Advertisement

Grid Assisted Ensemble Molecular Dynamics Simulations of HIV-1 Proteases Reveal Novel Conformations of the Inhibitor Saquinavir

  • S. Kashif Sadiq
  • Stefan J. Zasada
  • Peter V. Coveney
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4216)

Abstract

Drug resistant mutations have severely limited the success of HIV therapy. Here we provide insight into the molecular basis of drug resistance in HIV-1 protease with the inhibitor saquinavir. We employ protocols consisting of chained molecular dynamics simulations that allow preparation of desired mutants from an available wildtype structure. By conducting ensembles of molecular dynamics simulations we report differing frequencies of adoption of four stable conformations of the P2 subsite of saquinavir. The P2 subsite hydrogen bonds more frequently with the catalytic aspartic acid dyad in the wildtype, whilst preferring to bind with the flaps of the protease in three chosen mutants. Previously such simulations have been demanding to perform on computational grids due to the difficulty in tracking large numbers of simulations. Using the Application Hosting Environment, a lightweight grid middleware solution, we present a simple way to construct chained ensembles of simulations seamlessly across multiple grid resources.

Keywords

Root Mean Square Deviation Grid Resource Drug Resistant Mutation General Amber Force Field G48V Mutation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Wittayanarakul, K., Aruksakunwong, O., Saen-oon, S., Chantratita, W., Parasuk, V., Sompornpisut, P., Hannongbua, S.: Insights into saquinavir resistance in the G48V HIV-1 protease: Quantum calculations and molecular dynamic simulations. Biophys. J. 88, 867–879 (2005)CrossRefGoogle Scholar
  2. 2.
    Perryman, A.L., Lin, J., McCammon, J.A.: HIV-1 protease molecular dynamics of a wild-type and of the V82F/I84V mutant: Possible contributions to drug resistance and a potential new target site for drugs. Protein Sci. 13, 1108–1123 (2004)CrossRefGoogle Scholar
  3. 3.
    Wlodawer, A., Erickson, J.W.: Structure-based inhibitors of HIV-1 Protease. Annu. Rev. Biochem. 62, 543–585 (1993)CrossRefGoogle Scholar
  4. 4.
    Wlodawer, A., Vondrasek, J.: Inhibitors of HIV-1 Protease: A Major Success of Structure-Assissted Drug Design. Annu. Rev. Biophys. Biomol. Struct. 27, 249–284 (1998)CrossRefGoogle Scholar
  5. 5.
    Johnson, V.A., Brun-Vezinet, F., Clotet, B., Conway, B., Kuritzkes, D.R., Pillay, D., Schapiro, J., Telenti, A., Richman, D.: Update of the Drug Resistance Mutations in HIV-1: 2005. Int. AIDS Soc. - USA 13, 51–57 (2005)Google Scholar
  6. 6.
    Hoffman, N.G., Schiffer, C.A., Swanstrom, R.: Covariation of amino acid positions in HIV-1 protease. Virology 314, 536–548 (2003)CrossRefGoogle Scholar
  7. 7.
    Zoete, V., Michielin, O., Karplus, M.: Relation between Sequence and Structure of HIV-1 Protease Inhibitor Complexes: A Model System for the Analysis of Protein Flexibility. J. Mol. Biol. 315, 21–52 (2002)CrossRefGoogle Scholar
  8. 8.
    Kumar, M., Hosur, M.V.: Adaptability and flexibility of HIV-1 protease. Eur. J. Biochem. 270, 1231–1239 (2003)CrossRefGoogle Scholar
  9. 9.
    Ermolieff, J., Lin, X., Tang, J.: Kinetic Properties of Saquinavir-Resistant Mutants of Human Immunodeficiency Virus Type 1 Protease and Their Implications in Drug Resistance in Vivo. Biochemistry 36, 12364–12370 (1997)CrossRefGoogle Scholar
  10. 10.
    Graham, S., Karmarkar, A., Mischkinsky, J., Robinson, I., Sedukin, I.: Web Services Resource Framework. Technical report, OASIS Technical Report (2006), http://docs.oasis-open.org/wsrf/wsrf-ws_resource-1.2-spec-os.pdf
  11. 11.
    Meagher, K.L., Carlson, H.A.: Solvation Influences Flap Collapse in HIV-1 Protease. Proteins: Struct. Funct. Bioinf. 58, 119–125 (2005)CrossRefGoogle Scholar
  12. 12.
    Schuettelkopf, A.W., van Aalten, D.M.F.: PRODRG - a tool for high-throughput crystallography of protein-ligand complexes. Acta Crystallogr. D60, 1355–1363 (2004)Google Scholar
  13. 13.
    Frisch, M.J., Trucks, G.W., Schlegel, H.B., Scuseria, G.E., Robe, M.A., Cheeseman, J.R., Zakrzewski, V.G., Montgomery, J.A., Stratman, J., Burant, J.C., et al.: Gaussian 1998, Gaussian Inc., Pittsburgh, PA (2002)Google Scholar
  14. 14.
    Wang, J., Wolf, R.M., Case, D.A., Kollman, P.A.: Development and Testing of a General AMBER Force Field (GAFF). J. Comp. Chem. 25, 1157–1174 (2004)CrossRefGoogle Scholar
  15. 15.
    Lepsik, M., Kriz, Z., Havlas, Z.: Efficiency of a Second-Generation HIV-1 Protease Inhibitor Studied by Molecular Dynamics and Absolute Binding Free Energy Calculations. Proteins: Struct. Funct. Bioinf. 57, 279–293 (2004)CrossRefGoogle Scholar
  16. 16.
    Humphrey, W., Dalke, A., Schulten, K.: VMD - Visual Molecular Dynamics. J. Mol. Graph. 14, 33–38 (1996)CrossRefGoogle Scholar
  17. 17.
    Wang, J.M., Cieplak, P., Kollman, P.A.: How well does a restrained electrostatic potential (RESP) model perform in calculating conformational energies of organic and biological molecules? J. Comp. Chem. 21, 1049–1074 (2000)CrossRefGoogle Scholar
  18. 18.
    Schafmeister, C.E.A.F., Ross, W.S., Romanovski, V.: LEaP. University of California, San Francisco (1995)Google Scholar
  19. 19.
    Case, D.A., Pearlman, J.C.D., III, T.C., Wang, J., Ross, W., Simmerling, C., Darden, T., Merz, T., Stanton, R., Cheng, A., et al.: AMBER7. University of California, San Francisco (2002)Google Scholar
  20. 20.
    Jorgensen, W.L., Chandrasekhar, J., Madura, J.D., Impey, R.W., Klein, M.L.: Comparison of simple potential functions for simulating liquid water. J. Chem. Phys. 79, 926–935 (1983)CrossRefGoogle Scholar
  21. 21.
    Kale, L., Skeel, R., Bhandarkar, M., Brunner, R., Gursoy, A., Krawetz, N., Phillips, J., Shinozaki, A., Varadarajan, K., Schulten, K.: NAMD2: Greater scalability for parallel molecular dynamics. J. Comp. Phys. 151, 283–312 (1999)MATHCrossRefGoogle Scholar
  22. 22.
    Essmann, U., Perera, L., Berkowitz, M.L., Darden, T.: A smooth particle mesh Ewald method. J. Chem. Phys. 103, 8577–9593 (1995)CrossRefGoogle Scholar
  23. 23.
    Ryckaert, J.P., Ciccotti, G., Berendsen, H.J.C.: Numerical integration of the Cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes. J. Comp. Phys. 23, 327–341 (1977)CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • S. Kashif Sadiq
    • 1
  • Stefan J. Zasada
    • 1
  • Peter V. Coveney
    • 1
  1. 1.Centre for Computational Science, Department of ChemistryUniversity College London, Christopher Ingold LaboratoriesLondon

Personalised recommendations