The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Hidden complexity of free energy surfaces for peptide (protein) folding
Open accessAbstract
An understanding of the thermodynamics and kinetics of protein folding requires a knowledge of the free energy surface governing the motion of the polypeptide chain. Because of the many degrees of freedom involved, surfaces projected on only one or two progress variables are generally used in descriptions of the folding reaction. Such projections result in relatively smooth surfaces, but they could mask the complexity of the unprojected surface. Here we introduce an approach to determine the actual (unprojected) free energy surface and apply it to the second β-hairpin of protein G, which has been used as a model system for protein folding. The surface is represented by a disconnectivity graph calculated from a long equilibrium folding-unfolding trajectory. The denatured state is found to have multiple low free energy basins. Nevertheless, the peptide shows exponential kinetics in folding to the native basin. Projected surfaces obtained from the present analysis have a simple form in agreement with other studies of the β-hairpin. The hidden complexity found for the β-hairpin surface suggests that the standard funnel picture of protein folding should be revisited.
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From Levinthal to pathways to funnels
Dill, K. A., & Chan, H. S. (1997) · Nature Structural & Molecular Biology · doi:10.1038/nsb0197-10 · Cited by 2,293
Cited by
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
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
“gle reference structure, the radius of gyration, or pre-selected distances or angles are often not good indicators of the slow eigenfunctions, and thus bear the danger of disguising the slow kinetics [45, 61, 56]. In order to avoid this, Markov model construction has focused in the last years focused on the other extr…”
BackgroundConstructing 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
Schwantes, C. R., & Pande, V. S. (2013) · Journal of Chemical Theory and Computation · doi:10.1021/ct300878a · Cited by 597
Transition 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
Metadata
- Authors
- Krivov, S. V., & Karplus, M.
- Venue
- Proceedings of the National Academy of Sciences
- Published
- 2004-10-04
- Volume
- 101
- Issue
- 41
- Pages
- 14766-14770
- ISSN
- 0027-8424 (ISSN-L)
- 1091-6490
- OpenAlex
- W2072290134
- Cited by
- 358
- References
- 1
- FWCI
- 5.03
- Type
- journal article
- Language
- en
- Open access
- green
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