@article {doi:10.1021/acs.jpcb.8b05842,
	title = {Accurate Protein-Folding Transition-Path Statistics from a Simple Free-Energy Landscape},
	journal = {The Journal of Physical Chemistry B},
	volume = {122},
	year = {2018},
	note = {PMID: 30091592},
	pages = {11126-11136},
	abstract = {A central goal of protein-folding theory is to predict the stochastic dynamics of transition paths{\textemdash}the rare trajectories that transit between the folded and unfolded ensembles{\textemdash}using only thermodynamic information, such as a low-dimensional equilibrium free-energy landscape. However, commonly used one-dimensional landscapes typically fall short of this aim, because an empirical coordinate-dependent diffusion coefficient has to be fit to transition-path trajectory data in order to reproduce the transition-path dynamics. We show that an alternative, first-principles free-energy landscape predicts transition-path statistics that agree well with simulations and single-molecule experiments without requiring dynamical data as an input. This {\textquotedblleft}topological configuration{\textquotedblright} model assumes that distinct, native-like substructures assemble on a time scale that is slower than native-contact formation but faster than the folding of the entire protein. Using only equilibrium simulation data to determine the free energies of these coarse-grained intermediate states, we predict a broad distribution of transition-path transit times that agrees well with the transition-path durations observed in simulations. We further show that both the distribution of finite-time displacements on a one-dimensional order parameter and the ensemble of transition-path trajectories generated by the model are consistent with the simulated transition paths. These results indicate that a landscape based on transient folding intermediates, which are often hidden by one-dimensional projections, can form the basis of a predictive model of protein-folding transition-path dynamics.},
	doi = {10.1021/acs.jpcb.8b05842},
	url = {https://doi.org/10.1021/acs.jpcb.8b05842},
	author = {Jacobs, William M. and Shakhnovich, EugeneI.}
}
