Abrams, C and Bussi, G (2014) Enhanced sampling in molecular dynamics using metadynamics, replica-exchange, and temperature-acceleration. Entropy 16, 163–199.
Amadei, A, Linssen, ABM and Berendsen, HJC (1993) Essential dynamics of proteins. Proteins-Structure Function and Genetics 17, 412–425.
Anders, C, Niewoehner, O, Duerst, A and Jinek, M (2014) Structural basis of PAM-dependent target DNA recognition by the Cas9 endonuclease. Nature 513, 569–573.
Aqvist, J (1990) Ion-water interaction potentials derived from free energy perturbation simulations. Journal of Physical Chemistry 94, 8021–8024.
Banas, P, Hollas, D, Zgarbova, M, Jurecka, P, Orozco, M, Cheatham, TE, Sponer, J and Otyepka, M (2010) Performance of molecular mechanics force fields for RNA simulations: stability of UUCG and GNRA hairpins. Journal of Chemical Theory and Computation 6, 3836–3849.
Berendsen, HJC, Postma, JPM, Van Gunsteren, WF, Dinola, A and Haak, JR (1984) Molecular dynamics with coupling to an external bath. The Journal of Chemical Physics 81, 3684–3690.
Casalino, L, Palermo, G, Abdurakhmonova, N, Rothlisberger, U and Magistrato, A (2017) Development of site-specific Mg2+-RNA force field parameters: a dream or reality? Guidelines from combined molecular dynamics and quantum mechanics simulations. Journal of Chemical Theory and Computation 13, 340–352.
Casalino, L, Palermo, G, Rothlisberger, U and Magistrato, A (2016) Who activates the nucleophile in ribozyme catalysis? An answer from the splicing mechanism of group II introns. Journal of the American Chemical Society 138, 10374–10377.
Casalino, L, Palermo, G, Spinello, A, Rothlisberger, U and Magistrato, A (2018) All-atom simulations disentangle the functional dynamics underlying gene maturation in the intron lariat spliceosome. Proceedings of the National Academy of Sciences of the USA 115, 6584–6589.
Case, DA, Betz, RM, Botello-Smith, W, Cerutti, DS, Cheatham, TE III, Darden, TA, Duke, RE, Giese, TJ, Gohlke, H, Goetz, AW, Homeyer, N, Izadi, S, Janowski, P, Kaus, J, Kovalenko, A, Lee, TS, Legrand, S, Li, P, Lin, C, Luchko, T, Luo, R, Madej, B, Mermelstein, D, Merz, KM, Monard, G, Nguyen, H, Nguyen, HT, Omelyan, I, Onufriev, A, Roe, DR, Roitberg, A, Sagui, C, Simmerling, CL, Swails, J, Walker, RC, Wang, J, Wolf, RM, Wu, X, Xiao, L, York, DM and Kollman, PA (2016). AMBER 2016. San Francisco: University of California.
Casini, A, Olivieri, M, Petris, G, Montagna, C, Reginato, G, Maule, G, Lorenzin, F, Prandi, D, Romanel, A, Demichelis, F, Inga, A and Cereseto, A (2018) A highly specific spCas9 variant is identified by in vivo screening in yeast. Nature Biotechnology 36, 265–271.
Chen, JS, Dagdas, YS, Kleinstiver, BP, Welch, MM, Harrington, LB, Sternberg, SH, Joung, JK, Yildiz, A and Doudna, JA (2017) Enhanced proofreading governs CRISPR-Cas9 targeting accuracy. Nature 550, 407–410.
Chen, JS and Doudna, JA (2017) The chemistry of Cas9 and its CRISPR colleagues. Nature Reviews Chemistry 1, 78.
Dagdas, YS, Chen, JS, Sternberg, SH, Doudna, JA and Yildiz, A (2017) A conformational checkpoint between DNA binding and cleavage By CRISPR-Cas9. Science Advances 3, eaao0027.
Doudna, JA and Charpentier, E (2014) Genome editing. The new frontier of genome engineering with CRISPR-Cas9. Science 346, 1258096–1258099.
Huai, C, Li, G, Yao, RJ, Zhang, Y, Cao, M, Kong, LL, Jia, CQ, Yuan, H, Chen, HY, Lu, DR and Huang, Q (2017) Structural insights into DNA cleavage activation of CRISPR-Cas9 system. Nature Communications 8, 1375.
Jiang, F and Doudna, JA (2017) CRISPR-Cas9 structures and mechanisms. Annual Review of Biophysics 46, 505–529.
Jiang, F, Zhou, K, Ma, L, Gressel, S and Doudna, JA (2015) STRUCTURAL BIOLOGY. A Cas9-guide RNA complex preorganized for target DNA recognition. Science 348, 1477–1481.
Jiang, FG, Taylor, DW, Chen, JS, Kornfeld, JE, Zhou, KH, Thompson, AJ, Nogales, E and Doudna, JA (2016) Structures of a CRISPR-Cas9 R-loop complex primed for DNA cleavage. Science 351, 867–871.
Jinek, M, Chylinski, K, Fonfara, I, Hauer, M, Doudna, JA and Charpentier, E (2012) A programmable dual-RNA-guided DNA endonuclease in adaptive bacterial immunity. Science 337, 816–821.
Jinek, M, Jiang, F, Taylor, DW, Sternberg, SH, Kaya, E, Ma, E, Anders, C, Hauer, M, Zhou, K, Lin, S, Kaplan, M, Iavarone, AT, Charpentier, E, Nogales, E and Doudna, JA (2014) Structures of Cas9 endonucleases reveal RNA-mediated conformational activation. Science 343, 1247997–1247111.
Jorgensen, WL, Chandrasekhar, J, Madura, JD, Impey, RW and Klein, ML (1983) Comparison of simple potential functions for simulating liquid water. Journal of Chemical Physics 79, 926–935.
Kleinstiver, BP, Pattanayak, V, Prew, MS, Tsai, SQ, Nguyen, NT, Zheng, ZL and Joung, JK (2016) High-fidelity CRISPR-Cas9 nucleases with no detectable genome-wide off-target effects. Nature 529, 490–595.
Lange, OF and Grubmuller, H (2006) Generalized correlation for biomolecular dynamics. Proteins-Structure Function and Bioinformatics 62, 1053–1061.
Le Grand, S, Goetz, AW and Walker, RC (2013) SPFP: speed without compromise – a mixed precision model for GPU accelerated molecular dynamics simulations. Computer Physics Communications 148, 374–380.
Lindahl, E, Hess, B and Van Der Spoel, D (2001) GROMACS 3.0: a package for molecular simulation and trajectory analysis. Journal of Molecular Modeling 7, 306–317.
Lindorff-Larsen, K, Maragakis, P, Piana, S and Shaw, DE (2016) Picosecond to millisecond structural dynamics in human ubiquitin. The Journal of Physical Chemistry B 120, 8313–8320.
Lippert, RA, Predescu, C, Ierardi, DJ, Mackenzie, KM, Eastwood, MP, Dror, RO and Shaw, DE (2013) Accurate and efficient integration for molecular dynamics simulations at constant temperature and pressure. The Journal of Chemical Physics 139.
Miao, Y, Feher, VA and Mccammon, JA (2015) Gaussian accelerated molecular dynamics: unconstrained enhanced sampling and free energy calculation. Journal of Chemical Theory and Computation 11, 3584–3595.
Miao, Y and Mccammon, JA (2016a) Graded activation and free energy landscapes of a muscarinic G protein-coupled receptor. Proceedings of the National Academy of Sciences of the USA 113, 12162–12167.
Miao, Y and Mccammon, JA (2016b) Unconstrained enhanced sampling for free energy calculations of biomolecules: a review. Molecular Simulations 42, 1046–1055.
Miao, Y and Mccammon, JA (2018) Mechanism of the G-protein mimetic nanobody binding to a muscarinic G-protein-coupled receptor. Proceedings of the National Academy of Sciences of the USA 115, 3036–3041.
Mouchlis, VD, Bucher, D, Mccammon, JA and Dennis, EA (2015) Membranes serve as allosteric activators of phospholipase A(2), enabling it to extract, bind, and hydrolyze phospholipid substrates. Proceedings of the National Academy of Sciences of the USA 112, E516–E525.
Nishimasu, H and Nureki, O (2017) Structures and mechanisms of CRISPR RNA-guided effector nucleases. Current Opinion in Structural Biology 43, 68–78.
Nishimasu, H, Ran, FA, Hsu, PD, Konermann, S, Shehata, SI, Dohmae, N, Ishitani, R, Zhang, F and Nureki, O (2014) Crystal structure of Cas9 in complex with guide RNA and target DNA. Cell 156, 935–949.
Nogales, E (2016) The development of cryo-EM into a mainstream structural biology technique. Nature Methods 13, 24–27.
Osuka, S, Isomura, K, Kajimoto, S, Komori, T, Nishimasu, H, Shima, T, Nureki, O and Uemura, S (2018) Real-time observation of flexible domain movements in Cas9. The EMBO Journal e96941.
Palermo, G, Cavalli, A, Klein, ML, Alfonso-Prieto, M, Dal Peraro, M and De Vivo, M (2015) Catalytic metal ions and enzymatic processing of DNA and RNA. Accounts of Chemical Research 48, 220–228.
Palermo, G, Miao, Y, Walker, RC, Jinek, M and Mccammon, JA (2016) Striking plasticity of CRISPR-Cas9 and key role of non-target DNA, as revealed by molecular simulations. ACS Central Science 2, 756–763.
Palermo, G, Miao, Y, Walker, RC, Jinek, M and Mccammon, JA (2017 a) CRISPR-Cas9 conformational activation as elucidated from enhanced molecular simulations. Proceedings of the National Academy of Sciences of the USA 114, 7260–7265.
Palermo, G, Ricci, CG, Fernando, A, Rajshekhar, B, Jinek, M, Rivalta, I, Batista, VS and Mccammon, JA (2017 b) PAM-induced allostery activates CRISPR-Cas9. Journal of the American Chemical Society 139, 16028–16031.
Palermo, G, Stenta, M, Cavalli, A, Dal Peraro, M and De Vivo, M (2013) Molecular simulations highlight the role of metals in catalysis and inhibition of type II topoisomerase. Journal of Chemical Theory and Computation 9, 857–862.
Paul, F, Wehmeyer, C, Abualrous, ET, Wu, H, Crabtree, MD, Schoneberg, J, Clarke, J, Freund, C, Weikl, TR and Noé, F (2017) Protein-peptide association kinetics beyond the seconds timescale from atomistic simulations. Nature Communications 8, 1095.
Perez, A, Marchan, I, Svozil, D, Sponer, J, Cheatham, TE III, Laughton, CA and Orozco, M (2007) Refinement of the AMBER force field for nucleic acids: improving the description of alpha/gamma conformers. Biophysical Journal 92, 3817–3829.
Raper, AT, Stephenson, AA and Suo, Z (2018) Functional insights revealed by the kinetic mechanism of CRISPR/Cas9. Journal of the American Chemical Society 140, 2971–2984.
Ricci, CG, Silveira, RL, Rivalta, I, Batista, VS and Skaf, MS (2016) Allosteric pathways in the PPAR gamma-RXR alpha nuclear receptor complex. Scientific Reports 6, 19940.
Ryckaert, JP, Ciccotti, G and Berendsen, HJC (1977) Numerical-integration of Cartesian equations of motion of a system with constraints – molecular-dynamics of N-alkanes. Journal of Computational Physics 23, 327–341.
Salomon-Ferrer, R, Gotz, AW, Poole, D, Le Grand, S and Walker, RC (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.
Shan, YB, Klepeis, JL, Eastwood, MP, Dror, RO and Shaw, DE (2005) Gaussian split Ewald: a fast Ewald mesh method for molecular simulation. Journal of Chemical Physics 122, 54101.
Shaw, DE, Grossman, JP, Bank, JA, Batson, B, Butts, JA, Chao, JC and Deneroff, MM (2014) Anton 2: raising the bar for performance and programmability in a special-purpose molecular dynamics supercomputer. 41–53. IEEE, 2014. doi:10.1109/SC.2014.9.
Shibata, M, Nishimasu, H, Kodera, N, Hirano, S, Ando, T, Uchihashi, T and Nureki, O (2017) Real-space and real-time dynamics of CRISPR-Cas9 visualized by high-speed atomic force microscopy. Nature Communications 8, 1430.
Singh, D, Sternberg, SH, Fei, J, Doudna, JA and Ha, T (2016) Real-time observation of DNA recognition and rejection by the RNA-guided endonuclease Cas9. Nature Communications 7, 12778.
Slaymaker, IM, Gao, L, Zetsche, B, Scott, DA, Yan, WX and Zhang, F (2016) Rationally engineered Cas9 nucleases with improved specificity. Science 351, 84–88.
Sponer, J, Bussi, G, Krepl, M, Banas, P, Bottaro, S, Cuhna, RA, Gil-Ley, A, Pinamonti, G, Poblete, S, Jurecka, P, Walter, NG and Otyepka, M (2018) RNA structural dynamics as captured by molecular simulations: a comprehensive overview. Chemical Reviews 118, 4177–4338.
Stelzl, LS and Hummer, G (2017) Kinetics from replica exchange molecular dynamics simulations. Journal of Chemical Theory and Computations 13, 3927–3935.
Sternberg, SH, Lafrance, B, Kaplan, M and Doudna, JA (2015) Conformational control of DNA target cleavage by CRISPR-Cas9. Nature 527, 110–113.
Sung, K, Park, J, Kim, J, Lee, LK and Kim, SK (2018) Target specificity of Cas9 nuclease via DNA rearrangement regulated by the REC2 domain. Journal of the American Chemical Society 140, 7778–7781.
Tuckerman, M, Berne, BJ and Martyna, GJ (1992) Reversible multiple time scale molecular-dynamics. Journal of Chemical Physics 97, 1990–2001.
Turq, P, Lantelme, F and Friedman, HL (1977) Brownian dynamics – its application to ionic-solutions. Journal of Chemical Physics 66, 3039–3044.
Zgarbova, M, Otyepka, M, Sponer, J, Mladek, A, Banas, P, Cheatham, TE, Jurecka, P (2011) Refinement of the Cornell et al. Nucleic acids force field based on reference quantum chemical calculations of glycosidic torsion profiles. Journal of Chemical Theory and Computation 7, 2886–2902.
Zuo, Z and Liu, J (2017) Structure and dynamics of Cas9 HNH domain catalytic state. Scientific Reports 7, 17271.