatorial chemistry & high throughput screening.

[13]  Margaret A. Johnson,et al.  A novel modeling protocol for protein receptors guided by bound-ligand conformation. , 2003, Biochemistry.

[14]  E. Jaeger,et al.  Docking: successes and challenges. , 2005, Current pharmaceutical design.

[15]  S. Tanuma,et al.  Structure basis for the inhibitory mechanism of a novel DNase γ-specific inhibitor, DR396 , 2006 .

[16]  G. Klebe,et al.  Successful virtual screening for a submicromolar antagonist of the neurokinin-1 receptor based on a ligand-supported homology model. , 2004, Journal of medicinal chemistry.

[17]  Johan Schultz,et al.  Structure-based screening and design in drug discovery. , 2002, Drug discovery today.

[18]  G Klebe,et al.  Docking ligands onto binding site representations derived from proteins built by homology modelling. , 2001, Journal of molecular biology.

[19]  Didier Rognan,et al.  Protein‐based virtual screening of chemical databases. II. Are homology models of g‐protein coupled receptors suitable targets? , 2002, Proteins.

[20]  Thomas Meyer,et al.  Identification of cylin-dependent kinase 1 inhibitors of a new chemical type by structure-based design and database searching , 2001, J. Comput. Aided Mol. Des..

[21]  M. Pusch,et al.  Molecular modeling of p-chlorophenoxyacetic acid binding to the CLC-0 channel. , 2003, Biochemistry.

[22]  T. Bishop,et al.  Homology modeling using multiple molecular dynamics simulations and docking studies of the human androgen receptor ligand binding domain bound to testosterone and nonsteroidal ligands. , 2001, Journal of medicinal chemistry.

[23]  Michael K. Gilson,et al.  Screening Drug-Like Compounds by Docking to Homology Models: A Systematic Study , 2006, J. Chem. Inf. Model..

[24]  Laurence Miguet,et al.  Comparison of a homology model and the crystallographic structure of human 11β-hydroxysteroid dehydrogenase type 1 (11βHSD1) in a structure-based identification of inhibitors , 2006, J. Comput. Aided Mol. Des..

[25]  Alexander Hillisch,et al.  Dissecting Physiological Roles of Estrogen Receptor α and β with Potent Selective Ligands from Structure-Based Design , 2004 .

[26]  M. Inagaki,et al.  Design and synthesis of Rho kinase inhibitors (I). , 2004, Bioorganic & medicinal chemistry.

[27]  J. Mccammon,et al.  Accommodating Protein Flexibility in Computational Drug Design 1 , 2 , 2000 .

[28]  M. Karplus,et al.  CHARMM: A program for macromolecular energy, minimization, and dynamics calculations , 1983 .

[29]  Cheng Luo,et al.  A 3D model of SARS_CoV 3CL proteinase and its inhibitors design by virtual screening. , 2003, Acta pharmacologica Sinica.

[30]  E. Bradley,et al.  Performance of 3D-database molecular docking studies into homology models. , 2004, Journal of medicinal chemistry.

[31]  Ruben Abagyan,et al.  Nuclear hormone receptor targeted virtual screening. , 2003, Journal of medicinal chemistry.

[32]  B. Honig,et al.  Structural genomics: Computational methods for structure analysis , 2003, Protein science : a publication of the Protein Society.

[33]  O. Wiest,et al.  Toward selective histone deacetylase inhibitor design: homology modeling, docking studies, and molecular dynamics simulations of human class I histone deacetylases. , 2005, Journal of medicinal chemistry.

[34]  M. Zacharias,et al.  Molecular determinants for high-affinity block of human EAG potassium channels by antiarrhythmic agents. , 2004, Molecular pharmacology.

[35]  P. Kollman,et al.  Combined molecular mechanical and continuum solvent approach (MM-PBSA/GBSA) to predict ligand binding , 2000 .

[36]  I. Muegge,et al.  Virtual screening for kinase targets. , 2004, Current medicinal chemistry.

[37]  Jiri Gut,et al.  Identification of novel parasitic cysteine protease inhibitors using virtual screening. 1. The ChemBridge database. , 2004, Journal of medicinal chemistry.

[38]  Renxiao Wang,et al.  Comparative evaluation of 11 scoring functions for molecular docking. , 2003, Journal of medicinal chemistry.

[39]  Hans-Dieter Höltje,et al.  Molecular design of two sterol 14α-demethylase homology models and their interactions with the azole antifungals ketoconazole and bifonazole , 2005, J. Comput. Aided Mol. Des..

[40]  B. Shoichet,et al.  Information decay in molecular docking screens against holo, apo, and modeled conformations of enzymes. , 2003, Journal of medicinal chemistry.

[41]  D. Diller,et al.  Kinases, homology models, and high throughput docking. , 2003, Journal of medicinal chemistry.

[42]  J A McCammon,et al.  Accommodating protein flexibility in computational drug design. , 2000, Molecular pharmacology.

[43]  Prashant Desai,et al.  Homology Modeling of Falcipain-2: Validation, De Novo Ligand Design and Synthesis of Novel Inhibitors , 2002, Journal of biomolecular structure & dynamics.

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

[45]  Gordon C K Roberts,et al.  Validation of model of cytochrome P450 2D6: an in silico tool for predicting metabolism and inhibition. , 2004, Journal of medicinal chemistry.

[46]  Irina D. Pogozheva,et al.  Homology modeling of opioid receptor-ligand complexes using experimental constraints , 2005, The AAPS Journal.

[47]  Daniel Fischer,et al.  Servers for protein structure prediction. , 2006, Current opinion in structural biology.

[48]  Berk Hess,et al.  GROMACS 3.0: a package for molecular simulation and trajectory analysis , 2001 .

[49]  A. Elcock,et al.  Rapid computational identification of the targets of protein kinase inhibitors. , 2005, Journal of medicinal chemistry.

[50]  Christian Drosten,et al.  Cinanserin Is an Inhibitor of the 3C-Like Proteinase of Severe Acute Respiratory Syndrome Coronavirus and Strongly Reduces Virus Replication In Vitro , 2005, Journal of Virology.

[51]  G. Klebe,et al.  Ligand-supported homology modelling of protein binding-sites using knowledge-based potentials. , 2003, Journal of molecular biology.

[52]  Nikhil V. Shirahatti,et al.  A Conserved Glutamate Residue in Transmembrane Helix 10 Influences Substrate Specificity of Rabbit OCT2 (SLC22A2)* , 2005, Journal of Biological Chemistry.

[53]  Didier Rognan,et al.  High-Throughput Modeling of Human G-Protein Coupled Receptors: Amino Acid Sequence Alignment, Three-Dimensional Model Building, and Receptor Library Screening , 2004, J. Chem. Inf. Model..

[54]  D. Warhurst,et al.  Resistance to Antifolates in Plasmodium Falciparum, the Causative Agent of Tropical Malaria , 2002, Science progress.

[55]  M. Waterman,et al.  Sterol 14α-demethylase, an abundant and essential mixed-function oxidase , 2005 .

[56]  T. Klabunde,et al.  Structure-based drug discovery using GPCR homology modeling: successful virtual screening for antagonists of the alpha1A adrenergic receptor. , 2005, Journal of medicinal chemistry.

[57]  Thomas Lengauer,et al.  FlexE: efficient molecular docking considering protein structure variations. , 2001, Journal of molecular biology.

[58]  O. Moran,et al.  Binding site of activators of the cystic fibrosis transmembrane conductance regulator in the nucleotide binding domains , 2005, Cellular and Molecular Life Sciences CMLS.

[59]  L. Karlsson,et al.  Checkpoint kinase inhibitors: SAR and radioprotective properties of a series of 2-arylbenzimidazoles. , 2005, Journal of medicinal chemistry.

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

[61]  K. Ginalski Comparative modeling for protein structure prediction. , 2006, Current opinion in structural biology.

[62]  S. Sine,et al.  Toward atomic-scale understanding of ligand recognition in the muscle nicotinic receptor. , 2004, Current medicinal chemistry.

[63]  John B. O. Mitchell,et al.  Predicting protein-ligand binding affinities: a low scoring game? , 2004, Organic & biomolecular chemistry.

[64]  Ceslovas Venclovas,et al.  Comparative modeling in CASP5: Progress is evident, but alignment errors remain a significant hindrance , 2003, Proteins.

[65]  Roland L. Dunbrack,et al.  Prediction of protein side-chain rotamers from a backbone-dependent rotamer library: a new homology modeling tool. , 1997, Journal of molecular biology.