209
Views
5
CrossRef citations to date
0
Altmetric
Research Article

Binding modes of GDP, GTP and GNP to NRAS deciphered by using Gaussian accelerated molecular dynamics simulations

, , & ORCID Icon
Pages 65-89 | Received 23 Nov 2022, Accepted 31 Dec 2022, Published online: 10 Feb 2023

References

  • A.D. Cox and C.J. Der, Ras history, Small GTPases 1 (2010), pp. 2–27. doi:10.4161/sgtp.1.1.12178.
  • C.W. Johnson, D. Reid, J.A. Parker, S. Salter, R. Knihtila, P. Kuzmic, and C. Mattos, The small GTPases K-Ras, N-Ras, and H-Ras have distinct biochemical properties determined by allosteric effects, J. Biol. Chem. 292 (2017), pp. 12981–12993. doi:10.1074/jbc.M117.778886.
  • S. Lu, H. Jang, S. Muratcioglu, A. Gursoy, O. Keskin, R. Nussinov, and J. Zhang, Ras conformational ensembles, allostery, and signaling, Chem. Rev. 116 (2016), pp. 6607–6665. doi:10.1021/acs.chemrev.5b00542.
  • S. Lu, H. Jang, S. Gu, J. Zhang, and R. Nussinov, Drugging Ras GTPase: A comprehensive mechanistic and signaling structural view, Chem. Soc. Rev. 45 (2016), pp. 4929–4952. doi:10.1039/C5CS00911A.
  • N.I. Nicely, J. Kosak, V. de Serrano, and C. Mattos, Crystal structures of Ral-GppNHp and Ral-GDP reveal two binding sites that are also present in Ras and Rap, Structure 12 (2004), pp. 2025–2036. doi:10.1016/j.str.2004.08.011.
  • F. Shima, Y. Ijiri, S. Muraoka, J. Liao, M. Ye, M. Araki, K. Matsumoto, N. Yamamoto, T. Sugimoto, Y. Yoshikawa, T. Kumasaka, M. Yamamoto, A. Tamura, and T. Kataoka, Structural basis for conformational dynamics of GTP-bound Ras protein, J. Biol. Chem. 285 (2010), pp. 22696–22705. doi:10.1074/jbc.M110.125161.
  • S.M.G. Dias and R.A. Cerione, X-ray crystal structures reveal two activated states for RhoC, Biochemistry 46 (2007), pp. 6547–6558. doi:10.1021/bi700035p.
  • A. Sultana, Y. Jin, C. Dregger, E. Franklin, L.S. Weisman, and A.R. Khan, The activation cycle of Rab GTPase Ypt32 reveals structural determinants of effector recruitment and GDI binding, FEBS Lett. 585 (2011), pp. 3520–3527. doi:10.1016/j.febslet.2011.10.013.
  • S. Xu, B.N. Long, G.H. Boris, A. Chen, S. Ni, and M.A. Kennedy, Structural insight into the rearrangement of the switch I region in GTP-bound G12A K-Ras, Acta Crystallogr. D 73 (2017), pp. 970–984. doi:10.1107/S2059798317015418.
  • Y. Sasson, L. Navon-Perry, D. Huppert, and J.A. Hirsch, RGK family G-domain: GTP analog complex structures and nucleotide-binding properties, J. Mol. Biol. 413 (2011), pp. 372–389. doi:10.1016/j.jmb.2011.08.017.
  • 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.
  • P.Y. Ting, C.W. Johnson, C. Fang, X. Cao, T.G. Graeber, C. Mattos, and J. Colicelli, Tyrosine phosphorylation of RAS by ABL allosterically enhances effector binding, FASEB J. 29 (2015), pp. 3750–3761. doi:10.1096/fj.15-271510.
  • C.W. Johnson, H.-S. Seo, E.M. Terrell, M.-H. Yang, F. KleinJan, T. Gebregiworgis, G.M.C. Gasmi-Seabrook, E.A. Geffken, J. Lakhani, K. Song, P. Bashyal, O. Popow, J.A. Paulo, A. Liu, C. Mattos, C.B. Marshall, M. Ikura, D.K. Morrison, S. Dhe-Paganon, and K.M. Haigis, Regulation of GTPase function by autophosphorylation, Mol. Cell 82 (2022), pp. 950–968.e914. doi:10.1016/j.molcel.2022.02.011.
  • J.M. Ostrem, U. Peters, M.L. Sos, J.A. Wells, and K.M. Shokat, K-Ras(G12C) inhibitors allosterically control GTP affinity and effector interactions, Nature 503 (2013), pp. 548–551. doi:10.1038/nature12796.
  • D. Kessler, M. Gmachl, A. Mantoulidis, L.J. Martin, A. Zoephel, M. Mayer, A. Gollner, D. Covini, S. Fischer, T. Gerstberger, T. Gmaschitz, C. Goodwin, P. Greb, D. Häring, W. Hela, J. Hoffmann, J. Karolyi-Oezguer, P. Knesl, S. Kornigg, M. Koegl, R. Kousek, L. Lamarre, F. Moser, S. Munico-Martinez, C. Peinsipp, J. Phan, J. Rinnenthal, J. Sai, C. Salamon, Y. Scherbantin, K. Schipany, R. Schnitzer, A. Schrenk, B. Sharps, G. Siszler, Q. Sun, A. Waterson, B. Wolkerstorfer, M. Zeeb, M. Pearson, S.W. Fesik, and D.B. McConnell, Drugging an undruggable pocket on KRAS, Proc. Natl. Acad. Sci. USA 116 (2019), pp. 15823–15829. doi:10.1073/pnas.1904529116.
  • R. Hansen, U. Peters, A. Babbar, Y. Chen, J. Feng, M.R. Janes, L.-S. Li, P. Ren, Y. Liu, and P.P. Zarrinkar, The reactivity-driven biochemical mechanism of covalent KRASG12C inhibitors, Nat. Struct. Mol. Biol. 25 (2018), pp. 454–462. doi:10.1038/s41594-018-0061-5.
  • D. Kessler, A. Bergner, J. Böttcher, G. Fischer, S. Döbel, M. Hinkel, B. Müllauer, A. Weiss-Puxbaum, and D.B. McConnell, Drugging all RAS isoforms with one pocket, Future Med. Chem. 12 (2020), pp. 1911–1923. doi:10.4155/fmc-2020-0221.
  • C.W. Johnson, Y.-J. Lin, D. Reid, J. Parker, S. Pavlopoulos, P. Dischinger, C. Graveel, A.J. Aguirre, M. Steensma, K.M. Haigis, and C. Mattos, Isoform-specific destabilization of the active site reveals a molecular mechanism of intrinsic activation of KRas G13D, Cell Rep. 28 (2019), pp. 1538–1550.e1537. doi:10.1016/j.celrep.2019.07.026.
  • A.C. Nelson, T.J. Turbyville, S. Dharmaiah, M. Rigby, R. Yang, T.-Y. Wang, J. Columbus, R. Stephens, T. Taylor, D. Sciacca, G. Onsongo, A. Sarver, S. Subramanian, D.V. Nissley, D.K. Simanshu, and E. Lou, RAS internal tandem duplication disrupts GTPase-activating protein (GAP) binding to activate oncogenic signaling, J. Biol. Chem. 295 (2020), pp. 9335–9348. doi:10.1074/jbc.RA119.011080.
  • Z. Yu, H. Su, J. Chen, and G. Hu, Deciphering conformational changes of the GDP-bound NRAS Induced by mutations G13D, Q61R, and C118S through Gaussian accelerated molecular dynamic simulations, Molecules 27 (2022), pp. 5596. doi:10.3390/molecules27175596.
  • J.S. Fraser, H. van den Bedem, A.J. Samelson, P.T. Lang, J.M. Holton, N. Echols, and T. Alber, Accessing protein conformational ensembles using room-temperature X-ray crystallography, Proc. Natl. Acad. Sci. USA 108 (2011), pp. 16247–16252. doi:10.1073/pnas.1111325108.
  • M. Spoerner, C. Herrmann, I.R. Vetter, H.R. Kalbitzer, and A. Wittinghofer, Dynamic properties of the ras switch I region and its importance for binding to effectors, Proc. Natl. Acad. Sci. USA 98 (2001), pp. 4944–4949. doi:10.1073/pnas.081441398.
  • A.A. Gorfe, B.J. Grant, and J.A. McCammon, Mapping the nucleotide and isoform-dependent structural and dynamical features of Ras proteins, Structure 16 (2008), pp. 885–896. doi:10.1016/j.str.2008.03.009.
  • A. Wittinghofer and E.F. Pal, The structure of Ras protein: A model for a universal molecular switch, Trends Biochem. Sci. 16 (1991), pp. 382–387. doi:10.1016/0968-0004(91)90156-P.
  • I.G. Serebriiskii, C. Connelly, G. Frampton, J. Newberg, M. Cooke, V. Miller, S. Ali, J.S. Ross, E. Handorf, S. Arora, C. Lieu, E.A. Golemis, and J.E. Meyer, Comprehensive characterization of RAS mutations in colon and rectal cancers in old and young patients, Nat. Commun. 10 (2019), pp. 3722. doi:10.1038/s41467-019-11530-0.
  • 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.
  • J. Chen, L. Wang, W. Wang, H. Sun, L. Pang, and H. Bao, Conformational transformation of switch domains in GDP/K-Ras induced by G13 mutants: An investigation through Gaussian accelerated molecular dynamics simulations and principal component analysis, Comput. Biol. Med. 135 (2021), pp. 104639. doi:10.1016/j.compbiomed.2021.104639.
  • J. Neumann, E. Zeindl-Eberhart, T. Kirchner, and A. Jung, Frequency and type of KRAS mutations in routine diagnostic analysis of metastatic colorectal cancer, Pathol. Res. Pract. 205 (2009), pp. 858–862. doi:10.1016/j.prp.2009.07.010.
  • M. Eren, N. Tuncbag, H. Jang, R. Nussinov, A. Gursoy, and O. Keskin, Normal mode analysis of KRas4B reveals partner specific dynamics, J. Phys. Chem. B 125 (2021), pp. 5210–5221. doi:10.1021/acs.jpcb.1c00891.
  • G.A. Hobbs, N.M. Baker, A.M. Miermont, R.D. Thurman, M. Pierobon, T.H. Tran, A.O. Anderson, A.M. Waters, J.N. Diehl, B. Papke, R.G. Hodge, J.E. Klomp, C.M. Goodwin, J.M. DeLiberty, J. Wang, R.W.S. Ng, P. Gautam, K.L. Bryant, D. Esposito, S.L. Campbell, E.F. Petricoin III, D.K. Simanshu, A.J. Aguirre, B.M. Wolpin, K. Wennerberg, U. Rudloff, A.D. Cox, and C.J. Der, Atypical KRASG12R mutant is impaired in PI3K signaling and macropinocytosis in pancreatic cancer, Cancer Discov. 10 (2020), pp. 104–123. doi:10.1158/2159-8290.cd-19-1006.
  • J. Chen, S. Zhang, Q. Zeng, W. Wang, Q. Zhang, and X. Liu, Free energy profiles relating with conformational transition of the switch domains induced by G12 mutations in GTP-bound KRAS, Front. Mol. Biosci. 9 (2022). doi:10.3389/fmolb.2022.912518.
  • K. Scheffzek, M.R. Ahmadian, W. Kabsch, L. Wiesmüller, A. Lautwein, F. Schmitz, and A. Wittinghofer, The Ras-RasGAP complex: Structural basis for GTPase activation and its loss in oncogenic ras mutants, Science 277 (1997), pp. 333–339. doi:10.1126/science.277.5324.333.
  • D.K. Simanshu, D.V. Nissley, and F. McCormick, RAS proteins and their regulators in human disease, Cell 170 (2017), pp. 17–33. doi:10.1016/j.cell.2017.06.009.
  • 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.
  • Y.X. Yu, W.T. Liu, H.Y. Li, W. Wang, H.B. Sun, L.L. Zhang, and S.L. Wu, Decoding molecular mechanism underlying binding of drugs to HIV-1 protease with molecular dynamics simulations and MM-GBSA calculations, SAR QSAR Environ. Res. 32 (2021), pp. 889–915. doi:10.1080/1062936X.2021.1979647.
  • 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.
  • Z. Sun, Z. Gong, F. Xia, and X. He, Ion dynamics and selectivity of Nav channels from molecular dynamics simulation, Chem. Phys. 548 (2021), pp. 111245. doi:10.1016/j.chemphys.2021.111245.
  • Y. Xiong, J. Zeng, F. Xia, Q. Cui, X. Deng, and X. Xu, Conformations and binding pockets of HRas and its guanine nucleotide exchange factors complexes in the guanosine triphosphate exchange process, J. Comput. Chem. 43 (2022), pp. 906–916. doi:10.1002/jcc.26846.
  • J. Devillers and H. Devillers, Toxicity profiling and prioritization of plant-derived antimalarial agents, SAR QSAR Environ. Res. 30 (2019), pp. 801–824. doi:10.1080/1062936X.2019.1665844.
  • L. Wang, D. Lu, Y. Wang, X. Xu, P. Zhong, and Z. Yang, Binding selectivity-dependent molecular mechanism of inhibitors towards CDK2 and CDK6 investigated by multiple short molecular dynamics and free energy landscapes, J. Enzyme Inhib. Med. Chem. 38 (2023), pp. 84–99. doi:10.1080/14756366.2022.2135511.
  • J. Zeng, J. Chen, F. Xia, Q. Cui, X. Deng, and X. Xu, Identification of functional substates of KRas during GTP hydrolysis with enhanced sampling simulations, Phys. Chem. Chem. Phys. 24 (2022), pp. 7653–7665. doi:10.1039/D2CP00274D.
  • S. Liang, X. Liu, S. Zhang, M. Li, Q. Zhang, and J. Chen, Binding mechanism of inhibitors to SARS-CoV-2 main protease deciphered by multiple replica molecular dynamics simulations, Phys. Chem. Chem. Phys. 24 (2022), pp. 1743–1759. doi:10.1039/D1CP04361G.
  • 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.
  • 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.
  • 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.
  • Z. Sun, Z. Huai, Q. He, and Z. Liu, A general picture of cucurbit[8]uril host–guest binding, J. Chem. Inf. Model. 61 (2021), pp. 6107–6134. doi:10.1021/acs.jcim.1c01208.
  • S.L. Wu, J. Zhao, H.B. Sun, H.Y. Li, Y.Y. Yin, and L.L. Zhang, Insights into interaction mechanism of inhibitors E3T, E3H and E3B with CREB binding protein by using molecular dynamics simulations and MM-GBSA calculations, SAR QSAR Environ. Res. 32 (2021), pp. 221–246. doi:10.1080/1062936X.2021.1887351.
  • J. Devillers and H. Devillers, Prediction of acute mammalian toxicity from QSARs and interspecies correlations, SAR QSAR Environ. Res. 20 (2009), pp. 467–500. doi:10.1080/10629360903278651.
  • L.C.T. Pierce, R. Salomon-Ferrer, C. Augusto, F. de Oliveira, J.A. McCammon, and R.C. Walker, Routine access to millisecond time scale events with accelerated molecular dynamics, J. Chem. Theory Comput. 8 (2012), pp. 2997–3002. doi:10.1021/ct300284c.
  • 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.
  • Y. Miao, V.A. Feher, and J.A. McCammon, Gaussian accelerated molecular dynamics: Unconstrained enhanced sampling and free energy calculation, J. Chem. Theory Comput. 11 (2015), pp. 3584–3595. doi:10.1021/acs.jctc.5b00436.
  • 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. Scimol. Sci. 11 (2021), pp. e1521. doi:10.1002/wcms.1521.
  • 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. Wang and Y. Miao, Mechanistic insights into specific g protein interactions with adenosine receptors, J. Phys. Chem. B 123 (2019), pp. 6462–6473. doi:10.1021/acs.jpcb.9b04867.
  • Y. Miao and J.A. McCammon, Mechanism of the G-protein mimetic nanobody binding to a muscarinic G-protein-coupledreceptor, Proc. Natl. Acad. Sci. USA 115 (2018), pp. 3036–3041. doi:10.1073/pnas.1800756115.
  • J. Chen, J. Wang, Q. Zeng, W. Wang, H. Sun, and B. Wei, Exploring the deactivation mechanism of human β2 adrenergic receptor by accelerated molecular dynamic simulations, Front. Mol. Biosci. 9 (2022), pp. 972463. doi:10.3389/fmolb.2022.972463.
  • J. Wang, L. Lan, X. Wu, L. Xu, and Y. Miao, Mechanism of RNA recognition by a Musashi RNA-binding protein, Curr. Res. Struct. Biol. 4 (2022), pp. 10–20. doi:10.1016/j.crstbi.2021.12.002.
  • Y. Wang, M. Li, W. Liang, X. Shi, J. Fan, R. Kong, Y. Liu, J. Zhang, T. Chen, and S. Lu, Delineating the activation mechanism and conformational landscape of a class B G protein-coupled receptor glucagon receptor, Comput. Struct. Biotec. 20 (2022), pp. 628–639. doi:10.1016/j.csbj.2022.01.015.
  • J. Chen, S. Zhang, W. Wang, H. Sun, Q. Zhang, and X. Liu, Binding of inhibitors to BACE1 affected by pH-dependent protonation: An exploration from multiple replica Gaussian accelerated molecular dynamics and MM-GBSA calculations, ACS Chem. Neurosci. 12 (2021), pp. 2591–2607. doi:10.1021/acschemneuro.0c00813.
  • M. Li, X. Liu, S. Zhang, S. Liang, Q. Zhang, and J. Chen, Deciphering the binding mechanism of inhibitors of the SARS-CoV-2 main protease through multiple replica accelerated molecular dynamics simulations and free energy landscapes, Phys. Chem. Chem. Phys. 24 (2022), pp. 22129–22143. doi:10.1039/D2CP03446H.
  • J. Chen, Q. Zeng, W. Wang, H. Sun, and G. Hu, Decoding the identification mechanism of an SAM-III riboswitch on ligands through multiple independent Gaussian-accelerated molecular dynamics simulations, J. Chem. Inf. Model. 62 (2022), pp. 6118–6132. doi:10.1021/acs.jcim.2c00961.
  • A. Amadei, A.B.M. Linssen, and H.J.C. Berendsen, Essential dynamics of proteins, Proteins 17 (1993), pp. 412–425. doi:10.1002/prot.340170408.
  • 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.
  • 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.
  • X. He, V.H. Man, W. Yang, T.-S. Lee, and J. Wang, A fast and high-quality charge model for the next generation general AMBER force field, J. Chem. Phys. 153 (2020), pp. 114502. doi:10.1063/5.0019056.
  • 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.
  • J. Wang, W. Wang, P.A. Kollman, and D.A. Case, Automatic atom type and bond type perception in molecular mechanical calculations, J. Mol. Graph. Model. 25 (2006), pp. 247–260. doi:10.1016/j.jmgm.2005.12.005.
  • R. Anandakrishnan, B. Aguilar, and A.V. Onufriev, H++ 3.0: Automating pK prediction and the preparation of biomolecular structures for atomistic molecular modeling and simulations, Nucleic Acids Res. 40 (2012), pp. W537–W541. doi:10.1093/nar/gks375.
  • R. Salomon-Ferrer, D.A. Case, and R.C. Walker, An overview of the Amber biomolecular simulation package, WIREs Comput. Mol. Sci. 3 (2013), pp. 198–210. doi:10.1002/wcms.1121.
  • 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.
  • C. Tian, K. Kasavajhala, K.A.A. Belfon, L. Raguette, H. Huang, A.N. Migues, J. Bickel, Y. Wang, J. Pincay, Q. Wu, and C. Simmerling, ff19SB: Amino-acid-specific protein backbone parameters trained against quantum mechanics energy surfaces in solution, J. Chem. Theory Comput. 16 (2020), pp. 528–552. doi:10.1021/acs.jctc.9b00591.
  • W.L. Jorgensen, J. Chandrasekhar, J.D. Madura, R.W. Impey, and M.L. Klein, Comparison of simple potential functions for simulating liquid water, J. Chem. Phys. 79 (1983), pp. 926–935. doi:10.1063/1.445869.
  • I.S. Joung and T.E. Cheatham III, Determination of alkali and halide monovalent ion parameters for use in explicitly solvated biomolecular simulations, J. Phys. Chem. B 112 (2008), pp. 9020–9041. doi:10.1021/jp8001614.
  • I.S. Joung and T.E. Cheatham III, Molecular dynamics simulations of the dynamic and energetic properties of alkali and halide ions using water-model-specific ion parameters, J. Phys. Chem. B 113 (2009), pp. 13279–13290. doi:10.1021/jp902584c.
  • 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.
  • Y. Miao, W. Sinko, L. Pierce, D. Bucher, R.C. Walker, and J.A. McCammon, Improved reweighting of accelerated molecular dynamics simulations for free energy calculation, J. Chem. Theory Comput. 10 (2014), pp. 2677–2689. doi:10.1021/ct500090q.
  • 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.
  • 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.
  • W. Humphrey, A. Dalke, and K. Schulten, VMD: Visual molecular dynamics, J. Mol. Graph. 14 (1996), pp. 33–38. doi:10.1016/0263-7855(96)00018-5.
  • D.R. Roe and T.E. Cheatham III, 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.
  • 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.
  • S.S. Liang, X.G. Liu, Y.X. Cui, S.L. Zhang, Q.G. Zhang, and J.Z. Chen, Molecular mechanism concerning conformational changes of CDK2 mediated by binding of inhibitors using molecular dynamics simulations and principal component analysis, SAR QSAR Environ. Res. 32 (2021), pp. 573–594. doi:10.1080/1062936X.2021.1934896.
  • F. Yan, X. Liu, S. Zhang, J. Su, Q. Zhang, and J. Chen, Molecular dynamics exploration of selectivity of dual inhibitors 5M7, 65X, and 65Z toward fatty acid binding proteins 4 and 5, Int. J. Mol. Sci. 19 (2018), pp. 2496. doi:10.3390/ijms19092496.
  • S. Vatansever, B. Erman, and Z.H. Gümüş, Comparative effects of oncogenic mutations G12C, G12V, G13D, and Q61H on local conformations and dynamics of K-Ras, Comput. Struct. Biotec. 18 (2020), pp. 1000–1011. doi:10.1016/j.csbj.2020.04.003.
  • P. Prakash, J.F. Hancock, and A.A. Gorfe, Binding hotspots on K-Ras: Consensus ligand binding sites and other reactive regions from probe-based molecular dynamics analysis, Proteins 83 (2015), pp. 898–909. doi:10.1002/prot.24786.
  • X. Wang, Conformational fluctuations in GTP-bound K-Ras: A metadynamics perspective with harmonic linear discriminant analysis, J. Chem. Inf. Model. 61 (2021), pp. 5212–5222. doi:10.1021/acs.jcim.1c00844.

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.