Single Active Site Mutation Causes Serious Resistance of HIV Reverse Transcriptase to Lamivudine: Insight from Multiple Molecular Dynamics Simulations

Abstract

Molecular dynamics simulations, binding free energy calculations, principle component analysis (PCA), and residue interaction network analysis were employed in order to investigate the molecular mechanism of M184I single mutation which played pivotal role in making the HIV-1 reverse transcriptase (RT) totally resistant to lamivudine. Results showed that single mutations at residue 184 of RT caused (1) distortion of the orientation of lamivudine in the active site due to the steric conflict between the oxathiolane ring of lamivudine and the side chain of beta-branched amino acids Ile at position 184 which, in turn, perturbs inhibitor binding, (2) decrease in the binding affinity by (~8 kcal/mol) when compared to the wild-type, (3) variation in the overall enzyme motion as evident from the PCA for both systems, and (4) distortion of the hydrogen bonding network and atomic interactions with the inhibitor. The comprehensive analysis presented in this report can provide useful information for understanding the drug resistance mechanism against lamivudine. The results can also provide some potential clues for further design of novel inhibitors that are less susceptible to drug resistance.

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References

  1. 1.

    Morah, E. U. (2007). Are people aware of their HIV-positive status responsible for driving the epidemic in subsaharan Africa? The case of Malawi. Development Policy Review, 25(2), 215–242.

    Article  Google Scholar 

  2. 2.

    Pani, A., Loi, A. G., Mura, M., Marceddu, T., La Colla, P., & Marongiu, M. E. (2002). Targeting HIV: Old and new players. Current Drug Target Infectious Disorders, 2, 17–32.

    CAS  Article  PubMed  Google Scholar 

  3. 3.

    Esposito, F., Corona, A., & Tramontano, E. (2012). HIV-1 reverse transcriptase still remains a new drug target: Structure function, classical inhibitors, and new inhibitors with innovative mechanisms of actions. Molecular Biology International, 2012, 1–23.

    Article  Google Scholar 

  4. 4.

    Schinazi, R. F., Hernandez-Santiago, B. I., & Hurwitz, S. J. (2006). Pharmacology of current and promising nucleosides for the treatment of human immunodeficiency viruses (vol 71, pg 322, 2006). Antiviral Research, 72, 256.

    CAS  Article  Google Scholar 

  5. 5.

    Ilina, T., LaBarge, K., Sarafianos, S. G., Ishima, R., & Parniak, M. A. (2012). Inhibitors of HIV-1 reverse transcriptase—associated ribonuclease H activity. Biology, 1, 521–541.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  6. 6.

    Vivet-Boudou, V., Didierjean, J., Isel, C., & Marquet, R. (2006). Nucleoside and nucleotide inhibitors of HIV-1 replication. Cellular and Molecular Life Sciences, 63, 163–186.

    CAS  Article  PubMed  Google Scholar 

  7. 7.

    Bauman, J. D., Das, K., Ho, W. C., Baweja, M., Himmel, D. M., Clark, A. D, Jr, et al. (2008). Crystal engineering of HIV-1 reverse transcriptase for structure-based drug design. Nucleic Acids Research, 36, 5083–5092.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  8. 8.

    Turner, D., Brenner, B., & Wainberg, M. A. (2003). Multiple effects of the M184V resistance mutation in the reverse transcriptase of human immunodeficiency virus type 1. Clinical and Diagnostic Laboratory Immunology, 10, 979–981.

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Ray, A. S. (2005). Intracellular interactions between nucleos(t)ide inhibitors of HIV reverse transcriptase. AIDS Reviews, 7(2), 113–125.

    PubMed  Google Scholar 

  10. 10.

    Hamers, R. L., Kityo, C., Sigaloff, K. C., & de Wit, T. F. R. (2013). Pretreatment HIV-1 drug resistance in Africa. Lancet Infectious Diseases, 13, 476.

    Article  PubMed  Google Scholar 

  11. 11.

    Wainberg, M. A., & Turner, D. (2004). Resistance issues with new nucleoside/nucleotide backbone options. JAIDS Journal of Acquired Immune Deficiency Syndromes, 37, S36–S43.

    CAS  Article  PubMed  Google Scholar 

  12. 12.

    Gao, H. Q., Boyer, P. L., Sarafianos, S. G., Arnold, E., & Hughes, S. H. (2000). The role of steric hindrance in 3TC resistance of human immunodeficiency virus type-1 reverse transcriptase. Journal of Molecular Biology, 300, 403–418.

    CAS  Article  PubMed  Google Scholar 

  13. 13.

    Sarafianos, S. G., Das, K., Clark, A. D., Ding, J. P., Boyer, P. L., Hughes, S. H., & Arnold, E. (1999). Lamivudine (3TC) resistance in HIV-1 reverse transcriptase involves steric hindrance with beta-branched amino acids. Proceedings of the National Academy of Sciences of the United States of America, 96, 10027–10032.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  14. 14.

    Purohit, R. (2014). Role of ELA region in auto-activation of mutant KIT receptor: A molecular dynamics simulation insight. Journal of Biomolecular Structure and Dynamics, 32, 1033–1046.

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Bahareh, H., Govender, T., Maguire, G. E. M., Soliman, M. E. S., & Kruger, H. G. (2013). Integrated approach to structure-based enzymatic drug design: molecular modeling, spectroscopy, and experimental bioactivity. Chemical Reviews,. doi:10.1021/cr300314q.

    Google Scholar 

  16. 16.

    Purohit, R., Rajendran, V., & Sethumadhavan, R. (2011). Studies on adaptability of binding residues and flap region of TMC-114 resistance HIV-1 protease mutants. Journal of Biomolecular Structure and Dynamics, 29, 137–152.

    CAS  Article  PubMed  Google Scholar 

  17. 17.

    Rajendran, V., Purohit, R., & Sethumadhavan, R. (2012). In silico investigation of molecular mechanism of laminopathy caused by a point mutation (R482W) in lamin A/C protein. Amino Acids, 43, 603–615.

    CAS  Article  PubMed  Google Scholar 

  18. 18.

    Purohit, R., Rajendran, V., & Sethumadhavan, R. (2011). Relationship between mutation of serine residue at 315th position in M. tuberculosis catalase-peroxidase enzyme and isoniazid susceptibility: An in silico analysis. Journal of Molecular Modeling, 17, 869–877.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Balu, K., Rajendran, V., Sethumadhavan, R., & Purohit, R. (2013). Investigation of binding phenomenon of NSP3 and p130Cas mutants and their effect on cell signalling. Cell Biochemistry and Biophysics, 67, 623–633.

    CAS  Article  PubMed  Google Scholar 

  20. 20.

    Rajendran, V., & Sethumadhavan, R. (2014). Drug resistance mechanism of PncA in Mycobacterium tuberculosis. Journal of Biomolecular Structure and Dynamics, 32, 209–221.

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Aruksakunwong, O., Wolschann, P., Hannongbua, S., & Sompornpisut, P. (2006). Molecular dynamic and free energy studies of primary resistance mutations in HIV-1 protease-ritonavir complexes. Journal of Chemical Information and Modeling, 46, 2085–2092.

    CAS  Article  PubMed  Google Scholar 

  22. 22.

    Hou, T. J., & 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. Journal of Medicinal Chemistry, 50, 1177–1188.

    CAS  Article  PubMed  Google Scholar 

  23. 23.

    Stoica, I., Sadiq, S. K., & Coveney, P. V. (2008). Rapid and accurate prediction of binding free energies for saquinavir-bound HIV-1 proteases. Journal of the American Chemical Society, 130, 2639–2648.

    CAS  Article  PubMed  Google Scholar 

  24. 24.

    Zhou, Z. G., Madrid, M., Evanseck, J. D., & Madura, J. D. (2005). Effect of a bound non-nucleoside RT inhibitor on the dynamics of wild-type and mutant HIV-1 reverse transcriptase. Journal of the American Chemical Society, 127, 17253–17260.

    CAS  Article  PubMed  Google Scholar 

  25. 25.

    Xue, W. W., Qi, J., Yang, Y., Jin, X. J., Liu, H. X., & Yao, X. J. (2012). Understanding the effect of drug-resistant mutations of HIV-1 intasome on raltegravir action through molecular modeling study. Molecular BioSystems, 8, 2135–2144.

    CAS  Article  PubMed  Google Scholar 

  26. 26.

    Chachra, R., & Rizzo, R. C. (2008). Origins of resistance conferred by the R292K neuraminidase mutation via molecular dynamics and free energy calculations. Journal of Chemical Theory and Computation, 4, 1526–1540.

    CAS  Article  PubMed  Google Scholar 

  27. 27.

    Liu, H. X., Yao, X. J., Wang, C. Q., & Han, J. A. (2010). In silico identification of the potential drug resistance sites over 2009 influenza A (H1N1) virus neuraminidase. Molecular Pharmaceutics, 7, 894–904.

    CAS  Article  PubMed  Google Scholar 

  28. 28.

    Guo, Z. Y., Prongay, A., Tong, X., Fischmann, T., Bogen, S., Velazquez, F., et al. (2006). Computational study of the effects of mutations A156T, D168V, and D168Q on the binding of HCV protease inhibitors. Journal of Chemical Theory and Computation, 2, 1657–1663.

    CAS  Article  PubMed  Google Scholar 

  29. 29.

    Pan, D. B., Xue, W. W., Zhang, W. Q., Liu, H. X., & Yao, X. J. (2012). Understanding the drug resistance mechanism of hepatitis C virus NS3/4A to ITMN-191 due to R155K, A156V, D168A/E mutations: A computational study. Biochimica Et Biophysica Acta General Subjects, 1820, 1526–1534.

    CAS  Article  Google Scholar 

  30. 30.

    Cheng, X. L., Cui, G. L., Hornak, V., & Sinnnerling, C. (2005). Modified replica exchange simulation methods for local structure refinement. Journal of Physical Chemistry B, 109, 8220–8230.

    CAS  Article  Google Scholar 

  31. 31.

    Affentranger, R., Tavernelli, I., & Di Iorio, E. E. (2006). A novel Hamiltonian replica exchange MD protocol to enhance protein conformational space sampling. Journal of Chemical Theory and Computation, 2, 217–228.

    CAS  Article  PubMed  Google Scholar 

  32. 32.

    Okur, A., Wickstrom, L., Layten, M., Geney, R., Song, K., Hornak, V., & Simmerling, C. (2006). Improved efficiency of replica exchange simulations through use of a hybrid explicit/implicit solvation model. Journal of Chemical Theory and Computation, 2, 420–433.

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Liu, P., Kim, B., Friesner, R. A., & Berne, B. J. (2005). Replica exchange with solute tempering: A method for sampling biological systems in explicit water. Proceedings of the National Academy of Sciences of the United States of America, 102, 13749–13754.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  34. 34.

    Maisuradze, G. G., Liwo, A., & Scheraga, H. A. (2009). Principal component analysis for protein folding dynamics. Journal of Molecular Biology, 385, 312–329.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  35. 35.

    Thomas, J. R., Gedeon, P. C., Grant, B. J., & Madura, J. D. (2012). LeuT conformational sampling utilizing accelerated molecular dynamics and principal component analysis. Biophysical Journal, 103, L01–L03.

    Article  Google Scholar 

  36. 36.

    Amadei, A., Linssen, A. B., de Groot, B. L., van Aalten, D. M., & Berendsen, H. J. (1996). An efficient method for sampling the essential subspace of proteins. Journal of Biomolecular Structure and Dynamics, 13, 615–625.

    CAS  Article  PubMed  Google Scholar 

  37. 37.

    van Aalten, D. M., Findlay, J. B., Amadei, A., & Berendsen, H. J. (1995). Essential dynamics of the cellular retinol-binding protein—Evidence for ligand-induced conformational changes. Protein Engineering Design and Selection, 8, 1129–1135.

    Article  Google Scholar 

  38. 38.

    Amadei, A., Linssen, A. B. M., & Berendsen, H. J. C. (1993). Essential dynamics of proteins. Proteins: Structure Function, and Bioinformatics, 17, 412–425.

    CAS  Article  Google Scholar 

  39. 39.

    Word, J. M., Lovell, S. C., LaBean, T. H., Taylor, H. C., Zalis, M. E., Presley, B. K., et al. (1999). Visualizing and quantifying molecular goodness-of-fit: Small-probe contact dots with explicit hydrogen atoms. Journal of Molecular Biology, 285, 1711–1733.

    CAS  Article  PubMed  Google Scholar 

  40. 40.

    Case, D. A. (1994). Normal-mode analysis of protein dynamics. Current Opinion in Structural Biology, 4, 285–290.

    CAS  Article  Google Scholar 

  41. 41.

    Brooks, B., & Karplus, M. (1985). Normal-modes for specific motions of macromolecules—Application to the Hinge-Bending mode of lysozyme. Proceedings of the National Academy of Sciences of the United States of America, 82, 4995–4999.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  42. 42.

    Laine, E., de Beauchene, I. C., Perahia, D., Auclair, C., & Tchertanov, L. (2011). Mutation D816V alters the internal structure and dynamics of c-KIT receptor cytoplasmic region: Implications for dimerization and activation mechanisms. PLoS Computational Biology, 7(6), e1002068–e1002068.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  43. 43.

    Teodoro, M. L., Phillips, G. N., & Kavraki, L. E. (2003). Understanding protein flexibility through dimensionality reduction. Journal of Computational Biology, 10, 617–634.

    CAS  Article  PubMed  Google Scholar 

  44. 44.

    Yang, L., Song, G., Carriquiry, A., & Jernigan, R. L. (2008). Close correspondence between the motions from principal component analysis of multiple HIV-1 protease structures and elastic network modes. Structure, 16, 321–330.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  45. 45.

    del Sol, A., Fujihashi, H., Amoros, D., & Nussinov, R. (2006). Residues crucial for maintaining short paths in network communication mediate signaling in proteins. Molecular Systems Biology, 2. doi:10.1038/msb4100063.

  46. 46.

    Welsch, C., Schweizer, S., Shimakami, T., Domingues, F. S., Kim, S., Lemon, S. M., & Antes, I. (2012). Ketoamide resistance and hepatitis C virus fitness in Val55 variants of the NS3 serine protease. Antimicrobial Agents and Chemotherapy, 56, 1907–1915.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Welsch, C., Domingues, F. S., Susser, S., Antes, I., Hartmann, C., Mayr, G., et al. (2008). Molecular basis of telaprevir resistance due to V36 and T54 mutations in the NS3-4A protease of the hepatitis C virus. Genome Biology, 9, R16.

    Article  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Xue, W. W., Jin, X. J., Ning, L. L., Wang, M. X., Liu, H. X., & Yao, X. J. (2013). Exploring the molecular mechanism of cross-resistance to HIV-1 integrase strand transfer inhibitors by molecular dynamics simulation and residue interaction network analysis. Journal of Chemical Information and Modeling, 53, 210–222.

    CAS  Article  PubMed  Google Scholar 

  49. 49.

    Doncheva, N. T., Klein, K., Domingues, F. S., & Albrecht, M. (2011). Analyzing and visualizing residue networks of protein structures. Trends in Biochemical Sciences, 36, 179–182.

    CAS  Article  PubMed  Google Scholar 

  50. 50.

    Doncheva, N. T., Assenov, Y., Domingues, F. S., & Albrecht, M. (2012). Topological analysis and interactive visualization of biological networks and protein structures. Nature Protocols, 7, 670–685.

    CAS  Article  PubMed  Google Scholar 

  51. 51.

    Ahmed, S. M., Kruger, H. G., Govender, T., Maguire, G. E., Sayed, Y., Ibrahim, M. A., et al. (2013). Comparison of the molecular dynamics and calculated binding free energies for nine FDA-approved HIV-1 PR drugs against subtype B and C-SA HIV PR. Chemical Biology and Drug Design, 81, 208–218.

    CAS  Article  PubMed  Google Scholar 

  52. 52.

    Soliman, M. E. S. (2013). A hybrid structure/pharmacophore-based virtual screening approach to design potential leads: A computer-aided design of south African HIV-1 subtype C protease inhibitors. Drug Development Research, 74, 283–295.

    CAS  Article  Google Scholar 

  53. 53.

    Kanibolotsky, D. S., Novosyl’na, O. V., Abbott, C. M., Negrutskii, B. S., & El’skaya, A. V. (2008). Multiple molecular dynamics simulation of the isoforms of human translation elongation factor 1A reveals reversible fluctuations between “open” and “closed” conformations and suggests specific for eEF1A1 affinity for Ca(2+)-calmodulin. BMC Structural Biology, 8(1), 4.

    Article  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Goetz, A. W., Williamson, M. J., Xu, D., Poole, D., Le Grand, S., & Walker, R. C. (2012). Routine microsecond molecular dynamics simulations with AMBER on GPUs. 1. Generalized born. Journal of Chemical Theory and Computation, 8, 1542–1555.

    Article  Google Scholar 

  55. 55.

    Salomon-Ferrer, R., Goetz, A. W., Poole, D., Le Grand, S., & Walker, R. C. (2013). Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit solvent particle mesh Ewald. Journal of Chemical Theory and Computation, 9, 3878–3888.

    CAS  Article  PubMed  Google Scholar 

  56. 56.

    Salomon-Ferrer, R., Case, D. A., & Walker., R. C. (2013). An overview of the Amber biomolecular simulation package. WIREs Computational Molecular Science3, 198–210.

    CAS  Article  Google Scholar 

  57. 57.

    Case, D. A., Darden, T. A., Cheatham, III, T. E., Simmerling, C. L., Wang, J., Duke, R. E., et al. (2012). AMBER 12. San Francisco: University of California.

    Google Scholar 

  58. 58.

    Lindorff-Larsen, K., Piana, S., Palmo, K., Maragakis, P., Klepeis, J. L., Dror, R. O., & Shaw, D. E. (2010). Improved side-chain torsion potentials for the Amber ff99SB protein force field. Proteins Structure Function and Bioinformatics, 78, 1950–1958.

    CAS  Google Scholar 

  59. 59.

    Cieplak, P., Cornell, W. D., Bayly, C., & Kollman, P. A. (1995). Application of the multimolecule and multiconformational RESP methodology to biopolymers: Charge derivation for DNA, and proteins. Journal of Computational Chemistry, 16, 1357–1377.

    CAS  Article  Google Scholar 

  60. 60.

    Frisch, M. J., Trucks, G. W., Schlegel, H. B., Scuseria, G. E., Robb, M. A., Cheeseman, J. R., et al. (2009). Gaussian 09, Revision D.01. Wallingford, CT: Gaussian, Inc.

  61. 61.

    Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., & Klein, M. L. (1983). Comparison of simple potential functions for simulating liquid water. Journal of Chemical Physics, 79, 926–935.

    CAS  Article  Google Scholar 

  62. 62.

    Essmann, U., Perera, L., Berkowitz, M. L., Darden, T., Lee, H., & Pedersen, L. G. (1995). A smooth particle mesh Ewald method. Journal of Chemical Physics, 103, 8577–8593.

    CAS  Article  Google Scholar 

  63. 63.

    Ryckaert, J. P., Giovanni, C., & Berendsen, H. J. C. (1977). Numerical integration of the cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes. Journal of Computational Physics, 23, 327–341.

    CAS  Article  Google Scholar 

  64. 64.

    Le Grand, S., Götz, A. W., & Walker, R. C. (2013). SPFP: Speed without compromise—A mixed precision model for GPU accelerated molecular dynamics simulations. Computer Physics Communications, 184, 374–380.

    Article  Google Scholar 

  65. 65.

    Berendsen, H. J. C., Postma, J. P. M., van Gunsteren, W. F., DiNola, A., & Haak, J. R. (1984). Molecular dynamics with coupling to an external bath. Journal of Chemical Physics, 81, 3684–3690.

    CAS  Article  Google Scholar 

  66. 66.

    Kollman, P. A., Massova, I., Reyes, C., Kuhn, B., Huo, S. H., Chong, L., et al. (2000). Calculating structures and free energies of complex molecules: Combining molecular mechanics and continuum models. Accounts of Chemical Research, 33, 889–897.

    CAS  Article  PubMed  Google Scholar 

  67. 67.

    Massova, I., & Kollman, P. A. (2000). Combined molecular mechanical and continuum solvent approach (MM-PBSA/GBSA) to predict ligand binding. Perspectives in Drug Discovery and Design, 18, 113–135.

    CAS  Article  Google Scholar 

  68. 68.

    Tsui, V., & Case, D. A. (2000). Theory and applications of the Generalized born solvation model in macromolecular simulations. Biopolymers, 56, 275–291.

    CAS  Article  PubMed  Google Scholar 

  69. 69.

    Onufriev, A., Bashford, D., & Case, D. A. (2000). Modification of the generalized Born model suitable for macromolecules. Journal of Physical Chemistry B, 104, 3712–3720.

    CAS  Article  Google Scholar 

  70. 70.

    Humphrey, W., Dalke, A., & Schulten, K. (1996). VMD: Visual molecular dynamics. Journal of Molecular Graphics and Modelling, 14, 33–38.

    CAS  Article  Google Scholar 

  71. 71.

    Bakan, A., Meireles, L. M., & Bahar, I. (2011). ProDy: Protein dynamics inferred from theory and experiments. Bioinformatics, 27, 1575–1577.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  72. 72.

    Shannon, P., Markiel, A., Ozier, O., Baliga, N. S., Wang, J. T., Ramage, D., et al. (2003). Cytoscape: A software environment for integrated models of biomolecular interaction networks. Genome Research, 13, 2498–2504.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  73. 73.

    Choo, H., Chong, Y., & Chu, C. K. (2003). The role of 2′,3′-unsaturation on the antiviral activity of anti-HIV nucleosides against 3TC-resistant mutant (M184V). Bioorganic and Medicinal Chemistry Letters, 13, 1993–1996.

    CAS  Article  PubMed  Google Scholar 

  74. 74.

    Diallo, K., Gotte, M., & Wainberg, M. A. (2003). Molecular impact of the M184V mutation in human immunodeficiency virus type 1 reverse transcriptase. Antimicrobial Agents and Chemotherapy, 47, 3377–3383.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

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Acknowledgments

The authors acknowledge the School of Health Sciences, UKZN, for financial support and the Center of High Performance Computing (CHPC, www.chpc.ac.za) for computational facilities. SB acknowledges the consultancy support from Open Source Drug Design and In Silico Molecules (www.insilicomolecule.org) community. RCW acknowledges funding from the National Science Foundation (NSF) through the Scientific Software Innovations Institutes program NSF SI2-SSE (NSF114876) and a fellowship from NVIDIA Inc.

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Correspondence to Mahmoud E. S. Soliman.

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Suri Moonsamy and Soumendranath Bhakat have contributed equally to this work.

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Moonsamy, S., Bhakat, S., Walker, R.C. et al. Single Active Site Mutation Causes Serious Resistance of HIV Reverse Transcriptase to Lamivudine: Insight from Multiple Molecular Dynamics Simulations. Cell Biochem Biophys 74, 35–48 (2016). https://doi.org/10.1007/s12013-015-0709-2

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Keywords

  • M184I mutation
  • HIV-RT
  • Lamivudine resistance
  • Binding free energy calculations
  • Multiple molecular dynamic simulations