Accurate Protein-Folding Transition-Path Statistics from a Simple Free-Energy Landscape

William M. Jacobs, Eugene I. Shakhnovich

Research output: Contribution to journalArticle

4 Scopus citations

Abstract

A central goal of protein-folding theory is to predict the stochastic dynamics of transition paths - the rare trajectories that transit between the folded and unfolded ensembles - 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 "topological configuration" 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.

Original languageEnglish (US)
Pages (from-to)11126-11136
Number of pages11
JournalJournal of Physical Chemistry B
Volume122
Issue number49
DOIs
StatePublished - Dec 13 2018

All Science Journal Classification (ASJC) codes

  • Physical and Theoretical Chemistry
  • Surfaces, Coatings and Films
  • Materials Chemistry

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