Virtual Screening and Molecular Dynamics Simulations from a Bank of Molecules of the Amazon Region Against Functional NS3-4A Protease-Helicase Enzyme of Hepatitis C Virus

Applied Biochemistry and Biotechnology

Volumn 176, Issue 6, 2015, Pages 1709-1721

  Pinheiro, Alan Sena ^a   Duarte, Jaqueline Bianca Carvalho ^a   Alves, Cláudio Nahum ^a   de Molfetta, Fábio Alberto ^a  

^a FEDERAL UNIVERSITY OF PARÁ   (Brazil)

Author keywords

Bank of Molecules of the Amazon (BMA); Hepatitis C virus; Molecular docking; Molecular dynamics; NS3 4A protease helicase

Indexed keywords

DIAGNOSIS; ENZYMES; MOLECULAR MODELING; MOLECULES; VIRUSES;

BANK OF MOLECULES OF THE AMAZON (BMA); HELICASES; HEPATITIS C VIRUS; MOLECULAR DOCKING; MOLECULAR DYNAMICS SIMULATIONS; NEW THERAPEUTIC AGENT; REPLICATION PROCESS; ROOT MEAN SQUARE DEVIATIONS;

MOLECULAR DYNAMICS;

HELICASE; HEPACIVIRIN; HYDROGEN; ANTIVIRUS AGENT; NS3 PROTEIN, HEPATITIS C VIRUS; PROTEINASE INHIBITOR; VIRUS PROTEIN;

ARTICLE; ENZYME ACTIVE SITE; ENZYME STRUCTURE; HEPATITIS C VIRUS; MOLECULAR DOCKING; MOLECULAR DYNAMICS; MOLECULAR STABILITY; NONHUMAN; ANTAGONISTS AND INHIBITORS; BRAZIL; CHEMISTRY; ENZYMOLOGY; FEMALE; HEPACIVIRUS; HUMAN; MALE; PRECLINICAL STUDY; PROCEDURES;

HEPATITIS C VIRUS;

ANTIVIRAL AGENTS; BRAZIL; DRUG EVALUATION, PRECLINICAL; FEMALE; HEPACIVIRUS; HUMANS; MALE; MOLECULAR DYNAMICS SIMULATION; PROTEASE INHIBITORS; VIRAL NONSTRUCTURAL PROTEINS;

EID: 84937976449     PISSN: 02732289     EISSN: 15590291     Source Type: Journal    
DOI: 10.1007/s12010-015-1672-5     Document Type: Article

References (63)

1. Ding, K., et al. (2014). Aryl-substituted aminobenzimidazoles targeting the hepatitis C virus internal ribosome entry site. Bioorganic & Medicinal Chemistry Letters, 24(14), 3113–3117.
2. Weiser, B. M., & Tellinghuisen, T. L. (2012). Structural biology of the hepatitis C virus proteins. Drug Discovery Today: Technologies, 9(3), e195–e204.
3. Rodriguez, A., Oliva, C., & Gonzalez, M. (2010). A comparative QM/MM study of the reaction mechanism of the Hepatitis C virus NS3/NS4A protease with the three main natural substrates NS5A/5B, NS4B/5A and NS4A/4B. Physical Chemistry Chemical Physics, 12(28), 8001–8015.
4. Yu, H. J., et al. (2014). Combined 3D-QSAR, Molecular Docking, Molecular Dynamics Simulation, and Binding Free Energy Calculation Studies on the 5-Hydroxy-2H-Pyridazin-3-One Derivatives as HCV NS5B Polymerase Inhibitors. Chemical Biology & Drug Design, 83(1), 89–105.
5. Ortqvist, P., et al. (2010). Discovery of achiral inhibitors of the hepatitis C virus NS3 protease based on 2(1H)-pyrazinones. Bioorganic & Medicinal Chemistry, 18(17), 6512–6525.
6. Meguellati, A., et al. (2014). B-ring modified aurones as promising allosteric inhibitors of hepatitis C virus RNA-dependent RNA polymerase. European Journal of Medicinal Chemistry, 80, 579–592.
7. Pawlotsky, J. M., Chevaliez, S., & McHutchison, J. G. (2007). The hepatitis C virus life cycle as a target for new antiviral therapies. Gastroenterology, 132(5), 1979–1998.
8. Takaya, D., et al. (2011). A new method for induced fit docking (GENIUS) and its application to virtual screening of novel HCV NS3-4A protease inhibitors. Bioorganic & Medicinal Chemistry, 19(22), 6892–6905.
9. Lasheen, D. S., et al. (2013). Analogs design, synthesis and biological evaluation of peptidomimetics with potential anti-HCV activity. Bioorganic & Medicinal Chemistry, 21(10), 2742–2755.
10. Li, X., et al. (2007). Prediction of binding for a kind of non-peptic HCV NS3 serine protease inhibitors from plants by molecular docking and MM-PBSA method. Bioorganic & Medicinal Chemistry, 15(1), 220–226.
11. Lampa, A., et al. (2011). P2-P1 ’ macrocyclization of P2 phenylglycine based HCV NS3 protease inhibitors using ring-closing metathesis. Bioorganic & Medicinal Chemistry, 19(16), 4917–4927.
12. Chaudhuri, R., et al. (2012). Identification of Non-Macrocyclic Small Molecule Inhibitors against the NS3/4A Serine Protease of Hepatitis C Virus through in Silico Screening. Journal of Chemical Information and Modeling, 52(8), 2245–2256.
13. Calderon, L. D., et al. (2009). Amazonian Biodiversity: A View of Drug Development for Leishmaniasis and Malaria. Journal of the Brazilian Chemical Society, 20(6), 1011–1023.
14. Durrant, J. D., Amaro, R. E., & McCammon, J. A. (2009). AutoGrow: A Novel Algorithm for Protein Inhibitor Design. Chemical Biology & Drug Design, 73(2), 168–178.
15. Senn, H. M., & Thiel, W. (2009). QM/MM Methods for Biomolecular Systems. Angewandte Chemie-International Edition, 48(7), 1198–1229.
16. Namba, A. M., V. B. d. Silva, and Silva, C. H. T. P. d. (2008). Dinâmica molecular: teoria e aplicações em planejamento de fármacos. Eclética Química, 33(4).
17. Okimoto, N., et al. (2009). High-Performance Drug Discovery: Computational Screening by Combining Docking and Molecular Dynamics Simulations. Plos Computational Biology, 5(10).
18. de Molfetta, F. A., et al. (2009). Docking and molecular dynamics simulation of quinone compounds with trypanocidal activity. Journal of Molecular Modeling, 15(10), 1175–1184.
19. Bostrom, J., Greenwood, J. R., & Gottfries, J. (2003). Assessing the performance of OMEGA with respect to retrieving bioactive conformations. Journal of Molecular Graphics & Modelling, 21(5), 449–462.
20. Halgren, T. A., & MMFF, V. I. I. (1999). Characterization of MMFF94, MMFF94s, and other widely available force fields for conformational energies and for intermolecular-interaction energies and geometries. Journal of Computational Chemistry, 20(7), 730–748.
21. Kirchmair, J., et al. (2006). Comparative performance assessment of the conformational model generators omega and catalyst: A large-scale survey on the retrieval of protein-bound ligand conformations. Journal of Chemical Information and Modeling, 46(4), 1848–1861.
22. Yongye, A. B., Bender, A., & Martinez-Mayorga, K. (2010). Dynamic clustering threshold reduces conformer ensemble size while maintaining a biologically relevant ensemble. Journal of Computer-Aided Molecular Design, 24(8), 675–686.
23. Thomsen, R., & Christensen, M. H. (2006). MolDock: A new technique for high-accuracy molecular docking. Journal of Medicinal Chemistry, 49(11), 3315–3321.
24. Lang, P. T., et al. (2009). DOCK 6: Combining techniques to model RNA-small molecule complexes. Rna-a Publication of the Rna Society, 15(6), 1219–1230.
25. Storn, R., & Price, K. (1997). Differential evolution - A simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 11(4), 341–359.
26. Gehlhaar, D. K., et al. (1995). Molecular recognition of the inhibitor AG-1343 BY HIV-1 protease - conformationally flexible docking by evolutionary programming. Chemistry & Biology, 2(5), 317–324.
27. Yang, J. M., & Chen, C. C. (2004). GEMDOCK: A generic evolutionary method for molecular docking. Proteins-Structure Function and Bioinformatics, 55(2), 288–304.
28. Deng, W., & Verlinde, C. (2008). Evaluation of Different Virtual Screening Programs for Docking in a Charged Binding Pocket. Journal of Chemical Information and Modeling, 48(10), 2010–2020.
29. Yao, N. H., et al. (1999). Molecular views of viral polyprotein processing revealed by the crystal structure of the hepatitis C virus bifunctional protease-helicase. Structure with Folding & Design, 7(11), 1353–1363.
30. Pettersen, E. F., et al. (2004). UCSF chimera - A visualization system for exploratory research and analysis. Journal of Computational Chemistry, 25(13), 1605–1612.
31. Khan, K. M., et al. (2014). Synthesis and molecular docking studies of potent alpha-glucosidase inhibitors based on biscoumarin skeleton. European Journal of Medicinal Chemistry, 81, 245–252.
32. Jakalian, A., et al. (2000). Fast, efficient generation of high-quality atomic Charges. AM1-BCC model: I. Method. Journal of Computational Chemistry, 21(2), 132–146.
33. Kuntz, I. D., et al. (1982). A geometric approach to macromolecule-ligand interactions. Journal of Molecular Biology, 161(2), 269–288.
34. Meng, E. C., Shoichet, B. K., & Kuntz, I. D. (1992). Automated docking with grid-based energy evaluation. Journal of Computational Chemistry, 13(4), 505–524.
35. Ronn, R., et al. (2006). Exploration of acyl sulfonamides as carboxylic acid replacements in protease inhibitors of the hepatitis C virus full-length NS3. Bioorganic & Medicinal Chemistry, 14(2), 544–559.
36. Moustakas, D. T., et al. (2006). Development and validation of a modular, extensible docking program: DOCK 5. Journal of Computer-Aided Molecular Design, 20(10-11), 601–619.
37. Vijayakumar, K. R., & Gowda, L. R. (2013). Rice (Oryza sativa) lipase: Molecular cloning, functional expression and substrate specificity. Protein Expression and Purification, 88(1), 67–79.
38. Bissantz, C., Folkers, G., & Rognan, D. (2000). Protein-based virtual screening of chemical databases. 1. Evaluation of different docking/scoring combinations. Journal of Medicinal Chemistry, 43(25), 4759–4767.
39. Charifson, P. S., et al. (1999). Consensus scoring: A method for obtaining improved hit rates from docking databases of three-dimensional structures into proteins. Journal of Medicinal Chemistry, 42(25), 5100–5109.
40. Perez-Pineiro, R., et al. (2009). Development of a Novel Virtual Screening Cascade Protocol to Identify Potential Trypanothione Reductase Inhibitors. Journal of Medicinal Chemistry, 52(6), 1670–1680.
41. Teramoto, R., & Fukunishi, H. (2007). Supervised consensus scoring for docking and virtual screening. Journal of Chemical Information and Modeling, 47(2), 526–534.
42. Wiggers, H. J., et al. (2011). Integration of Ligand- and Target-Based Virtual Screening for the Discovery of Cruzain Inhibitors. Molecular Informatics, 30(6-7), 565–578.
43. Wang, R. X., & Wang, S. M. (2001). How does consensus scoring work for virtual library screening? An idealized computer experiment. Journal of Chemical Information and Computer Sciences, 41(5), 1422–1426.
44. Carneiro, A. S., Lameira, J., & Alves, C. N. (2011). A theoretical study of the molecular mechanism of the GAPDH Trypanosoma cruzi enzyme involving iodoacetate inhibitor. Chemical Physics Letters, 514(4-6), 336–340.
45. Sondergaard, C. R., et al. (2011). Improved Treatment of Ligands and Coupling Effects in Empirical Calculation and Rationalization of pK(a) Values. Journal of Chemical Theory and Computation, 7(7), 2284–2295.
46. Byrd, R. H., et al. (1995). A limited memory algorithm for bound constrained optimization. Siam Journal on Scientific Computing, 16(5), 1190–1208.
47. Lima, A. H., Lameira, J., & Alves, C. N. (2012). Protein-ligand interaction of T. cruzi trans-sialidase inhibitors: a docking and QM/MM MD study. Structural Chemistry, 23(1), 147–152.
48. Silva, N. D., Lameira, J., & Alves, C. N. (2011). Computational analysis of aspartic protease plasmepsin II complexed with EH58 inhibitor: a QM/MM MD study. Journal of Molecular Modeling, 17(10), 2631–2638.
49. Dewar, M. J. S., et al. (1985). The development and use of quantum-mechanical molecular-models.76. AM1 - A new general-purpose quantum-mechanical molecular-model. Journal of the American Chemical Society, 107(13), 3902–3909.
50. Jorgensen, W. L., Maxwell, D. S., & TiradoRives, J. (1996). Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. Journal of the American Chemical Society, 118(45), 11225–11236.
51. Jorgensen, W. L., & Madura, J. D. (1983). Quantum and statistical studies of liquids.25. Solvation and conformation of methanol in water. Journal of the American Chemical Society, 105(6), 1407–1413.
52. Field, M. J., et al. (2000). The Dynamo library for molecular simulations using hybrid quantum mechanical and molecular mechanical potentials. Journal of Computational Chemistry, 21(12), 1088–1100.
53. Lameira, J., et al. (2008). A Quantum Mechanics/Molecular Mechanics Study of the Protein-Ligand Interaction of Two Potent Inhibitors of Human O-GlcNAcase: PUGNAc and NAG-Thiazoline. Journal of Physical Chemistry B, 112(45), 14260–14266.
54. Makatini, M. M., et al. (2011). Synthesis and structural studies of pentacycloundecane-based HIV-1 PR inhibitors: A hybrid 2D NMR and docking/QM/MM/MD approach. European Journal of Medicinal Chemistry, 46(9), 3976–3985.
55. Lipinski, C. A., et al. (1997). Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Advanced Drug Delivery Reviews, 23(1-3), 3–25.
56. Hubbard, R. E. (2001). Hydrogen bonds in proteins: Role and strength. In Encyclopedia of Life Sciences. Macmillan Publishers Ltd, Nature Publishing Group.
57. El Dine, R. S., et al. (2011). HCV-NS3/4A Protease Inhibitory Iridoid Glucosides and Dimeric Foliamenthoic Acid Derivatives from Anarrhinum orientale. Journal of Natural Products, 74(5), 943–948.
58. Nurbo, J., et al. (2008). Beta-Amino acid substitutions and structure-based CoMFA modeling of hepatitis C virus NS3 protease inhibitors. Bioorganic & Medicinal Chemistry, 16(10), 5590–5605.
59. Johansson, A., et al. (2003). Acyl sulfonamides as potent protease inhibitors of the hepatitis C virus full-length NS3 (protease-helicase/NTPase): A comparative study of different C-terminals. Bioorganic & Medicinal Chemistry, 11(12), 2551–2568.
60. Wadood, A., et al. (2014). In Silico Identification and Evaluation of Leads for the Simultaneous Inhibition of Protease and Helicase Activities of HCV NS3/4A Protease Using Complex Based Pharmacophore Mapping and Virtual Screening. Plos One, 9(2).
61. Höltje, H. D. S., W. Rognan, D., Folkers, G. (2003). Introduction to comparative protein modeling. In Molecular Modeling: Basic Principles and Applications, Weinheim: Wiley-VCH.
62. Xue, W. W., et al. (2012). Understanding the structural and energetic basis of inhibitor and substrate bound to the full-length NS3/4A: insights from molecular dynamics simulation, binding free energy calculation and network analysis. Molecular Biosystems, 8(10), 2753–2765.
63. Johansson, A., et al. (2002). Tetrapeptides as potent protease inhibitors of hepatitis C virus full-length NS3 (protease-helicase/NTPase). Bioorganic & Medicinal Chemistry, 10(12), 3915–3922.