Abstract
Simulations of protein dynamics may work on different levels of molecular detail. The levels of simplification (coarse-graining) may concern different simulation aspects, including protein representation, interaction schemes or models of molecular motion. So-called coarse-grained (CG) models offer many advantages, unreachable by classical simulation tools, as demonstrated in numerous studies of protein dynamics. Followed by a brief introduction, we present example applications of CG models for efficient predictions of biophysical mechanisms. We discuss the following topics: mechanisms of chaperonin action, mechanical properties of proteins and their complexes, membrane proteins , protein-protein interactions and intrinsically unfolded proteins. These areas illustrate the opportunities for practical applications of CG simulations.
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References
Abeln, S., Frenkel, D.: Disordered flanks prevent peptide aggregation. PLoS Comput. Biol. 4, e1000241 (2008). https://doi.org/10.1371/journal.pcbi.1000241
Arad-Haase, G., et al.: Mechanical unfolding of acylphosphatase studied by single-molecule force spectroscopy and MD simulations. Biophys. J. 99, 238–247 (2010). https://doi.org/10.1016/j.bpj.2010.04.004
Arkhipov, A., Freddolino, P.L., Schulten, K.: Stability and dynamics of virus capsids described by coarse-grained modeling. Structure 14, 1767–1777 (2006). https://doi.org/10.1016/j.str.2006.10.003
Auer, S., Meersman, F., Dobson, C.M., Vendruscolo, M.: A generic mechanism of emergence of amyloid protofilaments from disordered oligomeric aggregates. PLoS Comput. Biol. 4, e1000222 (2008). https://doi.org/10.1371/journal.pcbi.1000222
Baumketner, A., Jewett, A., Shea, J.E.: Effects of confinement in chaperonin assisted protein folding: rate enhancement by decreasing the roughness of the folding energy landscape. J. Mol. Biol. 332, 701–713 (2003). https://doi.org/10.1016/S0022-2836(03)00929-X
Baumketner, A., Shea, J.E.: The structure of the Alzheimer amyloid beta 10–35 peptide probed through replica-exchange molecular dynamics simulations in explicit solvent. J. Mol. Biol. 366, 275–285 (2007)
Bell, G.I.: Models for the specific adhesion of cells to cells. Science 200, 618–627 (1978)
Bernetti, M., Cavalli, A., Mollica, L.: Protein-ligand (un)binding kinetics as a new paradigm for drug discovery at the crossroad between experiments and modelling. Medchemcomm 8, 534–550 (2017). https://doi.org/10.1039/c6md00581k
Best, R.B., Hummer, G.: Protein folding kinetics under force from molecular simulation. J. Am. Chem. Soc. 130, 3706–3707 (2008). https://doi.org/10.1021/ja0762691
Best, R.B., Paci, E., Hummer, G., Dudko, O.K.: Pulling direction as a reaction coordinate for the mechanical unfolding of single molecules. J. Phys. Chem. B 112, 5968–5976 (2008). https://doi.org/10.1021/Jp075955j
Betancourt, M.R., Thirumalai, D.: Exploring the kinetic requirements for enhancement of protein folding rates in the GroEL cavity. J. Mol. Biol. 287, 627–644 (1999). https://doi.org/10.1006/jmbi.1999.2591
Bindschadler, M.: Modeling actin dynamics. Wiley Interdisciplinary Rev. Syst. Biol. Med. 2, 481–488 (2010). https://doi.org/10.1002/wsbm.62
Brockwell, D.J., et al.: Pulling geometry defines the mechanical resistance of a beta-sheet protein (vol 10, pg 731, 2003). Nat. Struct. Biol. 10, 872–872 (2003). https://doi.org/10.1038/nsb1003-872b
Bustamante, C., Chemla, Y.R., Forde, N.R., Izhaky, D.: Mechanical processes in biochemistry. Annu. Rev. Biochem. 73, 705–748 (2004). https://doi.org/10.1146/annurev.biochem.72.121801.161542
Caraglio, M., Imparato, A., Pelizzola, A.: Pathways of mechanical unfolding of FnIII(10): low force intermediates. J. Chem. Phys. 133, 065101 (2010). https://doi.org/10.1063/1.3464476
Carrion-Vazquez, M., Li, H., Lu, H., Marszalek, P.E., Oberhauser, A.F., Fernandez, J.M.: The mechanical stability of ubiquitin is linkage dependent. Nat. struct. Biol. 10, 738–743 (2003). https://doi.org/10.1038/nsb965
Chan, H.S., Zhang, Z., Wallin, S., Liu, Z.: Cooperativity, local-nonlocal coupling, and nonnative interactions: principles of protein folding from coarse-grained models. Annu. Rev. Phys. Chem. 62, 301–326 (2011). https://doi.org/10.1146/annurev-physchem-032210-103405
Chang, S., Hu, J.P., Lin, P.Y., Jiao, X., Tian, X.H.: Substrate recognition and transport behavior analyses of amino acid antiporter with coarse-grained models. Mol. BioSyst. 6, 2430–2438 (2010). https://doi.org/10.1039/c005266c
Chetwynd, A.P., Scott, K.A., Mokrab, Y., Sansom, M.S.: CGDB: a database of membrane protein/lipid interactions by coarse-grained molecular dynamics simulations. Mol. Membr. Biol. 25, 662–669 (2008). https://doi.org/10.1080/09687680802446534
Chiricotto, M., Tran, T.T., Nguyen, P.H., Melchionna, S., Sterpone, F., Derreumaux, P.: Coarse-grained and all-atom simulations towards the early and late steps of amyloid fibril formation. Isr. J. Chem. 57, 564–573 (2017)
Chu, J.W., Voth, G.A.: Coarse-grained modeling of the actin filament derived from atomistic-scale simulations. Biophys. J. 90, 1572–1582 (2006). https://doi.org/10.1529/biophysj.105.073924
Ciemny, M.P., Kurcinski, M., Kamel, K., Kolinski, A., Nawsad, A., Schueler-Furman, O., Kmiecik, S.: Protein–peptide docking: opportunities and challenges. Drug Discov. Today. 23, 1530–1537 (2018)
Ciemny, M.P., Debinski, A., Paczkowska, M., Kolinski, A., Kurcinski, M., Kmiecik, S.: Protein-peptide molecular docking with large-scale conformational changes: the p 53-MDM2 interaction. Sci. Rep. 6, 37532 (2016). https://doi.org/10.1038/srep37532
Cieplak, M., Hoang, T.X., Robbins, M.O.: Folding and stretching in a go-like model of titin. Proteins 49, 114–124 (2002). https://doi.org/10.1002/prot.10087
Clementi, C., Nymeyer, H., Onuchic, J.N.: Topological and energetic factors: what determines the structural details of the transition state ensemble and “en-route” intermediates for protein folding? An investigation for small globular proteins. J. Mol. Biol. 298, 937–953 (2000). https://doi.org/10.1006/jmbi.2000.3693
Colizzi, F., Perozzo, R., Scapozza, L., Recanatini, M., Cavalli, A.: Single-molecule pulling simulations can discern active from inactive enzyme inhibitors. J. Am. Chem. Soc. 132, 7361–7371 (2010). https://doi.org/10.1021/ja100259r
De Sancho, D., Best, R.B.: Modulation of an IDP binding mechanism and rates by helix propensity and non-native interactions: association of HIF1alpha with CBP. Mol. BioSyst. 8, 256–267 (2012). https://doi.org/10.1039/c1mb05252g
Di Fenza, A., Rocchia, W., Tozzini, V.: Complexes of HIV-1 integrase with HAT proteins: multiscale models, dynamics, and hypotheses on allosteric sites of inhibition. Proteins: Struct. Funct. Bioinf. 76, 946–958 (2009). https://doi.org/10.1002/prot.22399
Dudko, O.K., Hummer, G., Szabo, A.: Intrinsic rates and activation free energies from single-molecule pulling experiments. Phys. Rev. Lett. 96, 108101 (2006). https://doi.org/10.1103/PhysRevLett.96.108101
Eliezer, D.: Biophysical characterization of intrinsically disordered proteins. Curr. Opin. Struct. Biol. 19, 23–30 (2009). https://doi.org/10.1016/j.sbi.2008.12.004
Evans, E., Ritchie, K.: Dynamic strength of molecular adhesion bonds. Biophys. J. 72, 1541–1555 (1997). https://doi.org/10.1016/S0006-3495(97)78802-7
Fernandez, J.M., Li, H.B.: Force-clamp spectroscopy monitors the folding trajectory of a single protein. Science 303, 1674–1678 (2004). https://doi.org/10.1126/science.1092497
Fletcher, D.A., Mullins, R.D.: Cell mechanics and the cytoskeleton. Nature 463, 485–492 (2010). https://doi.org/10.1038/nature08908
Florin, E.L., Moy, V.T., Gaub, H.E.: Adhesion forces between individual ligand-receptor pairs. Science 264, 415–417 (1994). https://doi.org/10.1126/science.8153628
Fowler, S.B., et al.: Mechanical unfolding of a titin Ig domain: structure of unfolding intermediate revealed by combining AFM, molecular dynamics simulations, NMR and protein engineering. J. Mol. Biol. 322, 841–849 (2002). https://doi.org/10.1016/S0022-2836(02)00805-7
Frembgen-Kesner, T., Elcock, A.H.: Absolute protein-protein association rate constants from flexible, coarse-grained brownian dynamics simulations: the role of intermolecular hydrodynamic interactions in Barnase-Barstar association. Biophys. J. 99, L75–L77 (2010). https://doi.org/10.1016/j.bpj.2010.09.006
Granzier, H.L., Labeit, S.: The giant protein titin: a major player in myocardial mechanics, signaling, and disease. Circ. Res. 94, 284–295 (2004). https://doi.org/10.1161/01.res.0000117769.88862.f8
Grubmuller, H., Heymann, B., Tavan, P.: Ligand binding: Molecular mechanics calculation of the streptavidin biotin rupture force. Science 271, 997–999 (1996). https://doi.org/10.1126/science.271.5251.997
Gu, J.F., Li, H.X., Wang, X.C.: A self-adaptive steered molecular dynamics method based on minimization of stretching force reveals the binding affinity of protein-ligand complexes. Molecules 20, 19236–19251 (2015). https://doi.org/10.3390/molecules201019236
Habchi, J., Tompa, P., Longhi, S., Uversky, V.N.: Introducing protein intrinsic disorder. Chem. Rev. 114, 6561–6588 (2014). https://doi.org/10.1021/cr400514h
Habibi, M., Rottler, J., Plotkin, S.S.: As simple as possible but not simpler: on the reliability of protein coarse-grained models. Biophys. J. 112, 176a–176a (2017)
Hall, B.A., Chetwynd, A.P., Sansom, M.S.: Exploring peptide-membrane interactions with coarse-grained MD simulations. Biophys. J. 100, 1940–1948 (2011). https://doi.org/10.1016/j.bpj.2011.02.041
Hall, B.A., Sansom, M.S.P.: Coarse-grained MD simulations and protein–protein interactions: the Cohesin–Dockerin system. J. Chem. Theory Comput. 5, 2465–2471 (2009). https://doi.org/10.1021/ct900140w
Hanson, P.I., Whiteheart, S.W.: AAA + proteins: have engine, will work. Nat. Rev. Mol. Cell Biol. 6, 519–529 (2005). https://doi.org/10.1038/nrm1684
He, C., Genchev, G.Z., Lu, H., Li, H.: Mechanically untying a protein slipknot: multiple pathways revealed by force spectroscopy and steered molecular dynamics simulations. J. Am. Chem. Soc. 134, 10428–10435 (2012). https://doi.org/10.1021/ja3003205
Heath, A.P., Kavraki, L.E., Clementi, C.: From coarse-grain to all-atom: toward multiscale analysis of protein landscapes. Proteins 68, 646–661 (2007). https://doi.org/10.1002/prot.21371
Huang, Y., Liu, Z.: Kinetic advantage of intrinsically disordered proteins in coupled folding-binding process: a critical assessment of the “Fly-Casting” mechanism. J. Mol. Biol. 393, 1143–1159 (2009). https://doi.org/10.1016/j.jmb.2009.09.010
Hunte, C.: Specific protein-lipid interactions in membrane proteins. Biochem. Soc. Trans. 33, 938–942 (2005). https://doi.org/10.1042/BST20050938
Irback, A., Mitternacht, S., Mohanty, S.: Dissecting the mechanical unfolding of ubiquitin. Proc Natl Acad Sci U S A 102, 13427–13432 (2005). https://doi.org/10.1073/pnas.0501581102
Jacob, E., Horovitz, A., Unger, R.: Different mechanistic requirements for prokaryotic and eukaryotic chaperonins: a lattice study. Bioinformatics 23, i240–i248 (2007). https://doi.org/10.1093/bioinformatics/btm180
Jamroz, M., Kolinski, A., Kmiecik, S.: CABS-flex: server for fast simulation of protein structure fluctuations. Nucleic Acids Res. 41, W427–W431 (2013). https://doi.org/10.1093/nar/gkt332
Jamroz, M., Kolinski, A., Kmiecik, S.: CABS-flex predictions of protein flexibility compared with NMR ensembles. Bioinformatics 30, 2150–2154 (2014). https://doi.org/10.1093/bioinformatics/btu184
Jamroz, M., Orozco, M., Kolinski, A., Kmiecik, S.: Consistent view of protein fluctuations from all-atom molecular dynamics and coarse-grained dynamics with knowledge-based force-field. J. Chem. Theor. Comput. 9, 119–125 (2013). https://doi.org/10.1021/ct300854w
Jewett, A.I., Baumketner, A., Shea, J.E.: Accelerated folding in the weak hydrophobic environment of a chaperonin cavity: creation of an alternate fast folding pathway. Proc Natl Acad Sci U S A 101, 13192–13197 (2004). https://doi.org/10.1073/pnas.0400720101
Jewett, A.I., Shea, J.E.: Reconciling theories of chaperonin accelerated folding with experimental evidence. Cell. Mol. Life Sci. 67, 255–276 (2009)
Jung, J., Mori, T., Kobayashi, C., Matsunaga, Y., Yoda, T., Feig, M., Sugita, Y.: GENESIS: a hybrid-parallel and multi-scale molecular dynamics simulator with enhanced sampling algorithms for biomolecular and cellular simulations. Wiley Interdisciplinary Rev. Comput. Mol. Sci. 5, 310–323 (2015). https://doi.org/10.1002/wcms.1220
Kalli, A.C., Hall, B.A., Campbell, I.D., Sansom, M.S.: A helix heterodimer in a lipid bilayer: prediction of the structure of an integrin transmembrane domain via multiscale simulations. Structure 19, 1477–1484 (2011). https://doi.org/10.1016/j.str.2011.07.014
Kamerlin, S.C., Vicatos, S., Dryga, A., Warshel, A.: Coarse-grained (multiscale) simulations in studies of biophysical and chemical systems. Annu. Rev. Phys. Chem. 62, 41–64 (2011). https://doi.org/10.1146/annurev-physchem-032210-103335
Kar, P., Gopal, S.M., Cheng, Y.M., Panahi, A., Feig, M.: Transferring the PRIMO coarse-grained force field to the membrane environment: simulations of membrane proteins and helix-helix association. J. Chem. Theor. Comput. 10, 3459–3472 (2014). https://doi.org/10.1021/ct500443v
Kim, Y.C., Hummer, G.: Coarse-grained models for simulations of multiprotein complexes: application to ubiquitin binding. J. Mol. Biol. 375, 1416–1433 (2008). https://doi.org/10.1016/j.jmb.2007.11.063
Kim, B.L., Schafer, N.P., Wolynes, P.G.: Predictive energy landscapes for folding alpha-helical transmembrane proteins. Proc. Natl. Acad. Sci. U S A 111, 11031–11036 (2014). https://doi.org/10.1073/pnas.1410529111. 1410529111 [pii]
Kim, Y.C., Tang, C., Clore, G.M., Hummer, G.: Replica exchange simulations of transient encounter complexes in protein-protein association. Proc. Natl. Acad. Sci. U S A 105, 12855–12860 (2008). https://doi.org/10.1073/pnas.0802460105
Kmiecik, S., Gront, D., Kolinski, A.: Towards the high-resolution protein structure prediction. Fast refinement of reduced models with all-atom force field. BMC Struct. Biol. 7, 43 (2007). https://doi.org/10.1186/1472-6807-7-43
Kmiecik, S., Gront, D., Kolinski, M., Wieteska, L., Dawid, A.E., Kolinski, A.: Coarse-grained protein models and their applications. Chem. Rev. 116, 7898–7936 (2016). https://doi.org/10.1021/acs.chemrev.6b00163
Kmiecik, S., Gront, D., Kouza, M., Kolinski, A.: From coarse-grained to atomic-level characterization of protein dynamics: transition state for the folding of B domain of protein A. J. Phys. Chem. B 116, 7026–7032 (2012). https://doi.org/10.1021/jp301720w
Kmiecik, S., Kolinski, A.: Folding pathway of the b1 domain of protein G explored by multiscale modeling. Biophys. J. 94, 726–736 (2008). https://doi.org/10.1529/biophysj.107.116095
Kmiecik, S., Kolinski, A.: Simulation of chaperonin effect on protein folding: a shift from nucleation-condensation to framework mechanism. J. Am. Chem. Soc. 133, 10283–10289 (2011). https://doi.org/10.1021/ja203275f
Kmiecik, S., Jamroz, M., Kolinski, A.: Multiscale approach to protein folding dynamics. In: Kolinski, A. (ed.) Multiscale Approaches to Protein Modeling, pp. 281–293. Springer, New York (2011). https://doi.org/10.1007/978-1-4419-6889-0_12
Knepp, A.M., Periole, X., Marrink, S.J., Sakmar, T.P., Huber, T.: Rhodopsin forms a dimer with cytoplasmic helix 8 contacts in native membranes. Biochemistry 51, 1819–1821 (2012). https://doi.org/10.1021/bi3001598
Koga, N., Takada, S.: Folding-based molecular simulations reveal mechanisms of the rotary motor F1-ATPase. Proc. Natl. Acad. Sci. U S A 103, 5367–5372 (2006). https://doi.org/10.1073/pnas.0509642103
Kolinski, A., Skolnick, J.: Reduced models of proteins and their applications. Polymer 45, 511–524 (2004). https://doi.org/10.1016/j.polymer.2003.10.064
Kolinski, A.: Protein modeling and structure prediction with a reduced representation. Acta Biochim. Pol. 51, 349–371 (2004). doi: 035001349
Kouza, M., Banerji, A., Kolinski, A., Buhimschi, I.A., Kloczkowski, A.: Oligomerization of FVFLM peptides and their ability to inhibit beta amyloid peptides aggregation: consideration as a possible model. Phys. Chem. Chem. Phys. 19, 2990–2999 (2017)
Kouza, M., Banerji, A., Kolinski, A., Buhimschi, I.A., Kloczkowski, A.: Role of Resultant Dipole Moment in Mechanical Dissociation of Biological Complexes. Molecules 23, 1995 (2018)
Kouza, M., Co, N.T., Li, M.S., Kmiecik, S., Kolinski, A., Kloczkowski, A., Buhimschi, I.A.: Kinetics and mechanical stability of the fibril state control fibril formation time of polypeptide chains: A computational study. J. Chem. Phys. 148, 215106 (2018)
Kouza, M., Hu, C.K., Li, M.S.: New force replica exchange method and protein folding pathways probed by force-clamp technique. J. Chem. Phys. 128, 045103 (2008). https://doi.org/10.1063/1.2822272
Kouza, M., Hu, C.K., Zung, H., Li, M.S.: Protein mechanical unfolding: importance of non-native interactions. J. Chem. Phys. 131, 215103 (2009). https://doi.org/10.1063/1.3272275
Kouza, M., Jamroz, M., Gront, D., Kmiecik, S., Kolinski, A.: Mechanical unfolding of DDFLN4 studied by coarse-grained knowledge-based CABS model. TASK Quaterly 18, 373–378 (2014)
Kouza, M., Co, N.T., Nguyen, P.H., Kolinski, A., Li, M.S.: Preformed template fluctuations promote fibril formation: Insights from lattice and all-atom models. J. Chem. Phys. 142 (2015). doi: Artn 145104. https://doi.org/10.1063/1.4917073
Kouza, M., Lan, P.D., Gabovich, A.M., Kolinski, A., Li, M.S.: Switch from thermal to force-driven pathways of protein refolding. J. Chem. Phys. 146 (2017b). doi: Artn 135101. https://doi.org/10.1063/1.4979201
Kramers, H.A.: Brownian motion in a field of force and the diffusion model of chemical reactions. Physica 7(7), 284–303 (1940). https://doi.org/10.1016/S0031-8914(40)90098-2
Kubelka, J., Hofrichter, J., Eaton, W.A.: The protein folding ‘speed limit’. Curr. Opin. Struct. Biol. 14, 76–88 (2004)
Kumar, S., Li, M.S.: Biomolecules under mechanical force. Phys. Rep.-Rev. Sect. Phys. Lett. 486, 1–74 (2010). https://doi.org/10.1016/j.physrep.2009.11.001
Kurcinski, M., Kolinski, A.: Theoretical study of molecular mechanism of binding TRAP220 coactivator to Retinoid X Receptor alpha, activated by 9-cis retinoic acid. J. Steroid Biochem. Mol. Biol. 121, 124–129 (2010). https://doi.org/10.1016/j.jsbmb.2010.03.086
Kurcinski, M., Kolinski, A., Kmiecik, S.: Mechanism of folding and binding of an intrinsically disordered protein as revealed by ab initio simulations. J. Chem. Theor. Comput. 10, 2224–2231 (2014). https://doi.org/10.1021/ct500287c
Kurcinski, M., Oleniecki, T., Ciemny, M.P., Kuriata, A., Kolinski, A., Kmiecik, S. CABS-flex standalone: a simulation environment for fast modeling of protein flexibility. Bioinformatics, bty685 (2018).
Kuriata, A., Gierut A.M., Oleniecki, T., Ciemny, M.P., Kolinski, A., Kurcinski, M., Kmiecik, S. CABS-flex 2.0: a web server for fast simulations of flexibility of protein structures. Nucl. Acids Res. W1: W338–W343 (2018).
Lau, T.L., Kim, C., Ginsberg, M.H., Ulmer, T.S.: The structure of the integrin alphaIIbbeta3 transmembrane complex explains integrin transmembrane signalling. EMBO J. 28, 1351–1361 (2009). https://doi.org/10.1038/emboj.2009.63
Lee, A.G.: How lipids affect the activities of integral membrane proteins. BBA-Biomembr. 1666, 62–87 (2004). https://doi.org/10.1016/j.bbamem.2004.05.012
Lee, E.H., Hsin, J., Sotomayor, M., Comellas, G., Schulten, K.: Discovery through the computational microscope. Structure 17, 1295–1306 (2009). https://doi.org/10.1016/j.str.2009.09.001
Levitt, M., Warshel, A.: Computer simulation of protein folding. Nature 253, 694–698 (1975). https://doi.org/10.1038/253694a0
Li, M.S.: Secondary structure, mechanical stability, and location of transition state of proteins. Biophys. J. 93, 2644–2654 (2007). https://doi.org/10.1529/biophysj.107.106138
Li, L., Huang, H.H., Badilla, C.L., Fernandez, J.M.: Mechanical unfolding intermediates observed by single-molecule force spectroscopy in a fibronectin type III module. J. Mol. Biol. 345, 817–826 (2005). https://doi.org/10.1016/j.jmb.2004.11.021
Li, M.S., Kouza, M.: Dependence of protein mechanical unfolding pathways on pulling speeds. J. Chem. Phys. 130, 145102 (2009). https://doi.org/10.1063/1.3106761
Li, M.S., Kouza, M., Hu, C.K.: Refolding upon force quench and pathways of mechanical and thermal unfolding of ubiquitin. Biophys. J. 92, 547–561 (2007). https://doi.org/10.1529/biophysj.106.087684
Li, M.S., Mai, B.K.: Steered molecular dynamics-a promising tool for drug design. Curr. Bioinform. 7, 342–351 (2012)
Lichter, S., Rafferty, B., Flohr, Z., Martini, A.: Protein high-force pulling simulations yield low-force results. PLoS ONE 7, e34781 (2012). https://doi.org/10.1371/journal.pone.0034781
Liphardt, J., Onoa, B., Smith, S.B., Tinoco Jr., I., Bustamante, C.: Reversible unfolding of single RNA molecules by mechanical force. Science 292, 733–737 (2001). https://doi.org/10.1126/science.1058498
Liu, X., Shi, D., Zhou, S., Liu, H., Yao, X.: Molecular dynamics simulations and novel drug discovery. Expert Opin. Drug Discov. 13, 23–37 (2018). https://doi.org/10.1080/17460441.2018.1403419
Lu, H., Isralewitz, B., Krammer, A., Vogel, V., Schulten, K.: Unfolding of titin immunoglobulin domains by steered molecular dynamics simulation. Biophys. J. 75, 662–671 (1998)
Lu, H., Schulten, K.: The key event in force-induced unfolding of Titin’s immunoglobulin domains. Biophys. J. 79, 51–65 (2000). https://doi.org/10.1016/S0006-3495(00)76273-4
Lucent, D., England, J., Pande, V.: Inside the chaperonin toolbox: theoretical and computational models for chaperonin mechanism. Phys. Biol. 6, 015003 (2009). https://doi.org/10.1088/1478-3975/6/1/015003
Malolepsza, E., Boniecki, M., Kolinski, A., Piela, L.: Theoretical model of prion propagation: a misfolded protein induces misfolding. Proc. Natl. Acad. Sci. USA 102, 7835–7840 (2005)
Marrink, S.J., Tieleman, D.P.: Perspective on the Martini model. Chem. Soc. Rev. 42, 6801–6822 (2013). https://doi.org/10.1039/c3cs60093a
Marszalek, P.E., Lu, H., Li, H., Carrion-Vazquez, M., Oberhauser, A.F., Schulten, K., Fernandez, J.M.: Mechanical unfolding intermediates in titin modules. Nature 402, 100–103 (1999). https://doi.org/10.1038/47083
Mittag, T., Kay, L.E., Forman-Kay, J.D.: Protein dynamics and conformational disorder in molecular recognition. J. Mol. Recognit. 23, 105–116 (2010). https://doi.org/10.1002/jmr.961
Morriss-Andrews, A., Shea, J.E.: Simulations of protein aggregation: insights from atomistic and coarse-grained models. J. Phys. Chem. Lett. 5, 1899–1908 (2014). https://doi.org/10.1021/jz5006847
Morriss-Andrews, A., Shea, J.E.: Computational studies of protein aggregation: methods and applications. Annu. Rev. Phys. Chem. 66, 643–666 (2015). https://doi.org/10.1146/annurev-physchem-040513-103738
Munoz, V., Henry, E.R., Hofrichter, J., Eaton, W.A.: A statistical mechanical model for beta-hairpin kinetics. Proc. Natl. Acad. Sci. U S A 95, 5872–5879 (1998). https://doi.org/10.1073/pnas.95.11.5872
Nasica-Labouze, J., et al.: Amyloid beta protein and Alzheimer’s Disease: when computer simulations complement experimental studies. Chem. Rev. 115, 3518–3563 (2015)
Nguyen, P.H., Li, M.S., Stock, G., Straub, J.E., Thirumalai, D.: Monomer adds to preformed structured oligomers of A beta-peptides by a two-stage dock-lock mechanism. Proc. Natl. Acad. Sci. U.S.A. 104, 111–116 (2007). https://doi.org/10.1073/Pnas.0607440104
Nilsson, J., Persson, B., von Heijne, G.: Comparative analysis of amino acid distributions in integral membrane proteins from 107 genomes. Proteins 60, 606–616 (2005). https://doi.org/10.1002/prot.20583
Norgaard, A.B., Ferkinghoff-Borg, J., Lindorff-Larsen, K.: Experimental parameterization of an energy function for the simulation of unfolded proteins. Biophys. J. 94, 182–192 (2008). https://doi.org/10.1529/biophysj.107.108241
Okazaki, K.-I., Sato, T., Takano, M.: Temperature-enhanced association of proteins due to electrostatic interaction: a coarse-grained simulation of Actin-Myosin binding. J. Am. Chem. Soc. 134, 8918–8925 (2012). https://doi.org/10.1021/ja301447j
Paci, E., Karplus, M.: Unfolding proteins by external forces and temperature: the importance of topology and energetics. Proc. Natl. Acad. Sci. U S A 97, 6521–6526 (2000). https://doi.org/10.1073/pnas.100124597
Peplowski, L., Sikora, M., Nowak, W., Cieplak, M.: Molecular jamming–the cystine slipknot mechanical clamp in all-atom simulations. J. Chem. Phys. 134, 085102 (2011). https://doi.org/10.1063/1.3553801
Perilla, J.R., et al.: Molecular dynamics simulations of large macromolecular complexes. Curr. Opin. Struct. Biol. 31, 64–74 (2015). https://doi.org/10.1016/j.sbi.2015.03.007
Periole, X., Knepp, A.M., Sakmar, T.P., Marrink, S.J., Huber, T.: Structural determinants of the supramolecular organization of G protein-coupled receptors in bilayers. J. Am. Chem. Soc. 134, 10959–10965 (2012). https://doi.org/10.1021/ja303286e
Plaxco, K.W., Simons, K.T., Baker, D.: Contact order, transition state placement and the refolding rates of single domain proteins. J. Mol. Biol. 277, 985–994 (1998). https://doi.org/10.1006/jmbi.1998.1645
Pulawski, W., Jamroz, M., Kolinski, M., Kolinski, A., Kmiecik, S.: Coarse-Grained simulations of membrane insertion and folding of small helical proteins using the CABS model. J. Chem. Inf. Model. 56, 2207–2215 (2016). https://doi.org/10.1021/acs.jcim.6b00350
Rathore, N., Knotts, T.A.T., de Pablo, J.J.: Confinement effects on the thermodynamics of protein folding: Monte Carlo simulations. Biophys. J. 90, 1767–1773 (2006). https://doi.org/10.1529/biophysj.105.071076
Rauscher, S., Gapsys, V., Gajda, M.J., Zweckstetter, M., de Groot, B.L., Grubmuller, H.: Structural ensembles of intrinsically disordered proteins depend strongly on force field: a comparison to experiment. J. Chem. Theor. Comput. 11, 5513–5524 (2015). https://doi.org/10.1021/acs.jctc.5b00736
Rauscher, S., Pomès, R.: Molecular simulations of protein disorder. This paper is one of a selection of papers published in this special issue entitled “Canadian Society of Biochemistry, Molecular & Cellular Biology 52nd Annual Meeting—Protein Folding: Principles and Diseases” and has undergone the Journal’s usual peer review process. Biochem. Cell Biol. 88, 269–290 (2010). https://doi.org/10.1139/o09-169
Rief, M., Gautel, M., Oesterhelt, F., Fernandez, J.M., Gaub, H.E.: Reversible unfolding of individual titin immunoglobulin domains by AFM. Science 276, 1109–1112 (1997). https://doi.org/10.1126/science.276.5315.1109
Rojas, A., Liwo, A., Browne, D., Scheraga, H.A.: Mechanism of fiber assembly: treatment of a beta peptide aggregation with a coarse-grained united-residue force field. J. Mol. Biol. 404, 537–552 (2010)
Ruprecht, J.J., Mielke, T., Vogel, R., Villa, C., Schertler, G.F.: Electron crystallography reveals the structure of metarhodopsin I. EMBO J. 23, 3609–3620 (2004). https://doi.org/10.1038/sj.emboj.7600374
Russel, D., Lasker, K., Phillips, J., Schneidman-Duhovny, D., Velazquez-Muriel, J.A., Sali, A.: The structural dynamics of macromolecular processes. Curr. Opin. Cell Biol. 21, 97–108 (2009). https://doi.org/10.1016/j.ceb.2009.01.022
Rydzewski, J., Nowak, W.: Ligand diffusion in proteins via enhanced sampling in molecular dynamics. Phys. Life Rev. (2017). https://doi.org/10.1016/j.plrev.2017.03.003
Sansom, M.S., Scott, K.A., Bond, P.J.: Coarse-grained simulation: a high-throughput computational approach to membrane proteins. Biochem. Soc. Trans. 36, 27–32 (2008). https://doi.org/10.1042/BST0360027
Saunders, M.G., Voth, G.A.: Coarse-graining of multiprotein assemblies. Curr. Opin. Struct. Biol. 22, 144–150 (2012). https://doi.org/10.1016/j.sbi.2012.01.003
Schafer, K., Oestereich, M., Gauss, J., Diezemann, G.: Force probe simulations using a hybrid scheme with virtual sites. J. Chem. Phys. 147 (2017)
Scheraga, H.A., Khalili, M., Liwo, A.: Protein-folding dynamics: overview of molecular simulation techniques. Annu. Rev. Phys. Chem. 58, 57–83 (2007). https://doi.org/10.1146/annurev.physchem.58.032806.104614
Schlick, T., Collepardo-Guevara, R., Halvorsen, L.A., Jung, S., Xiao, X.: Biomolecularmodeling and simulation: a field coming of age. Q. Rev. Biophys. 44, 191–228 (2011). https://doi.org/10.1017/S0033583510000284
Schwaiger, I., Kardinal, A., Schleicher, M., Noegel, A.A., Rief, M.: A mechanical unfolding intermediate in an actin-crosslinking protein. Nat. Struct. Mol. Biol. 11, 81–85 (2004)
Schwaiger, I., Kardinal, A., Schleicher, M., Noegel, A.A., Rief, M.: A mechanical unfolding intermediate in an actin-crosslinking protein. Nat. Struct. Mol. Biol. 11, 81–85 (2004). https://doi.org/10.1038/nsmb705
Scott, K.A., Bond, P.J., Ivetac, A., Chetwynd, A.P., Khalid, S., Sansom, M.S.: Coarse-grained MD simulations of membrane protein-bilayer self-assembly. Structure 16, 621–630 (2008). https://doi.org/10.1016/j.str.2008.01.014
Sen, T.Z., Kloster, M., Jernigan, R.L., Kolinski, A., Bujnicki, J.M., Kloczkowski, A.: Predicting the complex structure and functional motions of the outer membrane transporter and signal transducer FecA. Biophys. J. 94, 2482–2491 (2008). https://doi.org/10.1529/biophysj.107.116046
Sengupta, D., Marrink, S.J.: Lipid-mediated interactions tune the association of glycophorin A helix and its disruptive mutants in membranes. Phys. Chem. Chem. Phys. 12, 12987–12996 (2010). https://doi.org/10.1039/c0cp00101e
Serohijos, A.W., Chen, Y., Ding, F., Elston, T.C., Dokholyan, N.V.: A structural model reveals energy transduction in dynein. Proc. Natl. Acad. Sci. U S A 103, 18540–18545 (2006). https://doi.org/10.1073/pnas.0602867103
Shoemaker, B.A., Portman, J.J., Wolynes, P.G.: Speeding molecular recognition by using the folding funnel: the fly-casting mechanism. Proc. Natl. Acad. Sci. 97, 8868–8873 (2000). https://doi.org/10.1073/pnas.160259697
Sieben, C., et al.: Influenza virus binds its host cell using multiple dynamic interactions. Proc. Natl. Acad. Sci. U S A 109, 13626–13631 (2012). https://doi.org/10.1073/pnas.1120265109
Sieradzan, A.K., Jakubowski, R.: Introduction of steered molecular dynamics into UNRES coarse-grained simulations package. J. Comput. Chem. 38, 553–562 (2017)
Sikora, M., Cieplak, M.: Mechanical stability of multidomain proteins and novel mechanical clamps. Proteins 79, 1786–1799 (2011). https://doi.org/10.1002/prot.23001
Sikora, M., Sulkowska, J.I., Witkowski, B.S., Cieplak, M.: BSDB: the biomolecule stretching database. Nucleic Acids Res. 39, D443–D450 (2011). https://doi.org/10.1093/nar/gkq851
Simmons, R.M., Finer, J.T., Chu, S., Spudich, J.A.: Quantitative measurements of force and displacement using an optical trap. Biophys. J. 70, 1813–1822 (1996). https://doi.org/10.1016/S0006-3495(96)79746-1
Smith, S.O., et al.: Implications of threonine hydrogen bonding in the glycophorin A transmembrane helix dimer. Biophys. J. 82, 2476–2486 (2002). https://doi.org/10.1016/S0006-3495(02)75590-2
Smith, S.B., Cui, Y., Bustamante, C.: Overstretching B-DNA: the elastic response of individual double-stranded and single-stranded DNA molecules. Science 271, 795–799 (1996). https://doi.org/10.1126/science.271.5250.795
Spijker, P., van Hoof, B., Debertrand, M., Markvoort, A.J., Vaidehi, N., Hilbers, P.A.: Coarse grained molecular dynamics simulations of transmembrane protein-lipid systems. Int. J. Mol. Sci. 11, 2393–2420 (2010). https://doi.org/10.3390/ijms11062393
Stossel, T.P., Condeelis, J., Cooley, L., Hartwig, J.H., Noegel, A., Schleicher, M., Shapiro, S.S.: Filamins as integrators of cell mechanics and signalling. Nat. Rev. Mol. Cell Biol. 2, 138–145 (2001). https://doi.org/10.1038/35052082
Sulkowska, J.I., Sulkowski, P., Onuchic, J.N.: Jamming proteins with slipknots and their free energy landscape. Phys. Rev. Lett. 103, 268103 (2009). https://doi.org/10.1103/PhysRevLett.103.268103
Sulkowska, J.I., Sulkowski, P., Szymczak, P., Cieplak, M.: Untying knots in proteins. J. Am. Chem. Soc. 132, 13954–13956 (2010). https://doi.org/10.1021/Ja102441z
Sulkowska, J.I., Cieplak, M.: Mechanical stretching of proteins - a theoretical survey of the protein data bank. J. Phys.-Condens. Mat. 19 (2007). https://doi.org/10.1088/0953-8984/19/28/283201
Szilagyi, A., Gyorffy, D., Zavodszky, P.: The twilight zone between protein order and disorder. Biophys. J. 95, 1612–1626 (2008). https://doi.org/10.1529/biophysj.108.131151
Szymczak, P., Janovjak, H.: Periodic forces trigger a complex mechanical response in ubiquitin. J. Mol. Biol. 390, 443–456 (2009). https://doi.org/10.1016/j.jmb.2009.04.071
Takada, S.: Coarse-grained molecular simulations of large biomolecules. Curr. Opin. Struct. Biol. 22, 130–137 (2012). https://doi.org/10.1016/j.sbi.2012.01.010
Takagi, F., Koga, N., Takada, S.: How protein thermodynamics and folding mechanisms are altered by the chaperonin cage: molecular simulations. Proc. Natl. Acad. Sci. U.S.A. 100, 11367–11372 (2003). https://doi.org/10.1073/pnas.1831920100
Taylor, W.R., Katsimitsoulia, Z.: A coarse-grained molecular model for actin-myosin simulation. J. Mol. Graph. Model. 29, 266–279 (2010). https://doi.org/10.1016/j.jmgm.2010.06.004
Thirumalai, D., Reddy, G., Straub, J.E.: Role of water in protein aggregation and amyloid polymorphism. Acc. Chem. Res. 45, 83–92 (2012). https://doi.org/10.1021/ar2000869
Turjanski, A.G., Gutkind, J.S., Best, R.B., Hummer, G.: Binding-induced folding of a natively unstructured transcription factor. PLoS Comput. Biol. 4, e1000060 (2008). https://doi.org/10.1371/journal.pcbi.1000060
Uversky, V.N.: Introduction to intrinsically disordered proteins (IDPs). Chem. Rev. 114, 6557–6560 (2014). https://doi.org/10.1021/cr500288y
Uversky, V.N., Gillespie, J.R., Fink, A.L.: Why are “natively unfolded” proteins unstructured under physiologic conditions? Proteins: Struct. Funct. Bioinf. 41, 415–427 (2000). https://doi.org/10.1002/1097-0134(20001115)41:3%3c415:aid-prot130%3e3.0.co;2-7
Vajda, S., Kozakov, D.: Convergence and combination of methods in protein-protein docking. Curr. Opin. Struct. Biol. 19, 164–170 (2009). https://doi.org/10.1016/j.sbi.2009.02.008
Valbuena, A., et al.: On the remarkable mechanostability of scaffoldins and the mechanical clamp motif. Proc. Natl. Acad. Sci. U S A 106, 13791–13796 (2009). https://doi.org/10.1073/pnas.0813093106
Vendruscolo, M., Dobson, C.M.: Protein dynamics: Moore’s law in molecular biology. Curr. Biol. 21, R68–R70 (2011). https://doi.org/10.1016/j.cub.2010.11.062
Verkhivker, G.M.: Protein conformational transitions coupled to binding in molecular recognition of unstructured proteins: Deciphering the effect of intermolecular interactions on computational structure prediction of the p27Kip1 protein bound to the cyclin A–cyclin-dependent kinase 2 complex. Proteins: Struct. Funct. Bioinf. 58, 706–716 (2005). https://doi.org/10.1002/prot.20351
Verkhivker, G.M., Bouzida, D., Gehlhaar, D.K., Rejto, P.A., Freer, S.T., Rose, P.W.: Simulating disorder–order transitions in molecular recognition of unstructured proteins: where folding meets binding. Proc. Natl. Acad. Sci. 100, 5148–5153 (2003). https://doi.org/10.1073/pnas.0531373100
Vogel, V., Sheetz, M.: Local force and geometry sensing regulate cell functions. Nat. Rev. Mol. Cell Biol. 7, 265–275 (2006). https://doi.org/10.1038/nrm1890
Wang, Y.M., Latshaw, D.C., Hall, C.K.: Aggregation of A beta(17-36) in the presence of naturally occurring phenolic inhibitors using coarse-grained simulations. J. Mol. Biol. 429, 3893–3908 (2017)
Wang, J., Wang, Y., Chu, X., Hagen, S.J., Han, W., Wang, E.: Multi-scaled explorations of binding-induced folding of intrinsically disordered protein inhibitor IA3 to its target enzyme. PLoS Comput. Biol. 7, e1001118 (2011). https://doi.org/10.1371/journal.pcbi.1001118
West, D.K., Olmsted, P.D., Paci, E.: Mechanical unfolding revisited through a simple but realistic model. J. Chem. Phys. 124 (2006). https://doi.org/10.1063/1.2185100
Wolynes, P.G., Onuchic, J.N., Thirumalai, D.: Navigating the folding routes. Science 267, 1619–1620 (1995). https://doi.org/10.1126/science.7886447
Wright, P.E., Dyson, H.J.: Intrinsically unstructured proteins: re-assessing the protein structure-function paradigm. J. Mol. Biol. 293, 321–331 (1999). https://doi.org/10.1006/jmbi.1999.3110
Yao, X.Q., Kenzaki, H., Murakami, S., Takada, S.: Drug export and allosteric coupling in a multidrug transporter revealed by molecular simulations. Nat. Commun. 1, 117 (2010). https://doi.org/10.1038/ncomms1116
Zacharias, M.: Accounting for conformational changes during protein-protein docking. Curr. Opin. Struct. Biol. 20, 180–186 (2010). https://doi.org/10.1016/j.sbi.2010.02.001
Zhang, J., Muthukumar, M.: Simulations of nucleation and elongation of amyloid fibrils. J. Chem. Phys. 130, 035102 (2009). https://doi.org/10.1063/1.3050295
Zhmurov, A., Dima, R.I., Kholodov, Y., Barsegov, V.: Sop-GPU: accelerating biomolecular simulations in the centisecond timescale using graphics processors. Proteins 78, 2984–2999 (2010). https://doi.org/10.1002/prot.22824
Zhou, H.-X.: Polymer models of protein stability, folding, and interactions†. Biochemistry 43, 2141–2154 (2004). https://doi.org/10.1021/bi036269n
Zhou, H.X., Dill, K.A.: Stabilization of proteins in confined spaces. Biochemistry 40, 11289–11293 (2001). https://doi.org/10.3410/f.1002736.29765
Zhou, J., Thorpe, I.F., Izvekov, S., Voth, G.A.: Coarse-grained peptide modeling using a systematic multiscale approach. Biophys. J. 92, 4289–4303 (2007). https://doi.org/10.1529/biophysj.106.094425
Acknowledgements
We thank Dr. Joanna Sulkowska for critical reading of the section “Mechanical Unfolding and Refolding of Proteins and their Complexes” of the manuscript. We acknowledge partial support from: Foundation for Polish Science TEAM project (TEAM/2011-7/6) co-financed by the European Regional Development Fund operated within the Innovative Economy Operational Program; Polish National Science Center (NCN) on the basis of a decision DEC-2011/01/D/NZ2/05314; Polish National Science Center (NCN) Grant No. NN301071140, Polish Ministry of Science and Higher Education Grant No. IP2011024371, Polish National Science Center (NCN) Grant (MAESTRO 2014/14/A/ST6/00088). M. Kouza acknowledges the Polish Ministry of Science and Higher Education for financial support through ‘‘Mobilnosc Plus’’ Program No. 1287/MOB/IV/2015/0.
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Kmiecik, S., Wabik, J., Kolinski, M., Kouza, M., Kolinski, A. (2019). Protein Dynamics Simulations Using Coarse-Grained Models. In: Liwo, A. (eds) Computational Methods to Study the Structure and Dynamics of Biomolecules and Biomolecular Processes. Springer Series on Bio- and Neurosystems, vol 8. Springer, Cham. https://doi.org/10.1007/978-3-319-95843-9_3
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