Comprehensive Structural and Functional Characterization of the Human Kinome by Protein Structure Modeling and Ligand Virtual Screening

The growing interest in the identification of kinase inhibitors, promising therapeutics in the treatment of many diseases, has created a demand for the structural characterization of the entire human kinome. At the outset of the drug development process, the lead-finding stage, approaches that enrich the screening library with bioactive compounds are needed. Here, protein structure based methods can play an important role, but despite structural genomics efforts, it is unlikely that the three-dimensional structures of the entire kinome will be available soon. Therefore, at the proteome level, structure-based approaches must rely on predicted models, with a key issue being their utility in virtual ligand screening. In this study, we employ the recently developed FINDSITE/Q-Dock ligand homology modeling approach, which is well-suited for proteome-scale applications using predicted structures, to provide extensive structural and functional characterization of the human kinome. Specifically, we construct structure models for the human kinome; these are subsequently subject to virtual screening against a library of more than 2 million compounds. To rank the compounds, we employ a hierarchical approach that combines ligand- and structure-based filters. Modeling accuracy is carefully validated using available experimental data with particularly encouraging results found for the ability to identify, without prior knowledge, specific kinase inhibitors. More generally, the modeling procedure results in a large number of predicted molecular interactions between kinases and small ligands that should be of practical use in the development of novel inhibitors. The data set is freely available to the academic community via a user-friendly Web interface at http://cssb.biology.gatech.edu/kinomelhm/ as well as at the ZINC Web site ( http://zinc.docking.org/applications/2010Apr/Brylinski-2010.tar.gz ).

[1]  R. Gozalbes,et al.  Development and experimental validation of a docking strategy for the generation of kinase-targeted libraries. , 2008, Journal of medicinal chemistry.

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

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

[4]  Mark S. Johnson,et al.  Generating Conformer Ensembles Using a Multiobjective Genetic Algorithm , 2007, J. Chem. Inf. Model..

[5]  T. Hunter,et al.  The Protein Kinase Complement of the Human Genome , 2002, Science.

[6]  Michal Brylinski,et al.  Q‐DockLHM: Low‐resolution refinement for ligand comparative modeling , 2009, J. Comput. Chem..

[7]  Philip R. Cohen,et al.  The development and therapeutic potential of protein kinase inhibitors. , 1999, Current opinion in chemical biology.

[8]  Ruth Nussinov,et al.  Novel Approach for Efficient Pharmacophore-Based Virtual Screening: Method and Applications , 2009, J. Chem. Inf. Model..

[9]  Ruben Abagyan,et al.  ICM—A new method for protein modeling and design: Applications to docking and structure prediction from the distorted native conformation , 1994, J. Comput. Chem..

[10]  Jeffrey Skolnick,et al.  Assessment of programs for ligand binding affinity prediction , 2008, J. Comput. Chem..

[11]  Johann Hofmann,et al.  The potential for isoenzyme‐selective modulation of protein kinase C , 1997, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

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

[13]  T. Sasase,et al.  Novel protein kinase C‐β isoform selective inhibitor JTT‐010 ameliorates both hyper‐ and hypoalgesia in streptozotocin‐ induced diabetic rats , 2005, Diabetes, obesity & metabolism.

[14]  Jeffrey Skolnick,et al.  Fast procedure for reconstruction of full‐atom protein models from reduced representations , 2008, J. Comput. Chem..

[15]  David S. Goodsell,et al.  Automated docking using a Lamarckian genetic algorithm and an empirical binding free energy function , 1998, J. Comput. Chem..

[16]  Campbell McInnes,et al.  Virtual screening strategies in drug discovery. , 2007, Current opinion in chemical biology.

[17]  J. Skolnick,et al.  A threading-based method (FINDSITE) for ligand-binding site prediction and functional annotation , 2008, Proceedings of the National Academy of Sciences.

[18]  Hilmar Weinmann,et al.  Editorial: Drug Discovery Process for Kinease Inhibitors , 2005 .

[19]  I. Vakser.  Low-resolution docking: prediction of complexes for underdetermined structures. , 1998, Biopolymers.

[20]  Jeffrey Jie-Lou Liao,et al.  Molecular recognition of protein kinase binding pockets for design of potent and selective kinase inhibitors. , 2007, Journal of medicinal chemistry.

[21]  Yongping Yu,et al.  Discovery of a novel protein kinase B inhibitor by structure-based virtual screening. , 2009, Bioorganic & medicinal chemistry letters.

[22]  T J Stout,et al.  High-throughput structural biology in drug discovery: protein kinases. , 2004, Current pharmaceutical design.

[23]  Tania Pencheva,et al.  BMC Bioinformatics BioMed Central Methodology article AMMOS: Automated Molecular Mechanics Optimization tool for in silico Screening , 2022 .

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

[25]  Richard M. Jackson,et al.  Binding Site Similarity Analysis for the Functional Classification of the Protein Kinase Family , 2009, J. Chem. Inf. Model..

[26]  J. Irwin,et al.  Benchmarking sets for molecular docking. , 2006, Journal of medicinal chemistry.

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

[28]  Christine Humblet,et al.  Computation of 3D queries for ROCS based virtual screens , 2009, J. Comput. Aided Mol. Des..

[29]  J. Skolnick,et al.  Development and large scale benchmark testing of the PROSPECTOR_3 threading algorithm , 2004, Proteins.

[30]  Susumu Goto,et al.  LIGAND: database of chemical compounds and reactions in biological pathways , 2002, Nucleic Acids Res..

[31]  Yang Zhang,et al.  Tertiary structure predictions on a comprehensive benchmark of medium to large size proteins. , 2004, Biophysical journal.

[32]  E. Jaeger,et al.  Comparison of automated docking programs as virtual screening tools. , 2005, Journal of Medicinal Chemistry.

[33]  Jürgen Bajorath,et al.  Profile Scaling Increases the Similarity Search Performance of Molecular Fingerprints Containing Numerical Descriptors and Structural Keys , 2003, J. Chem. Inf. Comput. Sci..

[34]  G L Snyder,et al.  Indirubins inhibit glycogen synthase kinase-3 beta and CDK5/p25, two protein kinases involved in abnormal tau phosphorylation in Alzheimer's disease. A property common to most cyclin-dependent kinase inhibitors? , 2001, The Journal of biological chemistry.

[35]  Hilmar Weinmann,et al.  Drug discovery process for kinase inhibitors. , 2005, Chembiochem : a European journal of chemical biology.

[36]  Jaime Prilusky,et al.  Automated analysis of interatomic contacts in proteins , 1999, Bioinform..

[37]  Ajay N. Jain,et al.  Virtual screening in lead discovery and optimization. , 2004, Current opinion in drug discovery & development.

[38]  D. Fabbro,et al.  Activation of protein kinase C subtypes alpha, gamma, delta, epsilon, zeta, and eta by tumor-promoting and nontumor-promoting agents. , 1997, Biochemical pharmacology.

[39]  Jessica Friedman,et al.  A Kinase‐focused Compound Collection: Compilation and Screening Strategy , 2006, Chemical biology & drug design.

[40]  D. J. Price,et al.  Assessing scoring functions for protein-ligand interactions. , 2004, Journal of medicinal chemistry.

[41]  D. Fabbro,et al.  Protein kinase C and mammary cell differentiation: involvement of protein kinase C alpha in the induction of beta-casein expression. , 1994, Cell growth & differentiation : the molecular biology journal of the American Association for Cancer Research.

[42]  Kazuhiro Ishida,et al.  Identification of death-associated protein kinases inhibitors using structure-based virtual screening. , 2009, Journal of medicinal chemistry.

[43]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[44]  Jérôme Hert,et al.  Comparison of Fingerprint-Based Methods for Virtual Screening Using Multiple Bioactive Reference Structures , 2004, J. Chem. Inf. Model..

[45]  Gerhard Klebe,et al.  Successful virtual screening for novel inhibitors of human carbonic anhydrase: strategy and experimental confirmation. , 2002, Journal of medicinal chemistry.

[46]  G. Terstappen,et al.  In silico research in drug discovery. , 2001, Trends in pharmacological sciences.

[47]  Christopher I. Bayly,et al.  Evaluating Virtual Screening Methods: Good and Bad Metrics for the "Early Recognition" Problem , 2007, J. Chem. Inf. Model..

[48]  David Bradshaw,et al.  Therapeutic potential of protein kinase C inhibitors , 2005, Agents and Actions.

[49]  B. Shoichet,et al.  Hierarchical docking of databases of multiple ligand conformations. , 2005, Current topics in medicinal chemistry.

[50]  Tímea Polgár,et al.  Identification of a novel inhibitor of JAK2 tyrosine kinase by structure-based virtual screening. , 2009, Bioorganic & Medicinal Chemistry Letters.

[51]  H. Burris,et al.  Dual kinase inhibition in the treatment of breast cancer: initial experience with the EGFR/ErbB-2 inhibitor lapatinib. , 2004, The oncologist.

[52]  Gerhard Klebe,et al.  Virtual screening for inhibitors of human aldose reductase , 2004, Proteins.

[53]  J Skolnick,et al.  Defrosting the frozen approximation: PROSPECTOR— A new approach to threading , 2001, Proteins.

[54]  Michal Brylinski,et al.  FINDSITE: a combined evolution/structure-based approach to protein function prediction , 2009, Briefings Bioinform..

[55]  Xin Wen,et al.  BindingDB: a web-accessible database of experimentally determined protein–ligand binding affinities , 2006, Nucleic Acids Res..

[56]  Mindy I. Davis,et al.  A quantitative analysis of kinase inhibitor selectivity , 2008, Nature Biotechnology.

[57]  Megan L. Peach,et al.  Directed discovery of agents targeting the Met tyrosine kinase domain by virtual screening. , 2009, Journal of medicinal chemistry.

[58]  Egon L. Willighagen,et al.  The Blue Obelisk—Interoperability in Chemical Informatics , 2006, J. Chem. Inf. Model..

[59]  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..

[60]  M. Hemling,et al.  Protein kinase C inhibitors: novel spirosesquiterpene aldehydes from a marine sponge Aka (= Siphonodictyon) coralliphagum. , 1994, Journal of natural products.

[61]  Richard D. Taylor,et al.  Virtual Screening Using Protein—Ligand Docking: Avoiding Artificial Enrichment. , 2004 .

[62]  Hui Chen,et al.  Discovery of 5-[5-fluoro-2-oxo-1,2- dihydroindol-(3Z)-ylidenemethyl]-2,4- dimethyl-1H-pyrrole-3-carboxylic acid (2-diethylaminoethyl)amide, a novel tyrosine kinase inhibitor targeting vascular endothelial and platelet-derived growth factor receptor tyrosine kinase. , 2003, Journal of medicinal chemistry.

[63]  Z. Xiang,et al.  Prediction of side‐chain conformations on protein surfaces , 2007, Proteins.

[64]  Jin Li,et al.  On Evaluating Molecular-Docking Methods for Pose Prediction and Enrichment Factors , 2006, J. Chem. Inf. Model..

[65]  D. Auclair,et al.  BAY 43-9006 Exhibits Broad Spectrum Oral Antitumor Activity and Targets the RAF/MEK/ERK Pathway and Receptor Tyrosine Kinases Involved in Tumor Progression and Angiogenesis , 2004, Cancer Research.

[66]  Joannis Apostolakis,et al.  Similarity Based Docking , 2008, J. Chem. Inf. Model..

[67]  Stefan Knapp,et al.  Doing more than just the structure-structural genomics in kinase drug discovery. , 2008, Current opinion in chemical biology.

[68]  Conrad C. Huang,et al.  UCSF Chimera—A visualization system for exploratory research and analysis , 2004, J. Comput. Chem..

[69]  S. Soltoff,et al.  Rottlerin: an inappropriate and ineffective inhibitor of PKCdelta. , 2007, Trends in pharmacological sciences.

[70]  Kazuhiro Ito,et al.  Kinase inhibitors and airway inflammation. , 2006, European journal of pharmacology.

[71]  H. Coste,et al.  The bisindolylmaleimide GF 109203X is a potent and selective inhibitor of protein kinase C. , 1991, The Journal of biological chemistry.

[72]  F. Marks,et al.  Rottlerin, a novel protein kinase inhibitor. , 1994, Biochemical and biophysical research communications.

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

[74]  Adrian H Elcock,et al.  Structure selection for protein kinase docking and virtual screening: homology models or crystal structures? , 2006, Current protein & peptide science.

[75]  Dora M Schnur.  Recent trends in library design: 'rational design' revisited. , 2008, Current opinion in drug discovery & development.

[76]  T. Hunter,et al.  The eukaryotic protein kinase superfamily: kinase (catalytic) domain structure and classification 1 , 1995, FASEB journal : official publication of the Federation of American Societies for Experimental Biology.

[77]  Michal Brylinski,et al.  Comparison of structure‐based and threading‐based approaches to protein functional annotation , 2010, Proteins.

[78]  Yongbo Hu,et al.  Comparison of Several Molecular Docking Programs: Pose Prediction and Virtual Screening Accuracy , 2009, J. Chem. Inf. Model..

[79]  Zbyszek Otwinowski,et al.  Structural genomics: keeping up with expanding knowledge of the protein universe. , 2007, Current opinion in structural biology.

[80]  Alexander D. MacKerell,et al.  All-atom empirical potential for molecular modeling and dynamics studies of proteins. , 1998, The journal of physical chemistry. B.

[81]  Jürg Zimmermann,et al.  Effects of a selective inhibitor of the Abl tyrosine kinase on the growth of Bcr–Abl positive cells , 1996, Nature Medicine.

[82]  R. Kroemer.  Structure-based drug design: docking and scoring. , 2007, Current protein & peptide science.

[83]  K. Gibson,et al.  Studies leading to the identification of ZD1839 (IRESSA): an orally active, selective epidermal growth factor receptor tyrosine kinase inhibitor targeted to the treatment of cancer. , 2001, Bioorganic & medicinal chemistry letters.

[84]  Paul Watson,et al.  Virtual Screening Using Protein-Ligand Docking: Avoiding Artificial Enrichment , 2004, J. Chem. Inf. Model..

[85]  R. Huber,et al.  Staurosporine-induced conformational changes of cAMP-dependent protein kinase catalytic subunit explain inhibitory potential. , 1997, Structure.

[86]  Brian K. Shoichet,et al.  ZINC - A Free Database of Commercially Available Compounds for Virtual Screening , 2005, J. Chem. Inf. Model..

[87]  G. Martiny-Baron,et al.  Selective inhibition of protein kinase C isozymes by the indolocarbazole Gö 6976. , 1993, The Journal of biological chemistry.

[88]  Marek Wojciechowski,et al.  Docking of small ligands to low‐resolution and theoretically predicted receptor structures , 2002, J. Comput. Chem..

[89]  T. Tamaoki,et al.  Staurosporine, a potent inhibitor of phospholipid/Ca++dependent protein kinase. , 1986, Biochemical and biophysical research communications.

[90]  Michael G. Rossmann,et al.  An application of the molecular replacement technique in direct space to a known protein structure , 1975 .

[91]  Burkhard Rost,et al.  Evaluation of template‐based models in CASP8 with standard measures , 2009, Proteins.

[92]  Aurélien Grosdidier,et al.  Docking, virtual high throughput screening and in silico fragment-based drug design , 2009, Journal of cellular and molecular medicine.

[93]  Robert W. Harrison,et al.  Stiffness and energy conservation in molecular dynamics: An improved integrator , 1993, J. Comput. Chem..

[94]  P. Parker,et al.  The extended protein kinase C superfamily. , 1998, The Biochemical journal.

[95]  Roland L. Dunbrack,et al.  proteins STRUCTURE O FUNCTION O BIOINFORMATICS Improved prediction of protein side-chain conformations with SCWRL4 , 2022 .

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

[97]  Z. Xiang,et al.  Extending the accuracy limits of prediction for side-chain conformations. , 2001, Journal of molecular biology.

[98]  Gerhard Klebe,et al.  Molecular Docking Screens Using Comparative Models of Proteins , 2009, J. Chem. Inf. Model..

[99]  N. Grishin,et al.  Side‐chain modeling with an optimized scoring function , 2002, Protein science : a publication of the Protein Society.

[100]  A. Basu,et al.  The potential of protein kinase C as a target for anticancer treatment. , 1993, Pharmacology & therapeutics.

[101]  L. Johnson,et al.  Protein Kinase Inhibitors: Insights into Drug Design from Structure , 2004, Science.

[102]  Mohane Selvaraj Coumar,et al.  Structure-based drug design of novel Aurora kinase A inhibitors: structural basis for potency and specificity. , 2009, Journal of medicinal chemistry.

[103]  J. Skolnick,et al.  Automated structure prediction of weakly homologous proteins on a genomic scale. , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[104]  A Gescher,et al.  Analogs of staurosporine: potential anticancer drugs? , 1998, General pharmacology.

[105]  P. Zarrinkar,et al.  High-throughput kinase profiling as a platform for drug discovery , 2008, Nature Reviews Drug Discovery.

[106]  Thomas Sander,et al.  Comparison of Ligand- and Structure-Based Virtual Screening on the DUD Data Set , 2009, J. Chem. Inf. Model..

[107]  L. Johnson,et al.  Protein kinase inhibition by staurosporine revealed in details of the molecular interaction with CDK2 , 1997, Nature Structural Biology.

[108]  Yang Zhang,et al.  Scoring function for automated assessment of protein structure template quality , 2004, Proteins.

[109]  L. Wodicka,et al.  A small molecule–kinase interaction map for clinical kinase inhibitors , 2005, Nature Biotechnology.

[110]  E. Sausville,et al.  Differential inhibition of protein kinase C isozymes by UCN-01, a staurosporine analogue. , 1994, Molecular pharmacology.

[111]  Y Nishizuka,et al.  Alfred P. Sloan Jr. prize. Studies and prospectives of the protein kinase C family for cellular regulation , 1989, Cancer.

[112]  P. Willett,et al.  Combination of molecular similarity measures using data fusion , 2000 .

[113]  Joannis Apostolakis,et al.  Graph-Based Molecular Alignment (GMA) , 2007, J. Chem. Inf. Model..

[114]  Tomohiko Sasase,et al.  PKC : a target for treating diabetic complications , 2006 .

[115]  P. Cohen,et al.  Specificity and mechanism of action of some commonly used protein kinase inhibitors. , 2000, The Biochemical journal.

[116]  Peter J Kennelly,et al.  Protein kinases and protein phosphatases in prokaryotes: a genomic perspective. , 2002, FEMS microbiology letters.

[117]  John Moult,et al.  A decade of CASP: progress, bottlenecks and prognosis in protein structure prediction. , 2005, Current opinion in structural biology.

[118]  Michal Brylinski,et al.  Q‐Dock: Low‐resolution flexible ligand docking with pocket‐specific threading restraints , 2008, J. Comput. Chem..