A Ligand-Based Molecular Modeling Study on Some Matrix Metalloproteinase-1 Inhibitors Using Several 3D QSAR Techniques

Some three-dimensional quantitative structure-activity relationship (3D-QSAR) models have been constructed using the comparative molecular field analysis (CoMFA) and comparative molecular similarity indices (CoMSIA) for a series of 84 proline-based plus 12 structurally more diversified nonproline matrix metalloproteinase inhibitors. The structures of these inhibitors were built from a structure template extracted from the crystal structure of stromelysin. The structures built were divided into the training and test sets for both the CoMFA and CoMSIA analyses for each being composed of 60 and 24 inhibitors, respectively. The structures in the training set were aligned using some alignment rules derived from the analysis of the Ligplot program on a recent crystal structure of ligand-collagenase-1 complex. Some stepwise CoMSIA's were performed on the aligned training set on which the best CoMFA result was obtained. The best CoMSIA model was identified from the stepwise results, and the corresponding pharmacophore features were used for the construction of a pharmacophore hypothesis by the Catalyst 4.9 program. The training set was extended to include 11 structurally more diversified and nonproline inhibitors. To construct a pharmacophore hypothesis, the conformation of 60 structurally aligned proline-based inhibitors was fixed, while that of the 11 structurally more diversified nonproline inhibitors was allowed to vary during the hypothesis construction process. It was found that the predicted activities by the top hypothesis constructed for both the training and test sets were as good in statistics as those predicted by the best CoMSIA model from which the hypothesis was derived. The top hypothesis was mapped onto the structures of several highly active inhibitors selected from both the training and test sets. The goodness of mapping on each inhibitor was found to be correlated well with the activity of each inhibitor.

[1]  R. Cramer,et al.  Comparative molecular field analysis (CoMFA). 1. Effect of shape on binding of steroids to carrier proteins. , 1988, Journal of the American Chemical Society.

[2]  N. Occleston,et al.  A potent, selective inhibitor of matrix metalloproteinase-3 for the topical treatment of chronic dermal ulcers. , 2003, Journal of medicinal chemistry.

[3]  Todd J. A. Ewing,et al.  Critical evaluation of search algorithms for automated molecular docking and database screening , 1997, J. Comput. Chem..

[4]  D. Talbot,et al.  A phase I and pharmacological study of the matrix metalloproteinase inhibitor BB-3644 in patients with solid tumours , 2004, British Journal of Cancer.

[5]  P. Kollman,et al.  A Second Generation Force Field for the Simulation of Proteins, Nucleic Acids, and Organic Molecules , 1995 .

[6]  H Matter,et al.  Affinity and selectivity of matrix metalloproteinase inhibitors: a chemometrical study from the perspective of ligands and proteins. , 1999, Journal of medicinal chemistry.

[7]  Anton J. Hopfinger,et al.  A Simple Clustering Technique To Improve QSAR Model Selection and Predictivity: Application to a Receptor Independent 4D-QSAR Analysis of Cyclic Urea Derived Inhibitors of HIV-1 Protease , 2003, J. Chem. Inf. Comput. Sci..

[8]  R. Leff.  Clinical Trials of a Stromelysin Inhibitor: Osteoarthritis, Matrix Metalloproteinase Inhibition, Cartilage Loss, Surrogate Markers, and Clinical Implications , 1999, Annals of the New York Academy of Sciences.

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

[10]  R. Greenwald.  Matrix metalloproteinase inhibitors in the treatment of arthritis: comment on the article by Vincenti et al. , 1995, Arthritis and rheumatism.

[11]  J. Yasuda,et al.  Highly water-soluble matrix metalloproteinases inhibitors and their effects in a rat adjuvant-induced arthritis model. , 2002, Bioorganic & medicinal chemistry.

[12]  A. Hopfinger,et al.  Construction of 3D-QSAR Models Using the 4D-QSAR Analysis Formalism , 1997 .

[13]  Yan Guo,et al.  Phenoxyphenyl sulfone N-formylhydroxylamines (retrohydroxamates) as potent, selective, orally bioavailable matrix metalloproteinase inhibitors. , 2002, Journal of medicinal chemistry.

[14]  A. Gearing,et al.  Design and therapeutic application of matrix metalloproteinase inhibitors. , 1999, Chemical reviews.

[15]  Y. Okada,et al.  Inhibition of membrane-type 1 matrix metalloproteinase by hydroxamate inhibitors: an examination of the subsite pocket. , 1998, Journal of medicinal chemistry.

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

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

[18]  J M Thornton,et al.  LIGPLOT: a program to generate schematic diagrams of protein-ligand interactions. , 1995, Protein engineering.

[19]  J. Römisch,et al.  Determination of metalloproteinases, plasminogen-activators and their inhibitors in the synovial fluids of patients with rheumatoid arthritis during chemical synoviorthesis. , 1996, Clinica chimica acta; international journal of clinical chemistry.

[20]  G Murphy,et al.  A novel coumarin‐labelled peptide for sensitive continuous assays of the matrix metalloproteinases , 1992, FEBS letters.

[21]  Y. Okada,et al.  A metalloproteinase from human rheumatoid synovial fibroblasts that digests connective tissue matrix components. Purification and characterization. , 1986, The Journal of biological chemistry.

[22]  U. Singh,et al.  A NEW FORCE FIELD FOR MOLECULAR MECHANICAL SIMULATION OF NUCLEIC ACIDS AND PROTEINS , 1984 .

[23]  Arup K. Ghose,et al.  Atomic physicochemical parameters for three dimensional structure directed quantitative structure-activity relationships. 4. Additional parameters for hydrophobic and dispersive interactions and their application for an automated superposition of certain naturally occurring nucleoside antibiotics , 1989, J. Chem. Inf. Comput. Sci..

[24]  G. Klebe.  The use of composite crystal-field environments in molecular recognition and the de novo design of protein ligands. , 1994, Journal of molecular biology.

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

[26]  T. Baker,et al.  Development of new hydroxamate matrix metalloproteinase inhibitors derived from functionalized 4-aminoprolines. , 2000, Journal of medicinal chemistry.

[27]  D. Wilson,et al.  Discovery of CGS 27023A, a non-peptidic, potent, and orally active stromelysin inhibitor that blocks cartilage degradation in rabbits. , 1997, Journal of medicinal chemistry.

[28]  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.

[29]  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.

[30]  Design, synthesis, and biological evaluation of matrix metalloproteinase inhibitors derived from a modified proline scaffold. , 1999, Journal of medicinal chemistry.

[31]  J. Bishop,et al.  Ro 32‐3555, an orally active collagenase inhibitor, prevents cartilage breakdown in vitro and in vivo , 1997, British journal of pharmacology.

[32]  A. Koch,et al.  Expression of matrix metalloproteinase 9 (96-kd gelatinase B) in human rheumatoid arthritis. , 1996, Arthritis and rheumatism.

[33]  Anton J. Hopfinger,et al.  Receptor-Independent 4D-QSAR Analysis of a Set of Norstatine Derived Inhibitors of HIV-1 Protease , 2003, J. Chem. Inf. Comput. Sci..

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

[35]  Andrew Smellie,et al.  Poling: Promoting conformational variation , 1995, J. Comput. Chem..

[36]  G. Klebe,et al.  Molecular similarity indices in a comparative analysis (CoMSIA) of drug molecules to correlate and predict their biological activity. , 1994, Journal of medicinal chemistry.

[37]  R. Cramer,et al.  Validation of the general purpose tripos 5.2 force field , 1989 .

[38]  A. Cole,et al.  Osteoarthritic lesions: involvement of three different collagenases. , 1997, Arthritis and rheumatism.

[39]  W. Welsh,et al.  Three-dimensional quantitative structure-activity relationship (3D-QSAR) models for a novel class of piperazine-based stromelysin-1 (MMP-3) inhibitors: applying a "divide and conquer" strategy. , 2001, Journal of medicinal chemistry.

[40]  S. Zucker,et al.  Localization of Tissue Inhibitor of Matrix Metalloproteinases in Alzheimer's Disease and Normal Brain , 1995, Journal of neuropathology and experimental neurology.

[41]  G. Cruciani,et al.  Generating Optimal Linear PLS Estimations (GOLPE): An Advanced Chemometric Tool for Handling 3D‐QSAR Problems , 1993 .