Journal of Computer-Aided Molecular Design

, Volume 25, Issue 3, pp 263–274 | Cite as

Structure-guided fragment-based in silico drug design of dengue protease inhibitors

  • Tim Knehans
  • Andreas Schüller
  • Danny N. Doan
  • Kassoum Nacro
  • Jeffrey Hill
  • Peter Güntert
  • M. S. Madhusudhan
  • Tanja Weil
  • Subhash G. Vasudevan
Article

Abstract

An in silico fragment-based drug design approach was devised and applied towards the identification of small molecule inhibitors of the dengue virus (DENV) NS2B-NS3 protease. Currently, no DENV protease co-crystal structure with bound inhibitor and fully formed substrate binding site is available. Therefore a homology model of DENV NS2B-NS3 protease was generated employing a multiple template spatial restraints method and used for structure-based design. A library of molecular fragments was derived from the ZINC screening database with help of the retrosynthetic combinatorial analysis procedure (RECAP). 150,000 molecular fragments were docked to the DENV protease homology model and the docking poses were rescored using a target-specific scoring function. High scoring fragments were assembled to small molecule candidates by an implicit linking cascade. The cascade included substructure searching and structural filters focusing on interactions with the S1 and S2 pockets of the protease. The chemical space adjacent to the promising candidates was further explored by neighborhood searching. A total of 23 compounds were tested experimentally and two compounds were discovered to inhibit dengue protease (IC50 = 7.7 μM and 37.9 μM, respectively) and the related West Nile virus protease (IC50 = 6.3 μM and 39.0 μM, respectively). This study demonstrates the successful application of a structure-guided fragment-based in silico drug design approach for dengue protease inhibitors providing straightforward hit generation using a combination of homology modeling, fragment docking, chemical similarity and structural filters.

Keywords

Dengue virus NS2B-NS3 protease West Nile virus Protease inhibitor Fragment-based drug design (FBDD) Homology modeling 

Supplementary material

10822_2011_9418_MOESM1_ESM.pdf (198 kb)
Supplementary material 1 (PDF 198 kb)

References

  1. 1.
    Division of Vector-Borne Infectious Disease. Centers for Disease Control and Prevention, Atlanta, USA (2010) http://www.cdc.gov/Dengue/ Accessed 23 Sept 2010
  2. 2.
    World Health Organization - Dengue (2010) Geneva, Switzerland. http://www.who.int/topics/dengue/en/ Accessed 23 Sept 2010
  3. 3.
    Lescar J, Luo D, Xu T, Sampath A, Lim SP, Canard B, Vasudevan SG (2008) Towards the design of antiviral inhibitors against flaviviruses: The case for the multifunctional NS3 protein from Dengue virus as a target. Antiviral Res 80:94–101CrossRefGoogle Scholar
  4. 4.
    Luo D, Wei N, Doan DN, Paradkar PN, Chong Y, Davidson AD, Kotaka M, Lescar J, Vasudevan SG (2010) Flexibility between the Protease and Helicase Domains of the Dengue Virus NS3 Protein Conferred by the Linker Region and Its Functional Implications. J Biol Chem 285:18817–18827CrossRefGoogle Scholar
  5. 5.
    Aleshin AE, Shiryaev SA, Strongin AY, Liddington RC (2007) Structural evidence for regulation and specificity of flaviviral proteases and evolution of the Flaviviridae fold. Prot Sci 16:795–806CrossRefGoogle Scholar
  6. 6.
    Erbel P, Schiering N, D’Arcy A, Renatus M, Kroemer M, Lim SP, Yin Z, Keller TH, Vasudevan SG, Hommel U (2006) Structural basis for the activation of flaviviral NS3 proteases from dengue and West Nile virus. Nat Struct Mol Biol 13:372–373CrossRefGoogle Scholar
  7. 7.
    Robin G, Chappell K, Stoermer MJ, Hu S, Young PR, Fairlie DP, Martin JL (2009) Structure of West Nile virus NS3 protease: ligand stabilization of the catalytic conformation. J Mol Biol 385:1568–1577CrossRefGoogle Scholar
  8. 8.
    Chandramouli S, Joseph JS, Daudenarde S, Gatchalian J, Cornillez-Ty C, Kuhn P (2010) Serotype-specific structural differences in the protease-cofactor complexes of the dengue virus family. J Virol 84:3059–3067CrossRefGoogle Scholar
  9. 9.
    Luo D, Xu T, Hunke C, Grüber G, Vasudevan SG, Lescar J (2008) Crystal structure of the NS3 protease-helicase from dengue virus. J Virol 82:173–183CrossRefGoogle Scholar
  10. 10.
    Su X, Ozawa K, Qi R, Vasudevan SG, Lim SP, Otting G (2009) NMR analysis of the dynamic exchange of the NS2B cofactor between open and closed conformations of the West Nile virus NS2B-NS3 protease. PLoS Negl Trop Dis 3:e561CrossRefGoogle Scholar
  11. 11.
    Tomlinson SM, Malmstrom RD, Russo A, Mueller N, Pang Y, Watowich SJ (2009) Structure-based discovery of dengue virus protease inhibitors. Antiviral Res 82:110–114CrossRefGoogle Scholar
  12. 12.
    Yin Z, Patel SJ, Wang W, Wang G, Chan W, Rao KR, Alam J, Jeyaraj DA, Ngew X, Patel V, Beer D, Lim SP, Vasudevan SG, Keller TH (2006) Peptide inhibitors of dengue virus NS3 protease. Part 1: warhead. Bioorg Med Chem Lett 16:36–39CrossRefGoogle Scholar
  13. 13.
    Yin Z, Patel SJ, Wang W, Chan W, Ranga Rao K, Wang G, Ngew X, Patel V, Beer D, Knox JE, Ma NL, Ehrhardt C, Lim SP, Vasudevan SG, Keller TH (2006) Peptide inhibitors of dengue virus NS3 protease. Part 2: SAR study of tetrapeptide aldehyde inhibitors. Bioorg Med Chem Lett 16:40–43CrossRefGoogle Scholar
  14. 14.
    Knox JE, Ma NL, Yin Z, Patel SJ, Wang W, Chan W, Ranga Rao KR, Wang G, Ngew X, Patel V, Beer D, Lim SP, Vasudevan SG, Keller TH (2006) Peptide inhibitors of West Nile NS3 protease:  SAR study of tetrapeptide aldehyde inhibitors. J Med Chem 49:6585–6590CrossRefGoogle Scholar
  15. 15.
    Stoermer MJ, Chappell KJ, Liebscher S, Jensen CM, Gan CH, Gupta PK, Xu W, Young PR, Fairlie DP (2008) Potent cationic inhibitors of West Nile virus NS2B/NS3 protease with serum stability, cell permeability and antiviral activity. J Med Chem 51:5714–5721CrossRefGoogle Scholar
  16. 16.
    Sidique S, Shiryaev SA, Ratnikov BI, Herath A, Su Y, Strongin AY, Cosford ND (2009) Structure-activity relationship and improved hydrolytic stability of pyrazole derivatives that are allosteric inhibitors of West Nile virus NS2B-NS3 proteinase. Bioorg Med Chem Lett 19:5773–5777CrossRefGoogle Scholar
  17. 17.
    Ekonomiuk D, Su X, Ozawa K, Bodenreider C, Lim SP, Otting G, Huang D, Caflisch A (2009) Flaviviral protease inhibitors identified by fragment-based library docking into a structure generated by molecular dynamics. J Med Chem 52:4860–4868CrossRefGoogle Scholar
  18. 18.
    Ekonomiuk D, Su X, Ozawa K, Bodenreider C, Lim SP, Yin Z, Keller TH, Beer D, Patel V, Otting G, Caflisch A, Huang D (2009) Discovery of a non-peptidic inhibitor of West Nile virus NS3 protease by high-throughput docking. PLoS Negl Trop Dis 3:e356CrossRefGoogle Scholar
  19. 19.
    Ganesh VK, Muller N, Judge K, Luan C, Padmanabhan R, Murthy KHM (2005) Identification and characterization of nonsubstrate based inhibitors of the essential dengue and West Nile virus proteases. Bioorg Med Chem 13:257–264CrossRefGoogle Scholar
  20. 20.
    Leung D, Schroder K, White H, Fang N, Stoermer MJ, Abbenante G, Martin JL, Young PR, Fairlie DP (2001) Activity of recombinant dengue 2 Virus NS3 protease in the presence of a truncated NS2B Co-factor, small peptide substrates, and inhibitors. J Biol Chem 276:45762–45771CrossRefGoogle Scholar
  21. 21.
    Nall TA, Chappell KJ, Stoermer MJ, Fang N, Tyndall JDA, Young PR, Fairlie DP (2004) Enzymatic characterization and homology model of a catalytically active recombinant West Nile virus NS3 protease. J Biol Chem 279:48535–48542CrossRefGoogle Scholar
  22. 22.
    Johnston PA, Phillips J, Shun TY, Shinde S, Lazo JS, Huryn DM, Myers MC, Ratnikov BI, Smith JW, Su Y, Dahl R, Cosford NDP, Shiryaev SA, Strongin AY (2007) HTS identifies novel and specific uncompetitive inhibitors of the two-component NS2B-NS3 proteinase of West Nile virus. Assay Drug Dev Technol 5:737–750CrossRefGoogle Scholar
  23. 23.
    Chanprapaph S, Saparpakorn P, Sangma C, Niyomrattanakit P, Hannongbua S, Angsuthanasombat C, Katzenmeier G (2005) Competitive inhibition of the dengue virus NS3 serine protease by synthetic peptides representing polyprotein cleavage sites. Biochem Biophys Res Commun 330:1237–1246CrossRefGoogle Scholar
  24. 24.
    Mueller NH, Pattabiraman N, Ansarah-Sobrinho C, Viswanathan P, Pierson TC, Padmanabhan R (2008) Identification and biochemical characterization of small-molecule inhibitors of west nile virus serine protease by a high-throughput screen. Antimicrob Agents Chemother 52:3385–3393CrossRefGoogle Scholar
  25. 25.
    Shiryaev S, Ratnikov B, Chekanov A, Sikora S, Rozanov D, Godzik A, Wang J, Smith J, Huang Z, Lindberg I, Samuel M, Diamond M, Strongin A (2006) Cleavage targets and the d-arginine-based inhibitors of the West Nile virus NS3 processing proteinase. Biochem J 393:503CrossRefGoogle Scholar
  26. 26.
    Tomlinson SM, Watowich SJ (2008) Substrate inhibition kinetic model for West Nile virus NS2B-NS3 protease. Biochemistry 47:11763–11770CrossRefGoogle Scholar
  27. 27.
    Schechter I, Berger A (1967) On the size of the active site in proteases. I. Papain. Biochem Biophys Res Commun 27:157–162CrossRefGoogle Scholar
  28. 28.
    Sali A, Blundell TL (1993) Comparative protein modelling by satisfaction of spatial restraints. J Mol Biol 234:779–815CrossRefGoogle Scholar
  29. 29.
    Marti-Renom MA, Madhusudhan MS, Sali A (2004) Alignment of protein sequences by their profiles. Protein Sci 13:1071–1087CrossRefGoogle Scholar
  30. 30.
    Shen M, Sali A (2006) Statistical potential for assessment and prediction of protein structures. Protein Sci 15:2507–2524CrossRefGoogle Scholar
  31. 31.
    DeLano W (2009) The PyMOL molecular graphics system. DeLano Scientific, Palo AltoGoogle Scholar
  32. 32.
    Chemical Computing Group (2009) MOE—the molecular operating environment. Montreal, CanadaGoogle Scholar
  33. 33.
    Ramachandran GN, Ramakrishnan C, Sasisekharan V (1963) Stereochemistry of polypeptide chain configurations. J Mol Biol 7:95–99CrossRefGoogle Scholar
  34. 34.
    Irwin JJ, Shoichet BK (2005) ZINC—a free database of commercially available compounds for virtual screening. J Chem Inf Model 45:177–182CrossRefGoogle Scholar
  35. 35.
    Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (2001) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 46:3–26CrossRefGoogle Scholar
  36. 36.
    Lewell XQ, Judd DB, Watson SP, Hann MM (1998) RECAP—retrosynthetic combinatorial analysis procedure: a powerful new technique for identifying privileged molecular fragments with useful applications in combinatorial chemistry. J Chem Inf Comput Sci 38:511–522Google Scholar
  37. 37.
    Congreve M, Carr R, Murray C, Jhoti H (2003) A ‘Rule of Three’ for fragment-based lead discovery? Drug Discov Today 8:876–877CrossRefGoogle Scholar
  38. 38.
    Gasteiger J, Marsili M (1980) Iterative partial equalization of orbital electronegativity - a rapid access to atomic charges. Tetrahedron 36:3219–3228CrossRefGoogle Scholar
  39. 39.
    Morris GM, Huey R, Lindstrom W, Sanner MF, Belew RK, Goodsell DS, Olson AJ (2009) AutoDock4 and AutoDockTools4: automated docking with selective receptor flexibility. J Comput Chem 30:2785–2791CrossRefGoogle Scholar
  40. 40.
    Markley JL, Westler WM (1996) Protonation-state dependence of hydrogen bond strengths and exchange rates in a serine protease catalytic triad: bovine chymotrypsinogen A. Biochem 35:11092–11097CrossRefGoogle Scholar
  41. 41.
    Wang J, Cieplak P, Kollman PA (2000) How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules? J Comput Chem 21:1049–1074CrossRefGoogle Scholar
  42. 42.
    Trott O, Olson AJ (2010) AutoDock Vina: improving the speed and accuracy of docking with a new scoring function, efficient optimization, and multithreading. J Comput Chem 31:455–461Google Scholar
  43. 43.
    Weininger D (1988) SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules. J Chem Inf Comput Sci 28:31–36Google Scholar
  44. 44.
    Accelrys Inc. (2007) Pipeline Pilot. Accelrys Inc., San DiegoGoogle Scholar
  45. 45.
    Rogers D, Hahn M (2010) Extended-connectivity fingerprints. J Chem Inf Model 50:742–754CrossRefGoogle Scholar
  46. 46.
    Tanimoto T (1957) IBM internal report. 1957Google Scholar
  47. 47.
    Jones G, Willett P, Glen RC, Leach AR, Taylor R (1997) Development and validation of a genetic algorithm for flexible docking. J Mol Biol 267:727–748CrossRefGoogle Scholar
  48. 48.
    Eldridge MD, Murray CW, Auton TR, Paolini GV, Mee RP (1997) Empirical scoring functions: I. The development of a fast empirical scoring function to estimate the binding affinity of ligands in receptor complexes. J Comput Aided Mol Des 11:425–445CrossRefGoogle Scholar
  49. 49.
    Li J, Lim SP, Beer D, Patel V, Wen D, Tumanut C, Tully DC, Williams JA, Jiricek J, Priestle JP, Harris JL, Vasudevan SG (2005) Functional profiling of recombinant NS3 proteases from all four serotypes of dengue virus using tetrapeptide and octapeptide substrate libraries. J Biol Chem 280:28766–28774CrossRefGoogle Scholar
  50. 50.
    GraphPad Software Inc. (2009) GraphPad prism. GraphPad Software Inc., La JollaGoogle Scholar
  51. 51.
    Wichapong K, Pianwanit S, Sippl W, Kokpol S (2010) Homology modeling and molecular dynamics simulations of Dengue virus NS2B/NS3 protease: insight into molecular interaction. J Mol Recognit 23:283–300Google Scholar
  52. 52.
    Chappell KJ (2007) Structure-function relationships of the West Nile virus protease NS3 and its cofactor NS2B. PhD thesis, University of Queensland, AustraliaGoogle Scholar
  53. 53.
    Chappell KJ, Stoermer MJ, Fairlie DP, Young PR (2006) Insights to substrate binding and processing by West Nile Virus NS3 protease through combined modeling, protease mutagenesis, and kinetic studies. J Biol Chem 281:38448–38458CrossRefGoogle Scholar
  54. 54.
    Shiryaev SA, Ratnikov BI, Aleshin AE, Kozlov IA, Nelson NA, Lebl M, Smith JW, Liddington RC, Strongin AY (2007) Switching the substrate specificity of the two-component NS2B-NS3 flavivirus proteinase by structure-based mutagenesis. J Virol 81:4501–4509CrossRefGoogle Scholar
  55. 55.
    Kolb P, Caflisch A (2006) Automatic and efficient decomposition of two-dimensional structures of small molecules for fragment-based high-throughput docking. J Med Chem 49:7384–7392CrossRefGoogle Scholar
  56. 56.
    Majeux N, Scarsi M, Caflisch A (2001) Efficient electrostatic solvation model for protein-fragment docking. Proteins 42:256–268CrossRefGoogle Scholar
  57. 57.
    Budin N, Majeux N, Caflisch A (2001) Fragment-based flexible ligand docking by evolutionary optimization. Biol Chem 382:1365–1372CrossRefGoogle Scholar
  58. 58.
    Bemis GW, Murcko MA (1996) The properties of known drugs. 1. Molecular frameworks. J Med Chem 39:2887–2893CrossRefGoogle Scholar
  59. 59.
    Xu Y, Johnson M (2001) Algorithm for naming molecular equivalence classes represented by labeled pseudographs. J Chem Inf Comput Sci 41:181–185Google Scholar
  60. 60.
    Schuffenhauer A, Ertl P, Roggo S, Wetzel S, Koch MA, Waldmann H (2007) The scaffold tree—visualization of the scaffold universe by hierarchical scaffold classification. J Chem Inf Model 47:47–58CrossRefGoogle Scholar
  61. 61.
    Xu Y, Johnson M (2002) Using molecular equivalence numbers to visually explore structural features that distinguish chemical libraries. J Chem Inf Comput Sci 42:912–926Google Scholar
  62. 62.
    Hopkins AL, Groom CR, Alex A (2004) Ligand efficiency: a useful metric for lead selection. Drug Discov Today 9:430–431CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  • Tim Knehans
    • 1
    • 2
  • Andreas Schüller
    • 2
  • Danny N. Doan
    • 2
  • Kassoum Nacro
    • 3
  • Jeffrey Hill
    • 3
  • Peter Güntert
    • 1
  • M. S. Madhusudhan
    • 4
  • Tanja Weil
    • 5
  • Subhash G. Vasudevan
    • 2
  1. 1.Institute of Biophysical Chemistry, Center for Biomolecular Magnetic Resonance and Frankfurt Institute for Advanced StudiesJ.W. Goethe-UniversityFrankfurt am MainGermany
  2. 2.Program in Emerging Infectious DiseasesDuke-NUS Graduate Medical SchoolSingaporeSingapore
  3. 3.Experimental Therapeutic CentreAgency for Science, Technology and Research (A*STAR)SingaporeSingapore
  4. 4.Bioinformatics InstituteAgency for Science, Technology and Research (A*STAR)SingaporeSingapore
  5. 5.Institute of Organic Chemistry III/Macromolecular ChemistryUniversity of UlmUlmGermany

Personalised recommendations