The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Constant pH Replica Exchange Molecular Dynamics in Explicit Solvent Using Discrete Protonation States: Implementation, Testing, and Validation
Open accessAbstract
Abstract By utilizing Graphics Processing Units, we show that constant pH molecular dynamics simulations (CpHMD) run in Generalized Born (GB) implicit solvent for long time scales can yield poor pKa predictions as a result of sampling unrealistic conformations. To address this shortcoming, we present a method for performing constant pH molecular dynamics simulations (CpHMD) in explicit solvent using a discrete protonation state model. The method involves standard molecular dynamics (MD) being propagated in explicit solvent followed by protonation state changes being attempted in GB implicit solvent at fixed intervals. Replica exchange along the pH-dimension (pH-REMD) helps to obtain acceptable titration behavior with the proposed method. We analyzed the effects of various parameters and settings on the titration behavior of CpHMD and pH-REMD in explicit solvent, including the size of the simulation unit cell and the length of the relaxation dynamics following protonation state changes. We tested the method with the amino acid model compounds, a small pentapeptide with two titratable sites, and hen egg white lysozyme (HEWL). The proposed method yields superior predicted pKa values for HEWL over hundreds of nanoseconds of simulation relative to corresponding predicted values from simulations run in implicit solvent.
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Comparison of simple potential functions for simulating liquid water
Jorgensen, W. L., Chandrasekhar, J., Madura, J. D., Impey, R. W., & Klein, M. L. (1983) · The Journal of Chemical Physics · doi:10.1063/1.445869 · Cited by 41,298
Particle mesh Ewald: An N ⋅log( N ) method for Ewald sums in large systems
Darden, T., York, D., & Pedersen, L. (1993) · The Journal of Chemical Physics · doi:10.1063/1.464397 · Cited by 30,546
Self-citationA smooth particle mesh Ewald method
Essmann, U., Perera, L., Berkowitz, M. L., Darden, T., Lee, H., & Pedersen, L. G. (1995) · The Journal of Chemical Physics · doi:10.1063/1.470117 · Cited by 22,514
Ryckaert, J.-P., Ciccotti, G., & Berendsen, H. J. C. (1977) · Journal of Computational Physics · doi:10.1016/0021-9991(77)90098-5 · Cited by 21,239
Settle: An analytical version of the SHAKE and RATTLE algorithm for rigid water models
Miyamoto, S., & Kollman, P. A. (1992) · Journal of Computational Chemistry · doi:10.1002/jcc.540130805 · Cited by 7,344
Comparison of multiple Amber force fields and development of improved protein backbone parameters
Hornak, V., Abel, R., Okur, A., Strockbine, B., Roitberg, A., & Simmerling, C. (2006) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.21123 · Cited by 6,914
Self-citationOnufriev, A., Bashford, D., & Case, D. A. (2004) · Proteins: Structure, Function, and Bioinformatics · doi:10.1002/prot.20033 · Cited by 2,507
Routine Microsecond Molecular Dynamics Simulations with AMBER on GPUs. 1. Generalized Born
Götz, A. W., Williamson, M. J., Xu, D., Poole, D., Le Grand, S., & Walker, R. C. (2012) · Journal of Chemical Theory and Computation · doi:10.1021/ct200909j · Cited by 2,046
Zgarbová, M., Otyepka, M., Šponer, J., Mládek, A., Banáš, P., Cheatham, T. E., & Jurečka, P. (2011) · Journal of Chemical Theory and Computation · doi:10.1021/ct200162x · Cited by 1,165
Hawkins, G. D., Cramer, C. J., & Truhlar, D. G. (1996) · The Journal of Physical Chemistry · doi:10.1021/jp961710n · Cited by 884
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Lee, T.-S., Cerutti, D. S., Mermelstein, D., Lin, C., LeGrand, S., Giese, T. J., Roitberg, A., Case, D. A., Walker, R. C., & York, D. M. (2018) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.8b00462 · Cited by 481
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Schindler, C. E. M., Baumann, H., Blum, A., Böse, D., Buchstaller, H.-P., Burgdorf, L., Cappel, D., Chekler, E., Czodrowski, P., Dorsch, D., et al. (2020) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.0c00900 · Cited by 303
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Hwang, W., Austin, S. L., Blondel, A., Boittier, E. D., Boresch, S., Buck, M., Buckner, J., Caflisch, A., Chang, H.-T., Cheng, X., et al. (2024) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.4c04100 · Cited by 136
Metadata
- Authors
- Swails, J. M., York, D. M., & Roitberg, A. E.
- Venue
- Journal of Chemical Theory and Computation
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-02-25
- Volume
- 10
- Issue
- 3
- Pages
- 1341-1352
- ISSN
- 1549-9618 (ISSN-L)
- 1549-9626
- OpenAlex
- W2032427406
- Cited by
- 268
- References
- 40
- FWCI
- 5.35
- Type
- journal article
- Language
- en
- Open access
- hybrid
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