215
Views
3
CrossRef citations to date
0
Altmetric
Research Article

Insights into effect of the Asp25/Asp25ʹ protonation states on binding of inhibitors Amprenavir and MKP97 to HIV-1 protease using molecular dynamics simulations and MM-GBSA calculations

ORCID Icon, , , , &
Pages 615-641 | Received 25 Mar 2021, Accepted 02 Jun 2021, Published online: 23 Jun 2021

References

  • A.S. Perelson, A.U. Neumann, M. Markowitz, J.M. Leonard, and D.D. Ho, HIV-1 dynamics in vivo: Virion clearance rate, infected cell life-span, and viral generation time, Science 271 (1996), pp. 1582–1586. doi:10.1126/science.271.5255.1582.
  • E.O. Freed, HIV-1 gag proteins: Diverse functions in the virus life cycle, Virology 251 (1998), pp. 1–15. doi:10.1006/viro.1998.9398.
  • T.W. Whitfield, D.A. Ragland, K.B. Zeldovich, and C.A. Schiffer, Characterizing protein–ligand binding using atomistic simulation and machine learning: Application to drug resistance in HIV-1 protease, J. Chem. Theory Comput. 16 (2020), pp. 1284–1299. doi:10.1021/acs.jctc.9b00781.
  • A. Wlodawer and J. Vondrasek, Inhibitors of HIV-1 protease: A major success of structure-assisted drug design, J. Annu. Rev. Biophys. Biomol. Struct. 27 (1998), pp. 249–284. doi:10.1146/annurev.biophys.27.1.249.
  • T.D. Wu, C.A. Schiffer, M.J. Gonzales, J. Taylor, R. Kantor, S. Chou, D. Israelski, A.R. Zolopa, W.J. Fessel, and R.W. Shafer, Mutation patterns and structural correlates in human immunodeficiency virus type 1 protease following different protease inhibitor treatments, J. Virol. 77 (2003), pp. 4836–4847. doi:10.1128/JVI.77.8.4836-4847.2003.
  • M.A. Navia, P.M.D. Fitzgerald, B.M. McKeever, C.-T. Leu, J.C. Heimbach, W.K. Herber, I.S. Sigal, P.L. Darke, and J.P. Springer, Three-dimensional structure of aspartyl protease from human immunodeficiency virus HIV-1, Nature 337 (1989), pp. 615–620. doi:10.1038/337615a0.
  • W.E. Harte and D.L. Beveridge, Prediction of the protonation state of the active site aspartyl residues in HIV-1 protease-inhibitor complexes via molecular dynamics simulation, J. Am. Chem. Soc. 115 (1993), pp. 3883–3886. doi:10.1021/ja00063a005.
  • T. Yamazaki, L.K. Nicholson, P. Wingfield, S.J. Stahl, J.D. Kaufman, C.J. Eyermann, C.N. Hodge, P.Y.S. Lam, and D.A. Torchia, 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 (1994), pp. 10791–10792. doi:10.1021/ja00102a057.
  • E.T. Baldwin, T.N. Bhat, S. Gulnik, B. Liu, I.A. Topol, Y. Kiso, T. Mimoto, H. Mitsuya, and J.W. Erickson, Structure of HIV-1 protease with KNI-272, a tight-binding transition-state analog containing allophenylnorstatine, Structure 3 (1995), pp. 581–590. doi:10.1016/S0969-2126(01)00192-7.
  • D.P. Oehme, R.T.C. Brownlee, and D.J.D. Wilson, Effect of atomic charge, solvation, entropy, and ligand protonation state on MM-PB(GB)SA binding energies of HIV protease, J. Comput. Chem. 33 (2012), pp. 2566–2580. doi:10.1002/jcc.23095.
  • J.L. Domínguez, T. Gossas, M. Carmen Villaverde, U. Helena Danielson, and F. Sussman, Experimental and ‘in silico’ analysis of the effect of pH on HIV-1 protease inhibitor affinity: Implications for the charge state of the protein ionogenic groups, Bioorg. Med. Chem. 20 (2012), pp. 4838–4847. doi:10.1016/j.bmc.2012.05.070.
  • G.-D. Hu, T. Zhu, S.-L. Zhang, D. Wang, and Q.-G. Zhang, 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 (2010), pp. 227–235. doi:10.1016/j.ejmech.2009.09.048.
  • R. Smith, I.M. Brereton, R.Y. Chai, and S.B.H. Kent, Ionization states of the catalytic residues in HIV-1 protease, Nat. Struct. Biol. 3 (1996), pp. 946–950. doi:10.1038/nsb1196-946.
  • Y.-X. Wang, D.I. Freedberg, T. Yamazaki, P.T. Wingfield, S.J. Stahl, J.D. Kaufman, Y. Kiso, and D.A. Torchia, Solution NMR evidence that the HIV-1 protease catalytic aspartyl groups have different ionization states in the complex formed with the asymmetric drug KNI-272, Biochemistry 35 (1996), pp. 9945–9950. doi:10.1021/bi961268z.
  • X. Chen and A. Tropsha, Relative binding free energies of peptide inhibitors of HIV-1 protease: The influence of the active site protonation state, J. Med. Chem. 38 (1995), pp. 42–48. doi:10.1021/jm00001a009.
  • K. Wittayanarakul, O. Aruksakunwong, S. Saen-oon, W. Chantratita, V. Parasuk, P. Sompornpisut, and S. Hannongbua, Insights into saquinavir resistance in the G48V HIV-1 protease: Quantum calculations and molecular dynamic simulations, Biophys. J. 88 (2005), pp. 867–879. doi:10.1529/biophysj.104.046110.
  • T. Hou and R. Yu, 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 (2007), pp. 1177–1188. doi:10.1021/jm0609162.
  • J. Chen, M. Yang, G. Hu, S. Shi, C. Yi, and Q. Zhang, 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 (2009), pp. 1245–1252. doi:10.1007/s00894-009-0452-y.
  • M. Yang, X. Jiang, and N. Jiang, Protonation state and free energy calculation of HIV-1 protease–inhibitor complex based on electrostatic polarisation effect, Mol. Phys. 112 (2014), pp. 1659–1669. doi:10.1080/00268976.2013.857050.
  • O. Gerlits, D.A. Keen, M.P. Blakeley, J.M. Louis, I.T. Weber, and A. Kovalevsky, Room temperature neutron crystallography of drug resistant HIV-1 protease uncovers limitations of x-ray structural analysis at 100 K, J. Med. Chem. 60 (2017), pp. 2018–2025. doi:10.1021/acs.jmedchem.6b01767.
  • J.B. Matthew, Electrostatic effects in proteins, Rev. Biophys. Biophys. Chem. 14 (1985), pp. 387–417. doi:10.1146/annurev.bb.14.060185.002131.
  • M.E. Davis and J.A. McCammon, Electrostatics in biomolecular structure and dynamics, Chem. Rev. 90 (1990), pp. 509–521. doi:10.1021/cr00101a005.
  • A. Weis, K. Katebzadeh, P. Söderhjelm, I. Nilsson, and U. Ryde, Ligand affinities predicted with the MM/PBSA method: Dependence on the simulation method and the force field, J. Med. Chem. 49 (2006), pp. 6596–6606. doi:10.1021/jm0608210.
  • J. Chen, X. Wang, T. Zhu, Q. Zhang, and J.Z.H. Zhang, A comparative insight into amprenavir resistance of mutations V32I, G48V, I50V, I54V, and I84V in HIV-1 protease based on thermodynamic integration and MM-PBSA methods, J. Chem. Inf. Model. 55 (2015), pp. 1903–1913. doi:10.1021/acs.jcim.5b00173.
  • G. Hu, A. Ma, X. Dou, L. Zhao, and J. Wang, Computational studies of a mechanism for binding and drug resistance in the wild type and four mutations of HIV-1 protease with a GRL-0519 inhibitor, Int. J. Mol. Sci. 17 (2016), pp. 819. doi:10.3390/ijms17060819.
  • L.L. Duan, T. Zhu, Y.C. Li, Q.G. Zhang, and J.Z.H. Zhang, Effect of polarization on HIV-1 protease and fluoro-substituted inhibitors binding energies by large scale molecular dynamics simulations, Sci. Rep. 7 (2017), pp. 42223. doi:10.1038/srep42223.
  • R. Wang and Q. Zheng, Multiple molecular dynamics simulations of the inhibitor GRL-02031 complex with wild type and mutant HIV-1 Protease reveal the binding and drug-resistance mechanism, Langmuir 36 (2020), pp. 13817–13832. doi:10.1021/acs.langmuir.0c02151.
  • R.-G. Wang, H.-X. Zhang, and Q.-C. Zheng, Revealing the binding and drug resistance mechanism of amprenavir, indinavir, ritonavir, and nelfinavir complexed with HIV-1 protease due to double mutations G48T/L89M by molecular dynamics simulations and free energy analyses, Phys. Chem. Chem. Phys. 22 (2020), pp. 4464–4480. doi:10.1039/C9CP06657H.
  • J. Chen, C. Peng, J. Wang, and W. Zhu, Exploring molecular mechanism of allosteric inhibitor to relieve drug resistance of multiple mutations in HIV-1 protease by enhanced conformational sampling, Proteins 86 (2018), pp. 1294–1305. doi:10.1002/prot.25610.
  • P. Kar, R. Lipowsky, and V. Knecht, Importance of polar solvation and configurational entropy for design of antiretroviral drugs targeting HIV-1 protease, J. Phys. Chem. B 117 (2013), pp. 5793–5805. doi:10.1021/jp3085292.
  • J.C. Adkins and D. Faulds, Amprenavir, Drugs 55 (1998), pp. 837–842. doi:10.2165/00003495-199855060-00015.
  • S. Noble and K.L. Goa, Amprenavir, Drugs 60 (2000), pp. 1383–1410. doi:10.2165/00003495-200060060-00012.
  • I.T. Weber, M.J. Waltman, M. Mustyakimov, M.P. Blakeley, D.A. Keen, A.K. Ghosh, P. Langan, and A.Y. Kovalevsky, Joint X-ray/neutron crystallographic study of HIV-1 protease with clinical inhibitor amprenavir: Insights for drug design, J. Med. Chem. 56 (2013), pp. 5631–5635. doi:10.1021/jm400684f.
  • J. Chen, J. Wang, B. Yin, L. Pang, W. Wang, and W. Zhu, Molecular mechanism of binding selectivity of inhibitors toward BACE1 and BACE2 revealed by multiple short molecular dynamics simulations and free-energy predictions, ACS Chem. Neurosci. 10 (2019), pp. 4303–4318. doi:10.1021/acschemneuro.9b00348.
  • J. Devillers, Computational Design of Chemicals for the Control of Mosquitoes and Their Diseases, CRC Press, Boca Raton, FL, 2018.
  • Y. Wang, L.F. Wang, L.L. Zhang, H.B. Sun, and J. Zhao, Molecular mechanism of inhibitor bindings to bromodomain-containing protein 9 explored based on molecular dynamics simulations and calculations of binding free energies, SAR QSAR Environ. Res. 31 (2020), pp. 149–170. doi:10.1080/1062936X.2019.1701075.
  • W. Xue, F. Yang, P. Wang, G. Zheng, Y. Chen, X. Yao, and F. Zhu, What contributes to serotonin–norepinephrine reuptake inhibitors’ dual-targeting mechanism? The key role of transmembrane domain 6 in human serotonin and norepinephrine transporters revealed by molecular dynamics simulation, ACS Chem. Neurosci. 9 (2018), pp. 1128–1140. doi:10.1021/acschemneuro.7b00490.
  • J. Wang, P.R. Arantes, A. Bhattarai, R.V. Hsu, S. Pawnikar, Y.-M.-M. Huang, G. Palermo, and Y. Miao, Gaussian accelerated molecular dynamics: Principles and applications, WIREs Comput. Mol. Sci. pp. e1521. doi:10.1002/wcms.1521.
  • M.-J. Yang, X.-Q. Pang, X. Zhang, and K.-L. Han, Molecular dynamics simulation reveals preorganization of the chloroplast FtsY towards complex formation induced by GTP binding, J. Struct. Biol. 173 (2011), pp. 57–66. doi:10.1016/j.jsb.2010.07.013.
  • G. Li, H. Shen, D. Zhang, Y. Li, and H. Wang, Coarse-grained modeling of nucleic acids using anisotropic gay–berne and electric multipole potentials, J. Chem. Theory Comput. 12 (2016), pp. 676–693. doi:10.1021/acs.jctc.5b00903.
  • J. Wang and Y. Miao, Peptide Gaussian accelerated molecular dynamics (Pep-GaMD): Enhanced sampling and free energy and kinetics calculations of peptide binding, J. Chem. Phys. 153 (2020), pp. 154109. doi:10.1063/5.0021399.
  • J. Chen, X. Wang, L. Pang, J.Z.H. Zhang, and T. Zhu, Effect of mutations on binding of ligands to guanine riboswitch probed by free energy perturbation and molecular dynamics simulations, Nucleic Acids Res. 47 (2019), pp. 6618–6631. doi:10.1093/nar/gkz499.
  • W. Xue, P. Wang, G. Tu, F. Yang, G. Zheng, X. Li, X. Li, Y. Chen, X. Yao, and F. Zhu, Computational identification of the binding mechanism of a triple reuptake inhibitor amitifadine for the treatment of major depressive disorder, Phys. Chem. Chem. Phys. 20 (2018), pp. 6606–6616. doi:10.1039/C7CP07869B.
  • E.L. Wu, K. Han, and J.Z.H. Zhang, Selectivity of neutral/weakly basic P1 group inhibitors of thrombin and trypsin by a molecular dynamics study, Chem. - Eur. J. 14 (2008), pp. 8704–8714. doi:10.1002/chem.200800277.
  • Y. Gao, T. Zhu, and J. Chen, Exploring drug-resistant mechanisms of I84V mutation in HIV-1 protease toward different inhibitors by thermodynamics integration and solvated interaction energy method, Chem. Phys. Lett. 706 (2018), pp. 400–408. doi:10.1016/j.cplett.2018.06.040.
  • X. Jia, M. Wang, Y. Shao, G. König, B.R. Brooks, J.Z.H. Zhang, and Y. Mei, Calculations of solvation free energy through energy reweighting from molecular mechanics to quantum mechanics, J. Chem. Theory Comput. 12 (2016), pp. 499–511. doi:10.1021/acs.jctc.5b00920.
  • J. Zhao, B. Yin, H. Sun, L. Pang, and J. Chen, Identifying hot spots of inhibitor-CDK2 bindings by computational alanine scanning, Chem. Phys. Lett. 747 (2020), pp. 137329. doi:10.1016/j.cplett.2020.137329.
  • R.M. Levy, A.R. Srinivasan, W.K. Olson, and J.A. McCammon, Quasi-harmonic method for studying very low frequency modes in proteins, Biopolymers 23 (1984), pp. 1099–1112. doi:10.1002/bip.360230610.
  • A. Amadei, A.B.M. Linssen, and H.J.C. Berendsen, Essential dynamics of proteins, Protein 17 (1993), pp. 412–425. doi:10.1002/prot.340170408.
  • J. Chen, W. Wang, H. Sun, L. Pang, and B. Yin, Mutation-mediated influences on binding of anaplastic lymphoma kinase to crizotinib decoded by multiple replica Gaussian accelerated molecular dynamics, J. Comput. Aid. Mol. Des. 34 (2020), pp. 1289–1305. doi:10.1007/s10822-020-00355-5.
  • T. Ichiye and M. Karplus, Collective motions in proteins: A covariance analysis of atomic fluctuations in molecular dynamics and normal mode simulations, Proteins 11 (1991), pp. 205–217. doi:10.1002/prot.340110305.
  • J. Zhao, H. Sun, W. Wang, L. Zhang, and J. Chen, Theoretical insights into mutation-mediated conformational changes of the GNP-bound H-RAS, Chem. Phys. Lett. 759 (2020), pp. 138042. doi:10.1016/j.cplett.2020.138042.
  • J. Chen, S. Zhang, W. Wang, L. Pang, Q. Zhang, and X. Liu, Mutation-induced impacts on the switch transformations of the GDP- and GTP-bound K-Ras: Insights from multiple replica Gaussian accelerated molecular dynamics and free energy analysis, J. Chem. Inf. Model. 61 (2021), pp. 1954–1969. doi:10.1021/acs.jcim.0c01470.
  • N.M. King, M. Prabu-Jeyabalan, R.M. Bandaranayake, M.N.L. Nalam, E.A. Nalivaika, A. Özen, T. Haliloǧlu, N.K. Yılmaz, and C.A. Schiffer, Extreme entropy–enthalpy compensation in a drug-resistant variant of HIV-1 protease, ACS Chem. Biol. 7 (2012), pp. 1536–1546. doi:10.1021/cb300191k.
  • M.K. Parai, D.J. Huggins, H. Cao, M.N.L. Nalam, A. Ali, C.A. Schiffer, B. Tidor, and T.M. Rana, Design, synthesis, and biological and structural evaluations of novel HIV-1 protease inhibitors to combat drug resistance, J. Med. Chem. 55 (2012), pp. 6328–6341. doi:10.1021/jm300238h.
  • D.A. Case, T.E. Cheatham III, T. Darden, H. Gohlke, R. Luo, K.M. Merz Jr, A. Onufriev, C. Simmerling, B. Wang, and R.J. Woods, The Amber biomolecular simulation programs, J. Comput. Chem. 26 (2005), pp. 1668–1688. doi:10.1002/jcc.20290.
  • A. Jakalian, D.B. Jack, and C.I. Bayly, Fast, efficient generation of high-quality atomic charges. AM1-BCC model: II. Parameterization and validation, J. Comput. Chem. 23 (2002), pp. 1623–1641. doi:10.1002/jcc.10128.
  • A. Jakalian, B.L. Bush, D.B. Jack, and C.I. Bayly, Fast, efficient generation of high-quality atomic charges. AM1-BCC model: I. Method, J. Comput. Chem. 21 (2000), pp. 132–146. doi:10.1002/(SICI)1096-987X(20000130)21:2<132::AID-JCC5>3.0.CO;2-P.
  • B. Machireddy, G. Kalra, S. Jonnalagadda, K. Ramanujachary, and C. Wu, Probing the binding pathway of BRACO19 to a parallel-stranded human telomeric g-quadruplex using molecular dynamics binding simulation with AMBER DNA OL15 and ligand GAFF2 force field, J. Chem. Inf. Model. 57 (2017), pp. 2846–2864. doi:10.1021/acs.jcim.7b00287.
  • J. Wang, R.M. Wolf, J.W. Caldwell, P.A. Kollman, and D.A. Case, Development and testing of a general amber force field, J. Comput. Chem. 25 (2004), pp. 1157–1174. doi:10.1002/jcc.20035.
  • J.A. Maier, C. Martinez, K. Kasavajhala, L. Wickstrom, K.E. Hauser, and C. Simmerling, ff14SB: Improving the accuracy of protein side chain and backbone parameters from ff99SB, J. Chem. Theory Comput. 11 (2015), pp. 3696–3713. doi:10.1021/acs.jctc.5b00255.
  • W.L. Jorgensen, J. Chandrasekhar, J.D. Madura, R.W. Impey, and M.L. Klein, Comparison of simple potential functions for simulating liquid wate, J. Chem. Phys. 79 (1983), pp. 926–935. doi:10.1063/1.445869.
  • R. Salomon-Ferrer, A.W. Götz, D. Poole, S. Le Grand, and R.C. Walker, Routine microsecond molecular dynamics simulations with AMBER on GPUs. 2. Explicit solvent particle mesh Ewald, J. Chem. Theory Comput. 9 (2013), pp. 3878–3888. doi:10.1021/ct400314y.
  • A.W. Götz, M.J. Williamson, D. Xu, D. Poole, S. Le Grand, and R.C. Walker, Routine microsecond molecular dynamics simulations with AMBER on GPUs. 1. Generalized born, J. Chem. Theory Comput. 8 (2012), pp. 1542–1555. doi:10.1021/ct200909j.
  • J.-P. Ryckaert, G. Ciccotti, and H.J.C. Berendsen, Numerical integration of the cartesian equations of motion of a system with constraints: Molecular dynamics of n-alkanes, J. Comput. Phys. 23 (1977), pp. 327–341. doi:10.1016/0021-9991(77)90098-5.
  • J.A. Izaguirre, D.P. Catarello, J.M. Wozniak, and R.D. Skeel, Langevin stabilization of molecular dynamics, J. Chem. Phys. 114 (2001), pp. 2090–2098. doi:10.1063/1.1332996.
  • T. Darden, D. York, and L. Pedersen, Particle mesh Ewald: An N log(N) method for Ewald sums in large systems, J. Chem. Phys. 98 (1993), pp. 10089–10092. doi:10.1063/1.464397.
  • U. Essmann, L. Perera, M.L. Berkowitz, T. Darden, H. Lee, and L.G. Pedersen, A smooth particle mesh Ewald method, J. Chem. Phys. 103 (1995), pp. 8577–8593. doi:10.1063/1.470117.
  • W. Wang and P.A. Kollman, Free energy calculations on dimer stability of the HIV protease using molecular dynamics and a continuum solvent model11Edited by B. Honig, J. Mol. Biol. 303 (2000), pp. 567–582. doi:10.1006/jmbi.2000.4057.
  • W. Wang and P.A. Kollman, Computational study of protein specificity: The molecular basis of HIV-1 protease drug resistance, Proc. Natl. Acad. Sci. U. S. A. 98 (2001), pp. 14937–14942. doi:10.1073/pnas.251265598.
  • C. Wang, D.A. Greene, L. Xiao, R. Qi, and R. Luo, Recent developments and applications of the MMPBSA method, Front. Mol. Biosci. 4 (2018), pp. 87.
  • S. Tian, J. Zeng, X. Liu, J. Chen, J.Z.H. Zhang, and T. Zhu, Understanding the selectivity of inhibitors toward PI4KIIIα and PI4KIIIβ based molecular modeling, Phys. Chem. Chem. Phys. 21 (2019), pp. 22103–22112. doi:10.1039/C9CP03598B.
  • S.L. Wu, L.F. Wang, H.B. Sun, W. Wang, and Y.X. Yu, Probing molecular mechanism of inhibitor bindings to bromodomain-containing protein 4 based on molecular dynamics simulations and principal component analysis, SAR QSAR Environ. Res. 31 (2020), pp. 547–570. doi:10.1080/1062936X.2020.1777584.
  • J. Chen, X. Liu, S. Zhang, J. Chen, H. Sun, L. Zhang, and Q. Zhang, Molecular mechanism with regard to the binding selectivity of inhibitors toward FABP5 and FABP7 explored by multiple short molecular dynamics simulations and free energy analyses, Phys. Chem. Chem. Phys. 22 (2020), pp. 2262–2275. doi:10.1039/C9CP05704H.
  • J. Chen, W. Wang, H. Sun, L. Pang, and H. Bao, Binding mechanism of inhibitors to p38α MAP kinase deciphered by using multiple replica Gaussian accelerated molecular dynamics and calculations of binding free energies, Comput. Biol. Med. 134 (2021), pp. 104485. doi:10.1016/j.compbiomed.2021.104485.
  • H. Sun, Y. Li, M. Shen, S. Tian, L. Xu, P. Pan, Y. Guan, and T. Hou, Assessing the performance of MM/PBSA and MM/GBSA methods. 5. Improved docking performance using high solute dielectric constant MM/GBSA and MM/PBSA rescoring, Phys. Chem. Chem. Phys. 16 (2014), pp. 22035–22045. doi:10.1039/C4CP03179B.
  • H. Sun, Y. Li, S. Tian, L. Xu, and T. Hou, Assessing the performance of MM/PBSA and MM/GBSA methods. 4. Accuracies of MM/PBSA and MM/GBSA methodologies evaluated by various simulation protocols using PDBbind data set, Phys. Chem. Chem. Phys. 16 (2014), pp. 16719–16729. doi:10.1039/C4CP01388C.
  • A. Onufriev, D. Bashford, and D.A. Case, Exploring protein native states and large-scale conformational changes with a modified generalized born model, Proteins 55 (2004), pp. 383–394. doi:10.1002/prot.20033.
  • H. Gohlke, C. Kiel, and D.A. Case, Insights into protein–protein binding by binding free energy calculation and free energy decomposition for the ras–raf and ras–ralGDS complexes, J. Mol. Biol. 330 (2003), pp. 891–913. doi:10.1016/S0022-2836(03)00610-7.
  • B.R. Miller, T.D. McGee, J.M. Swails, N. Homeyer, H. Gohlke, and A.E. Roitberg, MMPBSA.py: An efficient program for end-state free energy calculations, J. Chem. Theory Comput. 8 (2012), pp. 3314–3321. doi:10.1021/ct300418h.
  • D.R. Roe and T.E. Cheatham, PTRAJ and CPPTRAJ: Software for processing and analysis of molecular dynamics trajectory data, J. Chem. Theory Comput. 9 (2013), pp. 3084–3095. doi:10.1021/ct400341p.
  • J. Chen, B. Yin, W. Wang, and H. Sun, Effects of disulfide bonds on binding of inhibitors to β-amyloid cleaving enzyme 1 decoded by multiple replica accelerated molecular dynamics simulations, ACS Chem. Neurosci. 11 (2020), pp. 1811–1826. doi:10.1021/acschemneuro.0c00234.
  • F. Yan, X. Liu, S. Zhang, J. Su, Q. Zhang, and J. Chen, Effect of double mutations T790M/L858R on conformation and drug-resistant mechanism of epidermal growth factor receptor explored by molecular dynamics simulations, RSC Adv. 8 (2018), pp. 39797–39810. doi:10.1039/C8RA06844E.
  • L.F. Wang, Y. Wang, Z.Y. Yang, J. Zhao, H.B. Sun, and S.L. Wu, Revealing binding selectivity of inhibitors toward bromodomain-containing proteins 2 and 4 using multiple short molecular dynamics simulations and free energy analyses, SAR QSAR Environ. Res. 31 (2020), pp. 373–398. doi:10.1080/1062936X.2020.1748107.
  • J. Chen, W. Wang, L. Pang, and W. Zhu, Unveiling conformational dynamics changes of H-Ras induced by mutations based on accelerated molecular dynamics, Phys. Chem. Chem. Phys. 22 (2020), pp. 21238–21250. doi:10.1039/D0CP03766D.
  • W. Humphrey, A. Dalke, and K. Schulten, VMD: Visual molecular dynamics, J. Mole. Graph. 14 (1996), pp. 33–38. doi:10.1016/0263-7855(96)00018-5.
  • W.R.P. Scott and C.A. Schiffer, Curling of flap tips in HIV-1 Protease as a mechanism for substrate entry and tolerance of drug resistance, Structure 8 (2000), pp. 1259–1265. doi:10.1016/S0969-2126(00)00537-2.
  • T. Hou, W.A. McLaughlin, and W. Wang, Evaluating the potency of HIV-1 protease drugs to combat resistance, Proteins 71 (2008), pp. 1163–1174. doi:10.1002/prot.21808.
  • G. Leonis, T. Steinbrecher, and M.G. Papadopoulos, A contribution to the drug resistance mechanism of darunavir, amprenavir, indinavir, and saquinavir complexes with hiv-1 protease due to flap mutation I50V: A systematic MM–PBSA and thermodynamic integration study, J. Chem. Inf. Model. 53 (2013), pp. 2141–2153. doi:10.1021/ci4002102.
  • D. Li, J.-G. Han, H. Chen, L. Li, R.-N. Zhao, G. Liu, and Y. Duan, Insights into the structural function of the complex of HIV-1 protease with TMC-126: Molecular dynamics simulations and free-energy calculations, J. Mol. Model. 18 (2012), pp. 1841–1854. doi:10.1007/s00894-011-1205-2.
  • Y. Yu, J. Wang, Q. Shao, J. Shi, and W. Zhu, Effects of drug-resistant mutations on the dynamic properties of HIV-1 protease and inhibition by Amprenavir and Darunavir, Sci. Rep. 5 (2015), pp. 10517. doi:10.1038/srep10517.

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.