Skip to main content

Homology modeling, molecular dynamics, e-pharmacophore mapping and docking study of Chikungunya virus nsP2 protease

Journal of Molecular Modeling volume 18, pages 39–51 (2012)Cite this article

Abstract

To date, no suitable vaccine or specific antiviral drug is available to treat Chikungunya viral (CHIKV) fever. Hence, it is essential to identify drug candidates that could potentially impede CHIKV infection. Here, we present the development of a homology model of nsP2 protein based on the crystal structure of the nsP2 protein of Venezuelan equine encephalitis virus (VEEV). The protein modeled was optimized using molecular dynamics simulation; the junction peptides of a nonstructural protein complex were then docked in order to investigate the possible protein–protein interactions between nsP2 and the proteins cleaved by nsP2. The modeling studies conducted shed light on the binding modes, and the critical interactions with the peptides provide insight into the chemical features needed to inhibit the CHIK virus infection. Energy-optimized pharmacophore mapping was performed using the junction peptides. Based on the results, we propose the pharmacophore features that must be present in an inhibitor of nsP2 protease. The resulting pharmacophore model contained an aromatic ring, a hydrophobic and three hydrogen-bond donor sites. Using these pharmacophore features, we screened a large public library of compounds (Asinex, Maybridge, TOSLab, Binding Database) to find a potential ligand that could inhibit the nsP2 protein. The compounds that yielded a fitness score of more than 1.0 were further subjected to Glide HTVS and Glide XP. Here, we report the best four compounds based on their docking scores; these compounds have IDs of 27943, 21362, ASN 01107557 and ASN 01541696. We propose that these compounds could bind to the active site of nsP2 protease and inhibit this enzyme. Furthermore, the backbone structural scaffolds of these four lead compounds could serve as building blocks when designing drug-like molecules for the treatment of Chikungunya viral fever.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9

References

  1. Sourisseau M, Schilte C, Casartelli N, Trouillet C, Guivel-Benhassine F, Rudnicka D, Sol-Foulon N, Roux KL, Prevost M-C, Fsihi H, Frenkiel M-P, Blanchet F, Afonso PV, Ceccaldi P-E, Ozden S, Gessain A, Schuffenecker I, Verhasselt B, Zamborlini A, Saib A, Rey FA, Arenzana-Seisdedos F, Despres P, Michault A, Albert ML, Schwartz O (2007) Characterization of reemerging Chikungunya virus. PLoS Pathog 3:804–817

    Google Scholar 

  2. Schuffenecker I, Iteman I, Michault A, Murri S, Frangeul L, Vaney M-C, Lavenir R, Pardigon N, Reynes J-M, Pettinelli F, Biscornet L, Diancourt L, Michel S, Duquerroy S, Guigon G, Frenkiel M-P, Brhin A-C, Cubito N, Desprs P, Kunst F, Rey F, Zeller H, Brisse S (2006) Genome microevolution of chikungunya viruses causing the Indian Ocean outbreak. PLoS Med 3:1058–1070

    Article  CAS  Google Scholar 

  3. Ng LFP, Chow A, Sun YJ, Kwek DJC, Lim PL, Dimatatac F, Ng LC, Ooi EE, Choo KH, Her Z, Kourilsky P, Leo YS (2009) IL-β, IL-6, and RANTES as biomarkers of Chikungunya severity. PLoS ONE 4:e4261

  4. Vanlandingham DL, Hong C, Klingler K, Tsetsarkin K, McElroy KL, Powers AM, Lehane MJ, Higgs S (2005) Differential infectivities of O’nyong-nyong and Chikungunya virus isolates in anopheles gambiae and Aedes aegypti mosquitoes. Am J Trop Med Hyg 72:616–621

    Google Scholar 

  5. Chopra A, Anuradha V, Lagoo-Joshi V, Kunjir V, Salvi S, Saluja M (2008) Chikungunya virus aches and pains: an emerging challenge. Arthritis Rheum 58:2921–2922

    Google Scholar 

  6. Pardigon N (2009) The biology of chikungunya: a brief review of what we still do not know. Pathol Biol 57:127–132

    Google Scholar 

  7. Takkinen K (1986) Complete nucleotide sequence of the nonstructural protein genes of Semliki Forest virus. Nucleic Acids Res 14:5667–5682

    Article  CAS  Google Scholar 

  8. Khan AH, Morita K, MdC P, Hasebe F, Mathenge EGM, Igarashi A (2002) Complete nucleotide sequence of Chikungunya virus and evidence for an internal polyadenylation site. J Gen Virol 83:3075–3084

    Google Scholar 

  9. Strauss EGS, Strauss JH (1986) Structure and replication of the alphavirus genome. The Togaviridae and Flaviridae. Plenum, New York, pp 35–90

  10. Lulla A, Lulla V, Tints K, Ahola T, Merits A (2006) Molecular determinants of substrate specificity for Semliki Forest virus nonstructural protease. J Virol 80:5413–5422

    Google Scholar 

  11. Perri S, Driver DA, Gardner JP, Sherrill S, Belli BA, Dubensky TW Jr, Polo JM (2000) Replicon vectors derived from Sindbis virus and Semliki Forest virus that establish persistent replication in host cells. J Virol 74:9802–9807

    Google Scholar 

  12. Zhang D, Tözsér J, Waugh DS (2009) Molecular cloning, overproduction, purification and biochemical characterization of the p39 nsp2 protease domains encoded by three alphaviruses. Protein Expr Purif 64:89–97

    Article  CAS  Google Scholar 

  13. Vasiljeva L, Merits A, Auvinen P, Kaariainen L (2000) Identification of a novel function of the alphavirus capping apparatus. J Biol Chem 275:17281–17287

    Google Scholar 

  14. Li L, Darden T, Hiskey R, Pedersen L (1996) Homology modeling and molecular dynamics simulations of the Gla domains of human coagulation factor IX and its G[12]A mutant. J Phys Chem 100:2475–2479

    Google Scholar 

  15. Kevin JB, Edmond C, Huafeng X, Ron OD, Michael PE, Brent AG, John LK, Istvan K, Mark AM, Federico DS, John KS, Yibing S, David ES (2006) Scalable algorithms for molecular dynamics simulations on commodity clusters. In: Proceedings of the 2006 ACM/IEEE Conference on Supercomputing. ACM, Tampa

  16. Shaw DE (2005) A fast, scalable method for the parallel evaluation of distance-limited pairwise particle interactions. J Comput Chem 26:1318–1328

    Article  CAS  Google Scholar 

  17. Bairoch A, Boeckmann B, Ferro S, Gasteiger E (2004) Swiss-Prot: juggling between evolution and stability. Brief Bioinform 5:39–55

    Google Scholar 

  18. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ (1997) Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 25:3389–3402

    Article  CAS  Google Scholar 

  19. Russo AT, White MA, Watowich SJ (2006) The crystal structure of the Venezuelan equine encephalitis alphavirus nsP2 protease. Structure 14:1449–1458

    Google Scholar 

  20. Schrödinger, LLC (2009) Prime, version 2.1. Schrödinger, LLC, New York

  21. Jorgensen WL, Maxwell DS, Tirado-Rives J (1996) Development and testing of the OPLS all-atom force field on conformational energetics and properties of organic liquids. J Am Chem Soc 118:11225–11236

    Google Scholar 

  22. Laskowski RA, MacArthur MW, Moss DS, Thornton JM (1993) PROCHECK: a program to check the stereochemical quality of protein structures. J Appl Crystallogr 26:283–291

    Article  CAS  Google Scholar 

  23. Sippl MJ (1993) Recognition of errors in three-dimensional structures of proteins. Proteins Struct Funct Bioinf 17:355–362

    Google Scholar 

  24. PyMOL (2010) PyMOL molecular graphics system website. http://www.pymol.org, accessed 2010

  25. Bowers KJ, Dror RO, Shaw DE (2006) The midpoint method for parallelization of particle simulations. J Chem Phys 124:184109–184111

    Article  Google Scholar 

  26. Kaminski GA, Friesner RA, Tirado-Rives J, Jorgensen WL (2001) Evaluation and reparametrization of the OPLS-AA force field for proteins via comparison with accurate quantum chemical calculations on peptides. J Phys Chem B 105:6474–6487

    Google Scholar 

  27. Jørgensen AM, Topiol S (2008) Driving forces for ligand migration in the leucine transporter. Chem Biol Drug Des 72:265–272

    Google Scholar 

  28. Lauria A, Ippolito M, Almerico AM (2009) Inside the Hsp90 inhibitors binding mode through induced fit docking. J Mol Graph Model 27:712–722

    Article  CAS  Google Scholar 

  29. Wang H, Aslanian R, Madison VS (2008) Induced-fit docking of mometasone furoate and further evidence for glucocorticoid receptor 17[alpha] pocket flexibility. J Mol Graph 27:512–521

    Article  CAS  Google Scholar 

  30. Friesner RA, Banks JL, Murphy RB, Halgren TA, Klicic JJ, Mainz DT, Repasky MP, Knoll EH, Shelley M, Perry JK, Shaw DE, Francis P, Shenkin PS (2004) Glide: a new approach for rapid, accurate docking and scoring. 1. Method and assessment of docking accuracy. J Med Chem 47:1739–1749

    Google Scholar 

  31. Salam NK, Nuti R, Sherman W (2009) Novel method for generating structure-based pharmacophores using energetic analysis. J Chem Inf Model 49:2356–2368

    Google Scholar 

  32. Nabuurs SB, Wagener M, de Vlieg J (2007) A flexible approach to induced fit docking. J Med Chem 50:6507–6518

    Google Scholar 

  33. Duffy EM, Jorgensen WL (2000) Prediction of properties from simulations: free energies of solvation in hexadecane, octanol, and water. J Am Chem 122:2878–2888

    Google Scholar 

  34. Lipinski CA, Lombardo F, Dominy BW, Feeney PJ (1997) Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. Adv Drug Deliv Rev 23:3–25

    Article  CAS  Google Scholar 

Download references

Acknowledgments

The authors like to thank the Department of Bioinformatics, Alagappa University, Karaikudi, India for its support and providing the facilities for this work.

Author information

Affiliations

  1. Department of Bioinformatics , Alagappa University, Karaikudi, 63003, India

    Kh. Dhanachandra Singh, Palani Kirubakaran, Karthikeyan Muthusamy & Jeyaraman Jeyakanthan

  2. Bioinformatics Centre, Pondicherry University, Pondicherry, 605 014, India

    Shanthi Nagarajan

  3. Bioinformatics Centre and Computational Biology Laboratory, Department of Bioinformatics, Bharathiar University, Coimbatore, 641 046, India

    Sugunadevi Sakkiah

  4. CAS, Biophysics and Crystallography, University of Madras, Chennai, 600025, India

    Devadasan Velmurgan

Authors
  1. Kh. Dhanachandra Singh
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Palani Kirubakaran
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Shanthi Nagarajan
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Sugunadevi Sakkiah
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Karthikeyan Muthusamy
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Devadasan Velmurgan
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Jeyaraman Jeyakanthan
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Jeyaraman Jeyakanthan.

Additional information

Kh. Dhanachandra Singh, Palani Kirubakaran, and Shanthi Nagarajan contributed equally to this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

Supplementary Figs. 1-4

(DOC 4739 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Singh, K.D., Kirubakaran, P., Nagarajan, S. et al. Homology modeling, molecular dynamics, e-pharmacophore mapping and docking study of Chikungunya virus nsP2 protease. J Mol Model 18, 39–51 (2012). https://doi.org/10.1007/s00894-011-1018-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00894-011-1018-3

Keywords

  • Chikungunya virus
  • Homology modeling
  • Desmond
  • Nonstructural proteins (nsP)
  • Molecular dynamics simulation (MDS)