Analysis of X-ray Structures of Matrix Metalloproteinases via Chaotic Map Clustering

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Giangreco, Ilenia ^a   Nicolotti, Orazio ^a   Carotti, Angelo ^a   De Carlo, Francesco ^a   Gargano, Gianfranco ^a   Bellotti, Roberto ^a  

^a UNIVERSITY OF BARI   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

CELL SURFACE RECEPTORS; ELECTROSTATIC POTENTIALS; HOMEOSTATIC REGULATIONS; MATRIX METALLOPROTEINASES; PRIMARY STRUCTURES; SMITH-WATERMAN ALGORITHM; SUBSTRATE SPECIFICITY; TUMOUR PROGRESSION;

BIOINFORMATICS; CHAOTIC SYSTEMS; ELECTROSTATICS; LIGANDS; MULTIPROCESSING SYSTEMS; PROTEINS;

CLUSTERING ALGORITHMS;

LIGAND; MATRIX METALLOPROTEINASE;

ALGORITHM; ARTICLE; CHEMICAL STRUCTURE; CHEMISTRY; CLUSTER ANALYSIS; ENZYME SPECIFICITY; METABOLISM; PROTEIN CONFORMATION; X RAY CRYSTALLOGRAPHY;

ALGORITHMS; CLUSTER ANALYSIS; CRYSTALLOGRAPHY, X-RAY; LIGANDS; MATRIX METALLOPROTEINASES; MODELS, MOLECULAR; PROTEIN CONFORMATION; SUBSTRATE SPECIFICITY;

EID: 77957557405     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-500     Document Type: Article

References (27)

1. Burzlaff N. From Model Complexes for Zinc-Containing Enzymes. Concepts and Models in Bioinorganic Chemistry 2006, 397-429. Wiley-Vch.
2. Overall CM, Kleifeld O. Tumor Microenvironment - Opinion: Validating Matrix Metalloproteinases as Drug Targets and Anti-Targets for Cancer Therapy. Nat Rev Cancer 2006, 6:227-239. 10.1038/nrc1821, 16498445.
3. Terp GE, Cruciani G, Christensen IT, Jorgensen FS. Structural Differences of Matrix Metalloproteinases with Potential Implication for Selectivity Examined by the GRID/CPCA Approach. J Med Chem 2002, 45:675-2684.
4. Overall CM, Lopez-Otin C. Strategies for MMP Inhibition in Cancer: Innovations for the Post-Trial Era. Nat Rev Cancer 2002, 2:657-672. 10.1038/nrc884, 12209155.
5. Willett P. Similarity and Clustering in Chemical Information Systems 1987, New York: John Wiley & Sons.
6. Angelini L, De Carlo F, Marangi C, Pellicoro M, Stramaglia S. Clustering Data by Inhomogeneous Chaotic Map Lattices. Phys Rev Lett 2000, 85:554-557. 10.1103/PhysRevLett.85.554, 10991338.
7. Angelini L, De Carlo F, Marangi C, Mannarelli M, Nardulli G, Pellicoro M, Satalino G, Stramaglia S. Chaotic neural networks clustering: an application to antipersonnel mines detection by dynamical IR imaging. Opt Eng 2001, 40:2878-2884.
8. Marangi C, Angelici L, Mannarelli M, Pellicoro M, Stramaglia S, Attimonelli M, De Robertis M, Nitti L, Pesole G, Saccone C, Tommaseo M. Proceedings of the International Workshop on Modelling Biomedical Signals, Bari, 2001 2002, 196-208. World Scientific, Singapore, Nardulli G, Stramaglia S.
9. Bellotti R, De Carlo F, Stramaglia S. Chaotic map clustering algorithm for EEG analysis. Physica A 2004, 334:222-232.
10. Basalto N, Bellotti R, De Carlo F, Facchi P, Pascazio S. Clustering stock market companies via chaotic map synchronization. Physica A 2005, 345:196-206.
11. Lukacova V, Zhang Y, Mackov M, Baricic P, Raha S, Calva JA, Balaz S. Similarity of Binding Sites of Human Matrix Metalloproteinases. J Biol Chem 2004, 279:14194-14200. 10.1074/jbc.M313474200, 14732707.
12. Pirard B, Matter H. Matrix Metalloproteinase Target Family Landscape: a Chemometrical Approach to Ligand Selectivity Based on Protein Binding Site Analysis. J Med Chem 2006, 49:51-69. 10.1021/jm050363f, 16392792.
13. Nicolotti O, Miscioscia TF, Leonetti F, Muncipinto G, Carotti A. Screening of matrix metalloproteinases available from the protein data bank: insights into biological functions, domain organization, and zinc binding groups. J Chem Inf Mod 2007, 47:2439-48.
14. The Protein Data Bank. , http://www.rcsb.org/pdb/home/home.do
15. Gillet VJ, Nicolotti O. Evaluation of reactant-based and product-based approaches to the design of combinatorial libraries. Perspect Drug Discov Des 2000, 20:265-287.
16. Overall CM, Kleifeld O. Towards third generation matrix metalloproteinase inhibitors for cancer therapy. British Journal of Cancer 2006, 94:941-946. 10.1038/sj.bjc.6603043, 2361222, 16538215.
17. Agrawal A, Romero-Perez D, Jacobsen JA, Villarreal FJ, Cohen SM. Zinc-Binding Groups Modulate Selective Inhibition of MMPs. Chem Med Chem 2008, 3:812-820. 2836234, 18181119.
18. Nicolotti O, Giangreco I, Miscioscia TF, Carotti A. Improving Quantitative Structure-Activity Relationships through Multi-Objective Optimization. J Chem Inf Mod 2009, 49:2290-2302.
19. Henrich S, Richter S, Wade RC. On the use of PIPSA to Guide Target-Selective Drug Design. Chem Med Chem 2008, 3:413-417.
20. Baker NA, Sept D, Joseph S, Holst MJ, McCammon JA. Electrostatics of nanosystems: application to microtubules and the ribosome. Proc Natl Acad Sci USA 2001, 98:10037-10041. 10.1073/pnas.181342398, 56910, 11517324.
21. Dolinsky TJ, Nielsen JE, McCammon JA, Baker NA. PDB2PQR: an automated pipeline for the setup, execution, and analysis of Poisson-Boltzmann electrostatics calculations. Nucleic Acids Research 2004, 32:W665-W667. 10.1093/nar/gkh381, 441519, 15215472.
22. Wade RC, Gabdoulline RR, De Rienzo F. Protein Interaction Property Similarity Analysis. Intl J Quant Chem 2001, 83:122-127.
23. Hodgkin EE, Richards WG. Molecular similarity based on electrostatic potential and electric field. Int J Quant Chem Quant Biol Symp 1987, 14:105-110.
24. Smith TF, Waterman MS. Identification of Common Molecular Subsequences. J Mol Biol 1981, 147:195-197. 10.1016/0022-2836(81)90087-5, 7265238.
25. ROCS, version 2.4.2. 2005, OpenEye Scientific Software, Inc., Santa Fe, NM, USA., http://www.eyesopen.com
26. MATLAB The Language Of Technical Computing Version 7.3. The Mathworks; Natick, MA 2006,
27. Felsenstein J. Evolutionary trees from DNA sequences: a maximum likelihood approach. J Mol Evol 1981, 17:368-376. 10.1007/BF01734359, 7288891.