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Energetic basis for drug resistance of HIV-1 protease mutants against amprenavir

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Abstract

Amprenavir (APV) is a high affinity (0.15 nM) HIV-1 protease (PR) inhibitor. However, the affinities of the drug resistant protease variants V32I, I50V, I54V, I54M, I84V and L90M to amprenavir are decreased 3 to 30-fold compared to the wild-type. In this work, the popular molecular mechanics Poisson-Boltzmann surface area method has been used to investigate the effectiveness of amprenavir against the wild-type and these mutated protease variants. Our results reveal that the protonation state of Asp25/Asp25′ strongly affects the dynamics, the overall affinity and the interactions of the inhibitor with individual residues. We emphasize that, in contrast to what is often assumed, the protonation state may not be inferred from the affinities but requires pKa calculations. At neutral pH, Asp25 and Asp25′ are ionized or protonated, respectively, as suggested from pKa calculations. This protonation state was thus mainly considered in our study. Mutation induced changes in binding affinities are in agreement with the experimental findings. The decomposition of the binding free energy reveals the mechanisms underlying binding and drug resistance. Drug resistance arises from an increase in the energetic contribution from the van der Waals interactions between APV and PR (V32I, I50V, and I84V mutant) or a rise in the energetic contribution from the electrostatic interactions between the inhibitor and its target (I54M and I54V mutant). For the V32I mutant, also an increased free energy for the polar solvation contributes to the drug resistance. For the L90M mutant, a rise in the van der Waals energy for APV-PR interactions is compensated by a decrease in the polar solvation free energy such that the net binding affinity remains unchanged. Detailed understanding of the molecular forces governing binding and drug resistance might assist in the design of new inhibitors against HIV-1 PR variants that are resistant against current drugs.

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References

  1. Darke PL, Leu CT, Davis LJ, Heimbach JC, Diehl RE, Hill WS, Dixon RA, Sigal IS (1989) Human immunodeficiency virus protease. Bacterial expression and characterization of the purified aspartic protease. J Biol Chem 264:2307–2312

    CAS  Google Scholar 

  2. Seelmeir S, Schmidt H, Turk V, VonDer Helm K (1988) Human immunodeficiency virus has an aspartic-type protease that can be inhibited by pepstatin A. Proc Natl Acad Sci USA 85:6612–6616

    Article  Google Scholar 

  3. Mous J, Heimer EP, Le Grice SJJ (1988) Processing protease and reverse transcriptase from human immunodeficiency virus type I polyprotein in Escherichia coli. J Virol 62:1433–1436

    CAS  Google Scholar 

  4. Hornak V, Okur A, Rizzo RC, Simmerling C (2006) HIV-1 protease flaps spontaneously open and reclose in molecular dynamics simulations. Proc Natl Acad Sci USA 103:915–920

    Article  CAS  Google Scholar 

  5. Chang CA, Trylska J, Tozzini V, McCammon JA (2007) Binding pathways of ligands to HIV-1 protease: corase-grained and atomistic simulations. Chem Biol Drug Des 69:5–13

    Article  CAS  Google Scholar 

  6. Wood E, Hogg RS, Yip B, Moore D, Harringan PR, Montaner JS (2007) Superior virological response to boosted protease inhibitor-based highly active antiretroviral therapy in an observational treatment programme. HIV Med 8:80–85

    Article  CAS  Google Scholar 

  7. Walker BD, Burton DR (2008) Toward an AIDS vaccine. Science 320:760–764

    Article  CAS  Google Scholar 

  8. Foulkes-Murzycki JE, Scott WR, Schiffer CA (2007) Hydrophobic sliding: a possible mechanism for drug resistance in human immunodeficiency virus type 1 protease. Structure 15:225–233

    Article  CAS  Google Scholar 

  9. Shafer RW, Schapiro JM (2008) HIV-1 drug resistance mutations: an updated framework for the second decade of HAART. AIDS Rev 10:67–84

    Google Scholar 

  10. Vergne L, Peeters M, Mpoudi-Ngole E, Bourgeois A, Liegeois F, Toure-Kane C, Mboup S, Mulanga-Kabeya C, Saman E, Jourdan J, Reynes J, Delaporte E (2000) Genetic diversity of protease and reverse transcriptase sequences in non-subtype-B human immunodeficiency virus type 1 strains: evidence of many minor drug resistance mutations in treatment-naive patients. J Clin Microbiol 38:3919–3925

    CAS  Google Scholar 

  11. Shen C-H, Wang Y-F, Kovalevsky AY, Harrison RW, Weber IT (2010) Amprenavir complexes with HIV-1 protease and its drug-resistant mutants altering hydrophobic clusters. FEBS J 277:3699–3714

    Article  CAS  Google Scholar 

  12. Brik A, Wong CH (2003) HIV-1 protease: mechanism and drug discovery. Org Biomol Chem 1:5–14

    Article  CAS  Google Scholar 

  13. Smith R, Brereton IM, Chai RY, Kent SBH (1996) Ionization states of the catalytic residues in HIV-1 protease. Nat Struct Biol 3:946–950

    Article  CAS  Google Scholar 

  14. Chen J, Yang M, Hu G, Shi S, Yi C, Zhang Q (2009) Insights into the functional role of protonation states in the HIV-1 protease-BEA369 complex: molecular dynamics simulations and free energy calculations. J Mol Model 15:1245–1252

    Article  CAS  Google Scholar 

  15. Chen X, Tropsha A (1995) Relative binding free energies of peptide inhibitors of HIV-1 protease: the influence of the active site protonation state. J Med Chem 38:42–48

    Article  CAS  Google Scholar 

  16. Wittayaranakul K, Aruksakunwong O, Saen-oon S, Chantratita W, Parasuk V, Sompornpisut P, Hannongbua S (2005) Insights into saquinavir resistance in the G48V HIV-1 protease: quantum calculations and molecular dynamic simulations. Biophys J 88:867–879

    Article  Google Scholar 

  17. Wittayanarakul K, Hannongbua S, Feig M (2008) Accurate prediction of protonation state as a prerequisite for reliable MM-PB(GB)SA binding free energy calculations of HIV-1 protease inhibitors. J Comput Chem 29:673–685

    Article  CAS  Google Scholar 

  18. Yamazaki T, Nicholson LK, Wingfield P, Stahl SJ, Kaufman JD, Eyermann CJ, Hodge CN, Lam PYS, Torchia DA (1994) NMR and X-ray evidence that the HIV protease catalytic aspartyl groups are protonated in the complex formed by the protease and a non-peptide cyclic urea-based inhibitor. J Am Chem Soc 116:10791–10792

    Article  CAS  Google Scholar 

  19. Wang W, Kollman PA (2000) Free energy calculations on dimer stability of the HIV protease using molecular dynamics and a continuum solvent model. J Mol Biol 303:567–582

    Article  CAS  Google Scholar 

  20. Chen J, Zhang S, Liu X, Zhang Q (2010) Insights into drug resistance of mutations D30N and I50V to HIV-1 protease inhibitor TMC-114: free energy calculation and molecular dynamic simulation. J Mol Model 16:459–468

    Article  Google Scholar 

  21. Clavel F, Hance AJ (2004) HIV drug resistance. New Engl J Med 350:1023–1035

    CAS  Google Scholar 

  22. Wu TD, Schiffer CA, Gonzales MJ, Taylor J, Kantor R, Chou S, Israelski D, Zolopa AR, Fessel WJ, Shafer RW (2003) Mutation patterns and structural correlates in human immunodeficiency virus type 1 protease following different protease inhibitor treatments. J Virol 77:4836–4847

    Article  CAS  Google Scholar 

  23. Johnson VA, Brun-Vezinet F, Clotet B, Gunthard HF, Kuritzkes DR, Pillay D, Schapiro JM, Richman DD (2008) Update of the drug resistance mutations in HIV-1. Top HIV Med 16:138–145

    Google Scholar 

  24. Wang W, Kollman PA (2001) Computational study of protein specificity: the molecular basis of HIV-1 protease drug resistance. Proc Natl Acad Sci USA 98:14937–14942

    Article  CAS  Google Scholar 

  25. Kollman PA (1993) Free energy calculations: applications to chemical and biochemical phenomena. Chem Rev 93:2395–2417

    Article  CAS  Google Scholar 

  26. Lybrand T, McCammon JA, Wipff G (1986) Theoretical calculation of relative binding affinity in host-guest systems. Proc Natl Acad Sci USA 83:833–835

    Article  CAS  Google Scholar 

  27. Jayaram B, Sprous D, Young MA, Beveridge DL (1998) Free energy analysis of the conformational preferences of A and B forms of DNA in solution. J Am Chem Soc 120:10629–10633

    Article  CAS  Google Scholar 

  28. Vorobjev YN, Almagro JC, Hermans J (1998) Discrimination between native and intentionally misfolded conformations of proteins: ES/IS, a new method for calculating conformational free energy that uses both dynamics simulations with an explicit solvent and an implicit solvent continuum model. Proteins 32:399–413

    Article  CAS  Google Scholar 

  29. Kollman PA, Massova I, Reyes C, Kuhn B, Huo S, Chong L, Lee M, Lee T, Duan Y, Wang W, Donini O, Cieplak P, Srinivasan J, Case DA, Cheatham TE (2000) Calculating structures and free energies of complex molecules: combining molecular mechanics and continuum models. Acc Chem Res 33:889–897

    Article  CAS  Google Scholar 

  30. Kuhn B, Kollman PA (2000) Binding of a diverse set of ligands to avidin and streptavidin: an accurate quantitative prediction of their relative affinities by a combination of molecular mechanics and continuum solvent models. J Med Chem 43:3786–3791

    Article  CAS  Google Scholar 

  31. Rastelli G, Rio AD, Degliesposti G, Sgobba M (2010) Fast and accurate predictions of binding free energies using MM-PBSA and MM-GBSA. J. Comput. Chem. 31:797–810

    CAS  Google Scholar 

  32. Reyes CM, Kollman PA (2000) Investigating the binding specificity of U1A-RNA by computational mutagenesis. J Mol Biol 295:1–6

    Article  CAS  Google Scholar 

  33. Reyes CM, Kollman PA (2000) Structure and thermodynamics of RNA-protein binding: using molecular dynamics and free energy analyses to calculate the free energies of binding and conformational change. J Mol Biol 297:1145–1158

    Article  CAS  Google Scholar 

  34. Chen X, Weber IT, Harrison RW (2004) Molecular dynamics simulations of 14 HIV protease mutants in complexes with indinavir. J Mol Model 10:373–381

    Article  CAS  Google Scholar 

  35. Hou T, McLaughlin WA, Wang W (2007) Evaluating the potency of HIV-1 protease drugs to combat resistance. Proteins 71:1163–1174

    Article  Google Scholar 

  36. Stoica I, Sadiq SK, Coveney PV (2008) Rapid and accurate prediction of binding free energies for saquinavir-bound HIV-1 proteases. J Am Chem Soc 130:2639–2648

    Article  CAS  Google Scholar 

  37. Hu GD, Zhu T, Zhang SL, Wang D, Zhang QG (2010) Some insights into mechanism for binding and drug resistance of wild type and I50V V82A and I84V mutations in HIV-1 protease with GRL-98065 inhibitor from molecular dynamic simulations. Eur J Med Chem 45:227–235

    Article  CAS  Google Scholar 

  38. Cai Y, Schiffer CA (2010) Decomposing the energetic impact of drug resistant mutations in HIV-1 protease on binding DRV. J Chem Theory Comput 6:1358–1368

    Article  CAS  Google Scholar 

  39. Hou T, Yu R (2007) Molecular dynamics and free energy studies on the wild-type and double mutant HIV-1 protease complexed with amprenavir and two amprenavir-related inhibitors: mechanism for binding and drug resistance. J Med Chem 50:1177–1188

    Article  CAS  Google Scholar 

  40. Wang J, Morin P, Wang W, Kollman PA (2001) Use of MM-PBSA in reproducing the binding free energies to HIV-1 RT of TIBO derivatives and predicting the binding mode to HIV-1 RT of efavirenz by docking and MM-PBSA. J Am Chem Soc 123:5221–5230

    Article  CAS  Google Scholar 

  41. Worch R, Bökel C, Höfinger S, Schwille P, Weidemann T (2010) Focus on composition and interaction potential of single-pass transmembrane domains. Proteomics 10:4196–4208

    Article  CAS  Google Scholar 

  42. Kar P, Seel M, Weidemann T, Höfinger S (2009) Theoretical mimicry of biomembranes. FEBS Lett 583:1909–1915

    Article  CAS  Google Scholar 

  43. Hornak V, Abel R, Okur A, Strockbine B, Roitberg A, Simmerling C (2006) Comparison of multiple amber force fields and development of improved protein backbone parameters. Proteins 65:712–725

    Article  CAS  Google Scholar 

  44. Wang J, Wolf RM, Caldwell JW, Kollman PA, Case DA (2004) Development and testing of a general AMBER force field. J Comput Chem 25:1157–1174

    Article  CAS  Google Scholar 

  45. Jakalian A, Jack DB, Bayly CI (2002) Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation. J Comput Chem 23:1623–1641

    Article  CAS  Google Scholar 

  46. Wang J, Wang W, Kollman PA, Case DA (2006) Automatic atom type and bond type perception in molecular mechanical calculations. J Mol Gra Model 25:247–260

    Article  Google Scholar 

  47. Case DA, Cheatham T, Darden T, Gohlke H, Luo R, Merz KM Jr, Onufriev A, Simmerling C, Wang B, Woods R (2005) The Amber biomolecular simulation programs. J Computat Chem 26:1668–1688

    Article  CAS  Google Scholar 

  48. Kar P, Lipowsky R, Knecht V (2011) Importance of polar solvation for cross-reactivity of antibody and its variants with steroids. J Phys Chem B 115:7661–7669

    Article  CAS  Google Scholar 

  49. Jorgensen WL, Chandrasekar J, Madura JD, Impey R, Klein K (1983) Comparison of simple potential functions for simulating liquid water. J Chem Phys 79:926–935

    Article  CAS  Google Scholar 

  50. Ryckaert J-P, Ciccotti G, Berendsen HJC (1977) Numerical integration of the cartesian equations of motion of a system with constraints: molecular dynamics of n-alkanes. J Comput Phys 23:327–341

    Article  CAS  Google Scholar 

  51. Darden T, York D, Pedersen L (1993) Particle mesh Ewald—an Nlog(N) method for Ewald sums in large systems. J Chem Phys 98:10089–10092

    Article  CAS  Google Scholar 

  52. Sitkoff D, Sharp KA, Honig B (1994) Accurate calculation of hydration free energies using macroscopic solvent models. J Phys Chem 98:1978–1988

    Article  CAS  Google Scholar 

  53. Weise J, Shenkin PS, Still WC (1999) Fast, approximate algorithm for detection of solvent-inaccessible atoms. J Comput Chem 20:217–230

    Article  Google Scholar 

  54. Swanson JM, Henchman RH, McCammon JA (2004) Revisiting free energy calculations: a theoretical connection to MM/PBSA and direct calculation of the association free energy. Biophys J 86:67–74

    Article  CAS  Google Scholar 

  55. Kongsted J, Ryde U (2009) An improved method to predict the entropy term with the MM/PBSA approach. J Comput Aided Mol Des 23:63–71

    Article  CAS  Google Scholar 

  56. Massova I, Kollman PA (1999) Computational alanine scanning to probe protein-protein interactions: a novel approach to evaluate binding free energies. J Am Chem Soc 36:8133–8143

    Article  Google Scholar 

  57. Gohlke H, Kiel C, Case DA (2003) Insights into protein-protein binding by free energy calculation and free energy decomposition for the Ras–Raf and Ras–RalGDS complexes. J Mol Biol 330:891–913

    Article  CAS  Google Scholar 

  58. Li H, Robertson AD, Jensen JH (2005) Very fast empirical prediction and interpretation of protein pKa values. Proteins 61:704–721

    Article  CAS  Google Scholar 

  59. Bas DC, Rogers DM, Jensen JH (2008) Very fast prediction and rationalization of pKa values for protein–ligand complexes. Proteins 73:765–783

    Article  CAS  Google Scholar 

  60. Davies MN, Toseland CP, Moss DS, Flower DR (2006) Benchmarking pKa prediction. BMC Biochem 7:18

    Article  Google Scholar 

  61. Khandogin J, Brooks CL III (2005) Constant pH molecular dynamics with proton tautomerism. Biophys J 89:141–157

    Article  CAS  Google Scholar 

  62. Lee AC, Crippen GM (2009) Predicting pKa J. Chem Inf Model 49:2013–2033

    Article  CAS  Google Scholar 

  63. Adachi M, Ohhara T, Kurihara K, Tamada T, Honjo E, Okazaki N, Arai S, Shoyama Y, Kimura K, Maatsumura H, Sugiyama S, Adachi H, Takano K, Mori Y, Hidaka K, Kimura T, Hayashi Y, Kiso Y, Kuroki R (2009) Structure of HIV-1 protease in complex with potent inhibitor KNI-272 determined by high-resolution X-ray and neutron crystallography. Proc Natl Acad Sci USA 106:4641–4646

    Article  CAS  Google Scholar 

  64. Suguna K, Padlan EA, Smith CW, Carlson WD, Davies DR (1987) Binding of a reduced peptide inhibitor to the aspartic proteinase from Rhizopus chinensis: implications for a mechanism of action. Proc Natl Acad Sci U S A 84:7009–7013

    Article  CAS  Google Scholar 

  65. Chong LT, Duan Y, Wang L, Massova I, Kollman PA (1999) Molecular dynamics and free-energy calculations applied to affinity maturation in antibody 48G7. Proc Natl Acad Sci USA 96:14330–14335

    Article  CAS  Google Scholar 

  66. Knecht V (2010) Model amyloid peptide B18 monomer and dimer studied by replica exchange molecular dynamics simulations. J Phys Chem B 114:12701–12707

    Article  CAS  Google Scholar 

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Acknowledgements

The work was supported by the Federal Ministry of Education and Research (BMBF), Germany. The authors thank Reinhard Lipowsky for support. P. K. is thankful to Dr. Siegfried Höfinger, University of Bologna, Italy for discussion.

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Kar, P., Knecht, V. Energetic basis for drug resistance of HIV-1 protease mutants against amprenavir. J Comput Aided Mol Des 26, 215–232 (2012). https://doi.org/10.1007/s10822-012-9550-5

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