A practical approach to docking of zinc metalloproteinase inhibitors.

Forty zinc-dependent metalloproteinase/ligand complexes with known crystal structures were re-docked using five docking/scoring approaches (DOCK, FlexX, DrugScore, GOLD, and AutoDock). Correct geometry of the coordination bonds between the ligand's zinc binding group (ZBG) and the catalytic zinc is important for docking accuracy and scoring reliability. More than 75% of docked poses with RMSD less than 2A were found to have appropriate ZBG binding, but for poor ZBG binding, about 95% of poses failed to dock correctly. Elimination of poses with inappropriate zinc binding resulted in better binding energy predictions that were further improved by dividing the ligands into subsets according to the ZBG (carboxylates, hydroxamates, and phosphorus containing groups). After a subset re-scoring using the regression functions obtained for individual subsets, DrugScore was able to explain 77% and the consensus scoring scheme X-CSCORE even 88% of variance in binding energies. The approach combining ZBG-based pose selection and subset re-scoring improved the hit rate in virtual screening for metalloproteinase inhibitors for all tested methods by 4-16%.

[1]  R. Huber,et al.  X-ray structures of human neutrophil collagenase complexed with peptide hydroxamate and peptide thiol inhibitors. Implications for substrate binding and rational drug design. , 1995, European journal of biochemistry.

[2]  B C Finzel,et al.  Structural characterizations of nonpeptidic thiadiazole inhibitors of matrix metalloproteinases reveal the basis for stromelysin selectivity , 1998, Protein science : a publication of the Protein Society.

[3]  D. E. Clark,et al.  Flexible docking using tabu search and an empirical estimate of binding affinity , 1998, Proteins.

[4]  S Mangani,et al.  High-resolution structure of the complex between carboxypeptidase A and L-phenyl lactate. , 1993, Acta crystallographica. Section D, Biological crystallography.

[5]  J M Blaney,et al.  A geometric approach to macromolecule-ligand interactions. , 1982, Journal of molecular biology.

[6]  M. Walid Qoronfleh,et al.  Structure of human neutrophil collagenase reveals large S1′ specificity pocket , 1994, Nature Structural Biology.

[7]  W. Lipscomb,et al.  Comparison of the structures of three carboxypeptidase A-phosphonate complexes determined by X-ray crystallography. , 1994, Biochemistry.

[8]  J. Gasteiger,et al.  ITERATIVE PARTIAL EQUALIZATION OF ORBITAL ELECTRONEGATIVITY – A RAPID ACCESS TO ATOMIC CHARGES , 1980 .

[9]  H. V. Van Wart,et al.  Crystal structures of MMP-1 and -13 reveal the structural basis for selectivity of collagenase inhibitors , 1999, Nature Structural Biology.

[10]  Oleksandr V. Buzko,et al.  Modified AutoDock for accurate docking of protein kinase inhibitors , 2002, J. Comput. Aided Mol. Des..

[11]  Gennady Verkhivker,et al.  Deciphering common failures in molecular docking of ligand-protein complexes , 2000, J. Comput. Aided Mol. Des..

[12]  E. Shakhnovich,et al.  SMall Molecule Growth 2001 (SMoG2001): an improved knowledge-based scoring function for protein-ligand interactions. , 2002, Journal of medicinal chemistry.

[13]  Charles L. Brooks,et al.  Assessing energy functions for flexible docking , 1998 .

[14]  D. Christianson,et al.  Structural comparison of sulfodiimine and sulfonamide inhibitors in their complexes with zinc enzymes. , 1992, The Journal of biological chemistry.

[15]  Ingo Muegge,et al.  Evaluation of docking/scoring approaches: A comparative study based on MMP3 inhibitors , 2000, J. Comput. Aided Mol. Des..

[16]  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..

[17]  J. Drews.  Drug discovery: a historical perspective. , 2000, Science.

[18]  Robert Powers,et al.  Structure-based design of a novel, potent, and selective inhibitor for MMP-13 utilizing NMR spectroscopy and computer-aided molecular design , 2000 .

[19]  H Matter,et al.  Quantitative structure-activity relationship of human neutrophil collagenase (MMP-8) inhibitors using comparative molecular field analysis and X-ray structure analysis. , 1999, Journal of medicinal chemistry.

[20]  M. Browner,et al.  Crystal structures of matrilysin-inhibitor complexes , 1995 .

[21]  K Nadassy,et al.  Analysis of zinc binding sites in protein crystal structures , 1998, Protein science : a publication of the Protein Society.

[22]  R. Huber,et al.  Structure of malonic acid‐based inhibitors bound to human neutrophil collagenase. A new binding mode explains apparently anomalous data , 1998, Protein science : a publication of the Protein Society.

[23]  S H Kaufmann,et al.  Successful virtual screening of a chemical database for farnesyltransferase inhibitor leads. , 2000, Journal of medicinal chemistry.

[24]  S Mangani,et al.  Crystal structure of the complex between carboxypeptidase A and the biproduct analog inhibitor L-benzylsuccinate at 2.0 A resolution. , 1992, Journal of molecular biology.

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

[26]  Stephen Hanessian,et al.  A comparative docking study and the design of potentially selective MMP inhibitors , 2001, J. Comput. Aided Mol. Des..

[27]  R. Clark,et al.  Consensus scoring for ligand/protein interactions. , 2002, Journal of molecular graphics & modelling.

[28]  H. Tsuzuki,et al.  Homology modeling of gelatinase catalytic domains and docking simulations of novel sulfonamide inhibitors. , 1999, Journal of medicinal chemistry.

[29]  Thomas Lengauer,et al.  A fast flexible docking method using an incremental construction algorithm. , 1996, Journal of molecular biology.

[30]  F. Jørgensen,et al.  A new concept for multidimensional selection of ligand conformations (MultiSelect) and multidimensional scoring (MultiScore) of protein-ligand binding affinities. , 2001, Journal of medicinal chemistry.

[31]  Luhua Lai,et al.  Further development and validation of empirical scoring functions for structure-based binding affinity prediction , 2002, J. Comput. Aided Mol. Des..

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

[33]  W. Lipscomb,et al.  X-ray crystallographic investigation of substrate binding to carboxypeptidase A at subzero temperature. , 1982, Proceedings of the National Academy of Sciences of the United States of America.

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

[35]  M. L. Connolly.  Solvent-accessible surfaces of proteins and nucleic acids. , 1983, Science.

[36]  A. Patchett,et al.  Recent developments in the design of angiotensin‐converting enzyme inhibitors , 1985, Medicinal research reviews.

[37]  D S Goodsell,et al.  Automated docking of flexible ligands: Applications of autodock , 1996, Journal of molecular recognition : JMR.

[38]  M. Maccoss,et al.  Inhibition of stromelysin-1 (MMP-3) by P1'-biphenylylethyl carboxyalkyl dipeptides. , 1997, Journal of medicinal chemistry.

[39]  D. Goodsell,et al.  Automated docking of substrates to proteins by simulated annealing , 1990, Proteins.

[40]  I. Kuntz.  Structure-Based Strategies for Drug Design and Discovery , 1992, Science.

[41]  M. Browner,et al.  Matrilysin-inhibitor complexes: common themes among metalloproteases. , 1996, Biochemistry.

[42]  B P Roques,et al.  Crystal structures of alpha-mercaptoacyldipeptides in the thermolysin active site: structural parameters for a Zn monodentation or bidentation in metalloendopeptidases. , 1999, Biochemistry.

[43]  M Rarey,et al.  Detailed analysis of scoring functions for virtual screening. , 2001, Journal of medicinal chemistry.

[44]  Yuan-Ping Pang,et al.  EUDOC: a computer program for identification of drug interaction sites in macromolecules and drug leads from chemical databases , 2001, J. Comput. Chem..

[45]  Hans-Joachim Böhm,et al.  Prediction of binding constants of protein ligands: A fast method for the prioritization of hits obtained from de novo design or 3D database search programs , 1998, J. Comput. Aided Mol. Des..

[46]  Colin McMartin,et al.  QXP: Powerful, rapid computer algorithms for structure-based drug design , 1997, J. Comput. Aided Mol. Des..

[47]  Weiliang Zhu,et al.  Quantum Chemistry Study on the Interaction of the Exogenous Ligands and the Catalytic Zinc Ion in Matrix Metalloproteinases , 2002 .

[48]  R. Huber,et al.  The X‐ray crystal structure of the catalytic domain of human neutrophil collagenase inhibited by a substrate analogue reveals the essentials for catalysis and specificity. , 1994, The EMBO journal.

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

[50]  Luhua Lai,et al.  SCORE: A New Empirical Method for Estimating the Binding Affinity of a Protein-Ligand Complex , 1998 .

[51]  T. Blundell,et al.  X‐ray structure of human stromelysin catalytic domain complexed with nonpeptide inhibitors: Implications for inhibitor selectivity , 1999, Protein science : a publication of the Protein Society.

[52]  P A Kollman,et al.  Calculation and prediction of binding free energies for the matrix metalloproteinases. , 2000, Journal of medicinal chemistry.

[53]  D. Fairlie,et al.  Protease inhibitors: current status and future prospects. , 2000, Journal of medicinal chemistry.

[54]  Robin Taylor,et al.  SuperStar: a knowledge-based approach for identifying interaction sites in proteins. , 1999, Journal of molecular biology.

[55]  Jonathan W. Essex,et al.  A review of protein-small molecule docking methods , 2002, J. Comput. Aided Mol. Des..

[56]  Brian W. Matthews,et al.  Structural basis of the action of thermolysin and related zinc peptidases , 1988 .

[57]  W. Bode,et al.  Structure determination and analysis of human neutrophil collagenase complexed with a hydroxamate inhibitor. , 1995, Biochemistry.

[58]  M. Murcko,et al.  Consensus scoring: A method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins. , 1999, Journal of medicinal chemistry.

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

[60]  William G. Stetler-Stevenson,et al.  Matrix Metalloproteinases , 1997, Drugs & aging.

[61]  G. V. Paolini,et al.  Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes , 1997, J. Comput. Aided Mol. Des..

[62]  J. Springer,et al.  Stromelysin‐1: Three‐dimensional structure of the inhibited catalytic domain and of the C‐truncated proenzyme , 1995, Protein science : a publication of the Protein Society.

[63]  B Cox,et al.  Application of high-throughput screening techniques to drug discovery. , 2000 .

[64]  A. N. Jain,et al.  Hammerhead: fast, fully automated docking of flexible ligands to protein binding sites. , 1996, Chemistry & biology.

[65]  W. Lipscomb,et al.  Crystal structure of the complex of carboxypeptidase A with a strongly bound phosphonate in a new crystalline form: comparison with structures of other complexes. , 1990, Biochemistry.

[66]  G. Klebe,et al.  Knowledge-based scoring function to predict protein-ligand interactions. , 2000, Journal of molecular biology.