The DOI matches its Crossref record; 31 of the 31 references it cites were found in a registry or an index.
Molecular Simulation of ab Initio Protein Folding for a Millisecond Folder NTL9(1−39)
Open accessAbstract
To date, the slowest-folding proteins folded ab initio by all-atom molecular dynamics simulations have had folding times in the range of nanoseconds to microseconds. We report simulations of several folding trajectories of NTL9(1-39), a protein which has a folding time of approximately 1.5 ms. Distributed molecular dynamics simulations in implicit solvent on GPU processors were used to generate ensembles of trajectories out to approximately 40 micros for several temperatures and starting states. At a temperature less than the melting point of the force field, we observe a small number of productive folding events, consistent with predictions from a model of parallel uncoupled two-state simulations. The posterior distribution of the folding rate predicted from the data agrees well with the experimental folding rate (approximately 640/s). Markov State Models (MSMs) built from the data show a gap in the implied time scales indicative of two-state folding and heterogeneous pathways connecting diffuse mesoscopic substates. Structural analysis of the 14 out of 2000 macrostates transited by the top 10 folding pathways reveals that native-like pairing between strands 1 and 2 only occurs for macrostates with p(fold) > 0.5, suggesting beta(12) hairpin formation may be rate-limiting. We believe that using simulation data such as these to seed adaptive resampling simulations will be a promising new method for achieving statistically converged descriptions of folding landscapes at longer time scales than ever before.
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The protein folding ‘speed limit’
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Constructing the equilibrium ensemble of folding pathways from short off-equilibrium simulations
Noé, F., Schütte, C., Vanden-Eijnden, E., Reich, L., & Weikl, T. R. (2009) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0905466106 · Cited by 820
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Self-citationScreen Savers of the World Unite!
Shirts, M., & Pande, V. S. (2000) · Science · doi:10.1126/science.290.5498.1903 · Cited by 531
Self-citationAccelerating molecular dynamic simulation on graphics processing units
Friedrichs, M. S., Eastman, P., Vaidyanathan, V., Houston, M., Legrand, S., Beberg, A. L., Ensign, D. L., Bruns, C. M., & Pande, V. S. (2009) · Journal of Computational Chemistry · doi:10.1002/jcc.21209 · Cited by 529
Self-citationTransition networks for modeling the kinetics of conformational change in macromolecules
Noé, F., & Fischer, S. (2008) · Current Opinion in Structural Biology · doi:10.1016/j.sbi.2008.01.008 · Cited by 481
Transition Path Theory for Markov Jump Processes
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Markov models of molecular kinetics: Generation and validation
Prinz, J.-H., Wu, H., Sarich, M., Keller, B., Senne, M., Held, M., Chodera, J. D., Schütte, C., & Noé, F. (2011) · The Journal of Chemical Physics · doi:10.1063/1.3565032 · Cited by 1,275
PyEMMA 2: A Software Package for Estimation, Validation, and Analysis of Markov Models
Scherer, M. K., Trendelkamp-Schroer, B., Paul, F., Pérez-Hernández, G., Hoffmann, M., Plattner, N., Wehmeyer, C., Prinz, J.-H., & Noé, F. (2015) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5b00743 · Cited by 1,163
Identification of slow molecular order parameters for Markov model construction
Pérez-Hernández, G., Paul, F., Giorgino, T., De Fabritiis, G., & Noé, F. (2013) · The Journal of Chemical Physics · doi:10.1063/1.4811489 · Cited by 990
“…and validation The Journal of Chemical Physics 134, 174105 (2011); 10.1063/1.3565032 Slow dynamics in protein fluctuations revealed by time-structure based independent component analysis: The case of domain motions The Journal of Chemical Physics 134, 065101 (2011);…”
MethodInfluentialEverything you wanted to know about Markov State Models but were afraid to ask
Pande, V. S., Beauchamp, K., & Bowman, G. R. (2010) · Methods · doi:10.1016/j.ymeth.2010.06.002 · Cited by 698
Self-citationComplete reconstruction of an enzyme-inhibitor binding process by molecular dynamics simulations
Buch, I., Giorgino, T., & De Fabritiis, G. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1103547108 · Cited by 655
Metadata
- Authors
- Voelz, V. A., Bowman, G. R., Beauchamp, K., & Pande, V. S.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2010-01-13
- Volume
- 132
- Issue
- 5
- Pages
- 1526-1528
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W1990593157
- Cited by
- 503
- References
- 31
- FWCI
- 21.03
- Type
- journal article
- Language
- en
- Open access
- green
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