European Biophysics Journal

, Volume 39, Issue 7, pp 1051–1056 | Cite as

Temperature dependence of fluctuations in HIV1-protease

  • Kay HamacherEmail author
Original Paper


Revealing the structure and the intrinsic dynamics of a protein is paramount to understand its function and other properties of evolutionary importance. Several schemes to obtain such insight in silico were developed over the decades. A computationally efficient protocol approximates the molecular dynamics around its native state by a harmonic potential. In this paper, we introduce a new methodology to combine the various harmonic approaches to understand the folding/unfolding dynamics and the dynamics around the native structure of the protein in a temperature dependent way. We apply this new protocol to the HIV1-protease and discuss the results in the light of events in the adaptive evolution towards drug resistance, which is a major problem in HIV infection.


HIV1-protease Elastic network models Self-consistent pair-contact probability method Statistical mechanics Molecular dynamics 



Parts of this work were supported through a Liebig-Fellowship of the Fonds der chemischen Industrie. Additional financial support of the Fonds der chemischen Industrie is also acknowledged. Figures of molecular structures were generated using VMD (Humphrey et al. 1996).


  1. Atilgan A, Durrell S, Jernigan R, Demirel M, Keskin O, Bahar I (2001) Anisotropy of fluctuation dynamics of proteins with an elastic network model. Biophys J 80:505–515CrossRefPubMedGoogle Scholar
  2. Bahar I, Jernigan RL (1998) Vibrational dynamics of transfer RNAs. Comparison of the free and enzyme-bound forms. J Mol Biol 281:871–884CrossRefPubMedGoogle Scholar
  3. Bahar I, Jernigan R (1999) Cooperative fluctuations and subunit communication in tryptophan synthase. Biochemistry 38:3478–3490CrossRefPubMedGoogle Scholar
  4. Bahar I, Atilgan AR, Erman B (1997) Direct evaluation of thermal fluctuations in protein using a single parameter harmonic potential. Fold Des 2:173–181CrossRefPubMedGoogle Scholar
  5. Brooks B, Karplus M (1983) Harmonic dynamics of proteins: normal modes and fluctuations in bovine pancreatic trypsin inhibitor. Proc Nat Acad Sci 80:6571–6575CrossRefPubMedGoogle Scholar
  6. Brooks B, Janezic D, Karplus M (1995) Harmonic analysis of large systems. I. methodology. J Comp Chem 16(12):1522–1542CrossRefGoogle Scholar
  7. Canino L, Shen T, McCammon JA (2002) Changes in flexbility upon binding: application of the self-consistent pair contact probability method to protein–protein-interaction. J Chem Phys 117(21):9927–9933CrossRefGoogle Scholar
  8. Demirel MC, Keskin O (2005) Protein interactions and fluctuations in a proteomic network using an elastic network model. J Biomol Struct Dyn 22(4):381–386PubMedGoogle Scholar
  9. Dobbins SE, Lesk VI, Sternberg MJE (2008) Insights into protein flexibility: the relationship between normal modes and conformational change upon protein–protein docking. Proc Natl Acad Sci 105(30):10,390–10,395CrossRefPubMedGoogle Scholar
  10. Dodson GG, Lane DP, Verma CS (2008) Molecular simulations of protein dynamics: new windows on mechanisms in biology. EMBO Rep 9(2):144–150CrossRefPubMedGoogle Scholar
  11. Doruker P, Atilgan AR, Bahar I (2000) Dynamics of proteins predicted by molecular dynamics simulations and analytical approaches: application to a-amylase inhibitor. Proteins Struct Func Genet 40:512–524CrossRefGoogle Scholar
  12. Doruker P et al (2002) Important fluctuation dynamics of large protein structures are preserved upon coarse-grained renormalization. Int J Quantum Chem 90(2):822–837CrossRefGoogle Scholar
  13. Erman B (2006) The gaussian network model: precise prediction of residue fluctuations and application to binding problems. Biophys J 91(10):3589–3599CrossRefPubMedGoogle Scholar
  14. Eyal E, Bahar I (2008) Toward a molecular understanding of the anisotropic response of proteins to external forces: insights from elastic network models. Biophys J 94:3424–3435CrossRefPubMedGoogle Scholar
  15. Golub GH, Loan CFV (1996) Matrix Computations, 3rd edn. The Johns Hopkins University Press, BaltimoreGoogle Scholar
  16. Haliloglu T, Seyrek E, Erman B (2008) Prediction of binding sites in receptor-ligand complexes with the Gaussian Network Model. Phys Rev Lett 100:228102CrossRefPubMedGoogle Scholar
  17. Hamacher K (2005) On stochastic global optimization of one-dimensional functions. Physica A 354:547–557CrossRefGoogle Scholar
  18. Hamacher K (2006) Adaptation in stochastic tunneling global optimization of complex potential energy landscapes. Europhys Lett 74(6):944–950CrossRefGoogle Scholar
  19. Hamacher K (2007) Information theoretical measures to analyze trajectories in rational molecular design. J Comp Chem 28(16):2576–2580CrossRefGoogle Scholar
  20. Hamacher K (2008) Relating sequence evolution of HIV1-protease to its underlying molecular mechanics. Gene 422:30–36CrossRefPubMedGoogle Scholar
  21. Hamacher K, McCammon JA (2006) Computing the amino acid specificity of fluctuations in biomolecular systems. J Chem Theory Comput 2(3):873–878CrossRefGoogle Scholar
  22. Hamacher K, Wenzel W (1999) The scaling behaviour of stochastic minimization algorithms in a perfect funnel landscape. Phys Rev E 59(1):938–941CrossRefGoogle Scholar
  23. Hamacher K, Hübsch A, McCammon JA (2006a) A minimal model for stabilization of biomolecules by hydrocarbon cross-linking. J Chem Phys 124(16):164907CrossRefPubMedGoogle Scholar
  24. Hamacher K, Trylska J, McCammon JA (2006b) Dependency map of proteins in the small ribosomal subunit. PLoS Comput Biol 2:e10CrossRefPubMedGoogle Scholar
  25. Housaindokht M, Bozorgmehr M, Bahrololoom M (2008) Analysis of ligand binding to proteins using molecular dynamics simulations. J Theo Biol 254(2):294–300CrossRefGoogle Scholar
  26. Humphrey W, Dalke A, Schulten K (1996) VMD—visual molecular dynamics. J Mol Graphics 14:33Google Scholar
  27. Karplus M, McCammon J (2002) Molecular dynamics simulations of biomolecules. Nat Struct Biol 9(9):646–52CrossRefPubMedGoogle Scholar
  28. Keskin O, Jernigan RL, Bahar I (2000) Proteins with Similar Architecture Exhibit Similar Large-Scale Dynamic Behavior. Biophys J 78(4):2093–2106, URL,
  29. Keskin O, Durell S, Bahar I, Jernigan R, Covell D (2002) Relating molecular flexibility to function: a case study of tubulin. Biophys J 83:663–680CrossRefPubMedGoogle Scholar
  30. Kitao A, Go N (1999) Investigating protein dynamics in collective coordinate space. Curr Op Struct Biol 9:164–169CrossRefGoogle Scholar
  31. Kurt N, Scott W, Schiffer C, Haliloglu T (2003) Cooperative fluctuations of unliganded and substrate-bound HIV-1-protease: A structure-based analysis on a variety of conformations from crystallography and molecular dynamics simulations. Proteins Struct Func Genet 51:409–422CrossRefGoogle Scholar
  32. Lazaridis T (2002) Binding affinity and specifity from computational studies. Curr Org Chem 6:1319–1332CrossRefGoogle Scholar
  33. Little S, Holte S, Routy J, Daar E, Makrowitz M, Collier A, Koup R, Mellors J, Connick E et al (2002) Antiretroviral-drug resistance among patients recently infected with HIV. N Engl J Med 347:385Google Scholar
  34. Lu M, Ma J (2008) A minimalist network model for coarse-grained normal mode analysis and its application to biomolecular x-ray crystallography. Proc Natl Acad Sci 105(40):15358–15363CrossRefPubMedGoogle Scholar
  35. Micheletti C, Banavar JR, Maritan A (2001) Conformations of proteins in equilibrium. Phys Rev Lett 87(8):088102-1Google Scholar
  36. Micheletti C, Cecconi F, Flammini A, Maritan A (2002) Crucial stages of protein folding through a solvable model: prediciting target sites for enzyme-inhibiting drugs. Prot Sci 11:1878–1887CrossRefGoogle Scholar
  37. Micheletti C, Carloni P, Maritan A (2004) Accurate and efficient description of protein vibrational dynamics: comparing molecular dynamics and gaussian models. Proteins 55:635CrossRefPubMedGoogle Scholar
  38. Perryman A, Lin JH, McCammon J (2004) 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. Prot Sci 13:1108–1123CrossRefGoogle Scholar
  39. Press WH et al (1995) Numerical recipes in C. Cambridge University Press, CambridgeGoogle Scholar
  40. Reiling K, Endres N, Dauber D, Craik C, Stroud R (2002) Anisotropic dynamics of the je-2147-HIV protease complex: drug resistance and thermodynamic binding mode examined in a 1.09 a structure. Biochemistry 41:4582CrossRefPubMedGoogle Scholar
  41. Roux B, Karplus M (1988) The normal modes of the gramicidin-A dimer channel. Biophys J 53(3):297–309CrossRefPubMedGoogle Scholar
  42. Sen TZ, Fend Y, Garcia JV, Kolczkowski A, Jernigan RL (2006) The extent of cooperativity of protein motions observed with elastic network models is similar for atomic and coarser-grained models. J Chem Theo Comp 2(3):696–704CrossRefGoogle Scholar
  43. Soheilifard R, Makarov DE, Rodin GJ (2008) Critical evaluation of simple network models of protein dynamics and their comparison with crystallographic b-factors. Phys Biol 5:026,008CrossRefGoogle Scholar
  44. Tama F, Brooks I CL (2002) The mechanism and pathway of pH induced swelling in cowpea chlorotic mottle virus. J Mol Biol 318(3):733–747Google Scholar
  45. Tama F, Gadea F, Marques O (2000) A building block approach for determining low-frequency normal modes of macromolecules. Proteins Struct Func Genet 41:1–7CrossRefGoogle Scholar
  46. Tirion M (1996) Large amplitude elastic motions in proteins from a single-parameter, atomic analysis. Phys Rev Lett 77(9):1905–1908Google Scholar

Copyright information

© European Biophysical Societies' Association 2009

Authors and Affiliations

  1. 1.Bioinformatics and Theoretical Biology Group, Department of BiologyTechnische Universität DarmstadtDarmstadtGermany

Personalised recommendations