Functional motions modulating VanA ligand binding unraveled by self-organizing maps

Journal of Chemical Information and Modeling

Volumn 54, Issue 1, 2014, Pages 289-301

  Bouvier, Guillaume ^a   Duclert Savatier, Nathalie ^a   Desdouits, Nathan ^a   Meziane Cherif, Djalal ^a   Blondel, Arnaud ^a   Courvalin, Patrice ^a   Nilges, Michael ^a   Malliavin, Thérèse E ^a  

^a INSTITUT PASTEUR   (France)

Author keywords

[No Author keywords available]

Indexed keywords

BACTERIA; BINDING ENERGY; CONFORMAL MAPPING; COVALENT BONDS; DOCKS; HYDRAULIC STRUCTURES; LEARNING SYSTEMS; LIGANDS; MOLECULAR DYNAMICS; REACTION INTERMEDIATES; REACTION KINETICS; SUBSTRATES; SULFUR COMPOUNDS;

BINDING AFFINITIES; CONFORMATIONAL TRANSITIONS; ENTEROCOCCUS FAECIUM; MACHINE LEARNING METHODS; METHICILLIN-RESISTANT STAPHYLOCOCCUS AUREUS; MOLECULAR DYNAMICS TRAJECTORIES; PEPTIDOGLYCAN PRECURSORS; PROTEIN-LIGAND INTERACTIONS;

SELF ORGANIZING MAPS;

BACTERIAL PROTEIN; LIGAND; LIGASE; VANA LIGASE, BACTERIA;

ANTIBIOTIC RESISTANCE; ARTIFICIAL INTELLIGENCE; BIOLOGY; CHEMICAL STRUCTURE; CHEMISTRY; COMPUTER PROGRAM; DRUG DESIGN; ENTEROCOCCUS FAECIUM; ENZYME ACTIVE SITE; ENZYMOLOGY; METABOLISM; MOLECULAR DYNAMICS; PROTEIN CONFORMATION; X RAY CRYSTALLOGRAPHY;

ARTIFICIAL INTELLIGENCE; BACTERIAL PROTEINS; CARBON-OXYGEN LIGASES; CATALYTIC DOMAIN; COMPUTATIONAL BIOLOGY; CRYSTALLOGRAPHY, X-RAY; DRUG DESIGN; ENTEROCOCCUS FAECIUM; LIGANDS; MODELS, MOLECULAR; MOLECULAR DYNAMICS SIMULATION; PROTEIN CONFORMATION; SOFTWARE; VANCOMYCIN RESISTANCE;

EID: 84893415679     PISSN: 15499596     EISSN: 1549960X     Source Type: Journal    
DOI: 10.1021/ci400354b     Document Type: Article

References (64)

1. Courvalin, P. Vancomycin resistance in gram-positive cocci Clin. Infect. Dis. 2006, 42, S25-S34
2. Reynolds, P. E. Structure, biochemistry and mechanism of action of glycopeptide antibiotics Eur. J. Clin. Microbiol. Infect. Dis. 1989, 8, 943-950
3. Arthur, M.; Courvalin, P. Genetics and mechanisms of glycopeptide resistance in enterococci Antimicrob. Agents Chemother. 1993, 37, 1563
4. Kovac, A.; Konc, J.; Vehar, B.; Bostock, J.; Chopra, I.; Janezic, D.; Gobec, S. Discovery of new inhibitors of D-alanine:D-alanine ligase by structure-based virtual screening J. Med. Chem. 2008, 51, 7442-7448
5. Kitamura, Y.; Ebihara, A.; Agari, Y.; Shinkai, A.; Hirotsu, K.; Kuramitsu, S. Structure of D-alanine-D-alanine ligase from Thermus thermophilus HB8: cumulative conformational change and enzyme-ligand interactions Acta Crystallogr., Sect. D: Biol. Crystallogr. 2009, 65, 1098-1106
6. Meziane-Cherif, D.; Saul, F.; Haouz, A.; Courvalin, P. Structural and functional characterization of VanG D-Ala: D-Ser ligase associated with vancomycin resistance in Enterococcus faecalis J. Biol. Chem. 2012, 287, 37583-37592
7. Roper, D.; Huyton, T.; Vagin, A.; Dodson, G. The molecular basis of vancomycin resistance in clinically relevant enterococci: crystal structure of D-alanyl-D-lactate ligase (VanA) Proc. Natl. Acad. Sci. U. S. A. 2000, 97, 8921-8925
8. Weinan, E.; Vanden-Eijnden, E. Transition-path theory and path-finding algorithms for the study of rare events Annu. Rev. Phys. Chem. 2010, 61, 391-420
9. Kohonen, T. Essentials of the self-organizing map Neural Networks 2013, 37, 52-65
10. Digles, D.; Ecker, G. F. Self-organizing maps for in silico screening and data visualization Mol. Inf. 2011, 30, 838-846
11. Schneider, P.; Tanrikulu, Y.; Schneider, G. Self-organizing maps in drug discovery: compound library design, scaffold-hopping, repurposing Curr. Med. Chem. 2009, 16, 258-266
12. Noeske, T.; Sasse, B. C.; Stark, H.; Parsons, C. G.; Weil, T.; Schneider, G. Predicting compound selectivity by self-organizing maps: Cross-activities of metabotropic glutamate receptor antagonists ChemMedChem 2006, 1, 1066-1068
13. Ertl, P.; Jelfs, S.; Mühlbacher, J.; Schuffenhauer, A.; Selzer, P. Quest for the rings. in silico exploration of ring universe to identify novel bioactive heteroaromatic scaffolds J. Med. Chem. 2006, 49, 4568-4573
14. Fink, T.; Reymond, J.-L. Virtual exploration of the chemical universe up to 11 atoms of C, N, O, F: assembly of 26.4 million structures (110.9 million stereoisomers) and analysis for new ring systems, stereochemistry, physicochemical properties, compound classes, and drug discovery J. Chem. Inf. Model. 2007, 47, 342-353
15. Mantsyzov, A. B.; Bouvier, G.; Evrard-Todeschi, N.; Bertho, G. Contact-based ligand-clustering approach for the identification of active compounds in virtual screening Adv. Appl. Bioinf. Chem. 2012, 5, 61
16. Bouvier, G.; Evrard-Todeschi, N.; Girault, J.-P.; Bertho, G. Automatic clustering of docking poses in virtual screening process using self-organizing map Bioinformatics 2010, 26, 53-60
17. Hyvönen, M. T.; Hiltunen, Y.; El-Deredy, W.; Ojala, T.; Vaara, J.; Kovanen, P. T.; Ala-Korpela, M. Application of self-organizing maps in conformational analysis of lipids J. Am. Chem. Soc. 2001, 123, 810-816
18. Murtola, T.; Kupiainen, M.; Falck, E.; Vattulainen, I. Conformational analysis of lipid molecules by self-organizing maps J. Chem. Phys. 2007, 126, 054707
19. Fraccalvieri, D.; Pandini, A.; Stella, F.; Bonati, L. Conformational and functional analysis of molecular dynamics trajectories by Self-Organising Maps BMC Bioinf. 2011, 12, 158
20. Fraccalvieri, D.; Tiberti, M.; Pandini, A.; Bonati, L.; Papaleo, E. Functional annotation of the mesophilic-like character of mutants in a cold-adapted enzyme by self-organising map analysis of their molecular dynamics Mol. Biosyst. 2012, 8, 2680-2691
21. De Brevern, A.; Etchebest, C.; Hazout, S. Bayesian probabilistic approach for predicting backbone structures in terms of protein blocks Proteins 2000, 41, 271-287
22. Pandini, A.; Fraccalvieri, D.; Bonati, L. Artificial neural networks for efficient clustering of conformational ensembles and their potential for medicinal chemistry Curr. Top. Med. Chem. 2013, 13, 642-651
23. Case, D.; Cheatham, T.; Darden, T.; Gohlke, H.; Luo, R.; Merz, K.; Onufriev, A.; Simmerling, C.; Wang, B.; Woods, R. The Amber biomolecular simulation programs J. Comput. Chem. 2005, 26, 1668-1688
24. Hornak, V.; Abel, R.; Okur, A.; Strockbine, B.; Roitberg, A.; Simmerling, C. Comparison of multiple AMBER force fields and development of improved protein backbone parameters Proteins 2006, 65, 712-725
25. Wang, J.; Wang, W.; Kollman, P.; Case, D. Antechamber: an accessory software package for molecular mechanical calculations J. Am. Chem. Soc. 2001, 222, U403
26. Wang, J.; Wolf, R.; Caldwell, J.; Kollman, P.; Case, D. Development and testing of a general AMBER force field J. Comput. Chem. 2004, 25, 1157-1174
27. Jorgensen, W. Quantum and statistical mechanical studies of liquids. 10. Transferable intermolecular potential functions for water, alcohols, and ethers. Application to liquid water J. Am. Chem. Soc. 1981, 103, 335-340
28. Pearlman, D.; Case, D.; Caldwell, J.; Ross, W.; Cheatham, T.; DeBolt, S.; Ferguson, D.; Seibel, G.; Kollman, P. AMBER, a package of computer programs for applying molecular mechanics, normal mode analysis, molecular dynamics and free energy calculations to simulate the structural and energetic properties of molecules Comput. Phys. Commun. 1995, 91, 1-41
29. Berendsen, H.; Postma, J.; Gunsteren, W. V.; DiNola, A.; Haak, J. Molecular dynamics with coupling to an external bath J. Chem. Phys. 1984, 81, 3684-3690
30. Essmann, U.; Perera, L.; Berkowitz, M. L.; Darden, T.; Lee, H.; Pedersen, L. G. A smooth particle mesh ewald method J. Chem. Phys. 1995, 103, 8577-8593
31. Nam, K.; Gao, J.; York, D. M. An efficient linear-scaling ewald method for long-range electrostatic interactions in combined QM/MM calculations J. Chem. Theory. Comput. 2005, 1, 2-13
32. Ryckaert, J.; Ciccotti, G.; Berendsen, H. Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes J. Comput. Phys. 1977, 23, 327-341
33. Kohonen, T. Self-Organized formation of topologically correct feature maps Biol. Cybern. 1982, 43, 59-69
34. Kohonen, T. Self-Organizing Maps; Springer Series in Information Sciences, Heidelberg, Germany, 2001.
35. Kloczkowski, A.; Jernigan, R.; Wu, Z.; Song, G.; Yang, L.; Kolinski, A.; Pokarowski, P. Distance matrix-based approach to protein structure prediction J. Struct. Funct. Genomics 2009, 10, 67-81
36. Spill, Y.; Bouvier, G.; Nilges, M. A convective replica-exchange method for sampling new energy basins J. Comput. Chem. 2013, 34, 132-140
37. Beucher, S. Mathematical morphology and its applications to image processing; Springer: 1994; pp 69-76.
38. Pettersen, E.; Goddard, T.; Huang, C.; Couch, G.; Greenblatt, D.; Meng, E.; Ferrin, T. UCSF Chimera-a visualization system for exploratory research and analysis J. Comput. Chem. 2004, 25, 1605-1612
39. http://www.chemaxon.com/products/marvin/marvinsketch (accessed Jan 10, 2014).
40. Shoichet, B.; Bodian, D.; Kuntz, I. Molecular docking using shape descriptors J. Comput. Chem. 1992, 13, 380-397
41. Meng, E.; Shoichet, B.; Kuntz, I. Automated docking with grid-based energy evaluation J. Comput. Chem. 1992, 13, 505-524
42. Lang, P.; Brozell, S.; Mukherjee, S.; Pettersen, E.; Meng, E.; Thomas, V.; Rizzo, R.; Case, D.; James, T.; Kuntz, I. DOCK 6: Combining techniques to model RNA-small molecule complexes RNA 2009, 15, 1219-1230
43. Richards, F. Areas, volumes, packing and protein structure Annu. Rev. Biophys. Bioeng. 1977, 6, 151-176
44. Connolly, M. Solvent-accessible surfaces of proteins and nucleic acids Science 1983, 221, 709-713
45. Kuntz, I.; Blaney, J.; Oatley, S.; Langridge, R.; Ferrin, T. A geometric approach to macromolecule-ligand interactions J. Mol. Biol. 1982, 161, 269-88
46. Srinivasan, J.; Cheatham, T.; Cieplak, P.; Kollman, P.; David, A. Continuum solvent studies of the stability of DNA, RNA, and phosphoramidate-DNA helices J. Am. Chem. Soc. 1998, 120, 9401-9409
47. Kollman, P.; Massova, I.; Reyes, C.; Kuhn, B.; Huo, S.; Chong, L.; Lee, M.; Lee, T.; Duan, Y.; Wang, W.; Donini, G.; Cieplak, P.; Srinivasan, J.; Case, D.; Cheatham, T. Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models Acc. Chem. Res. 2000, 33, 889-897
48. Hawkins, G.; Cramer, C.; Truhlar, D. Pairwise solute descreening of solute charges from a dielectric medium Chem. Phys. Lett. 1995, 246, 122-129
49. Hawkins, G.; Cramer, C.; Truhlar, D. Parametrized models of aqueous free energies of solvation based on pairwise descreening of solute atomic charges from a dielectric medium J. Phys. Chem. 1996, 100, 19824-19839
50. Rizzo, R.; Aynechi, T.; David, A.; Kuntz, I. Estimation of absolute free energies of hydration using continuum methods: accuracy of partial charge models and optimization of nonpolar contributions J. Chem. Theory Comput. 2006, 2, 128-139
51. Ultsch, A. Maps for the visualization of high-dimensional data spaces Proc. Workshop on Self Organizing Maps 2003, 225-230
52. Ultsch, A. U*-matrix: a tool to visualize clusters in high dimensional data; Fachbereich Mathematik und Informatik: 2003.
53. Salomon-Ferrer, R.; Case, D. A.; Walker, R. C. An overview of the amber biomolecular simulation package. Wiley Interdiscip. Rev.: Comput. Mol. Sci. 2012
54. Ding, F.; Dokholyan, N.; Buldyrev, S.; Stanley, H.; Shakhnovich, E. Direct molecular dynamics observation of protein folding transition state ensemble Biophys. J. 2002, 83, 3525-3532
55. Mullins, L.; Zawadzke, L.; Walsh, C. T.; Raushel, F. Kinetic evidence for the formation of d-alanyl phosphate in the mechanism of d-alanyl-d-alanine ligase J. Biol. Chem. 1990, 265, 8993-8998
56. Hrast, M.; Vehar, B.; Turk, S.; Konc, J.; Gobec, S.; Janezic, D. Function of the D alanine: D-alanine ligase lid loop: A molecular modeling and bioactivity study J. Med. Chem. 2012, 55, 6849-6856
57. Klepeis, J. L.; Lindorff-Larsen, K.; Dror, R. O.; Shaw, D. E. Long-timescale molecular dynamics simulations of protein structure and function Curr. Opin. Struct. Biol. 2009, 19, 120-127
58. Hess, B. Convergence of sampling in protein simulations Phy. Rev. E 2002, 65, 031910
59. Bolhuis, P.; Chandler, D.; Dellago, C.; Geissler, P. Transition path sampling: Throwing ropes over rough mountain passes, in the dark Annu. Rev. Phys. Chem. 2002, 53, 291-318
60. Lei, H.; Duan, Y. Improved sampling methods for molecular simulation Curr. Opin. Struct. Biol. 2007, 17, 187-191
61. Mitsutake, A.; Mori, Y.; Okamoto, Y. Biomolecular Simulations Methods and Protocols; Humana Press: 2013; pp 153-195.
62. Vanden-Eijnden, W.; Ren, W.; Vanden-Eijnden, E. Transition pathways in complex systems: Reaction coordinates, isocommittor surfaces, and transition tubes Chem. Phys. Lett. 2005, 413, 242-247
63. Neuhaus, F. Role of the omega loop in specificity determination in subsite 2 of the D-alanine:D-alanine (D-lactate) ligase from Leuconostoc mesenteroides: a molecular docking study J. Mol. Graphics Modell. 2011, 30, 31-37
64. Humphrey, W.; Dalke, A.; Schulten, K. VMD-visual molecular dynamics J. Mol. Graphics 1996, 14, 33-38