Abstract
To address the large gap between time scales that can be easily reached by molecular simulations and those required to understand protein dynamics, we present a rapid self-consistent approximation of the side chain free energy at every integration step. In analogy with the adiabatic Born-Oppenheimer approximation for electronic structure, the protein backbone dynamics are simulated as preceding according to the dictates of the free energy of an instantaneously-equilibrated side chain potential. The side chain free energy is computed on the fly, allowing the protein backbone dynamics to traverse a greatly smoothed energetic landscape. This computation results in extremely rapid equilibration and sampling of the Boltzmann distribution. Our method, termed Upside, employs a reduced model involving the three backbone atoms, along with the carbonyl oxygen and amide proton, and a single (oriented) side chain bead having multiple locations reflecting the conformational diversity of the side chain’s rotameric states. We also introduce a novel, maximum-likelihood method to parameterize the side chain interactions using protein structures. We demonstrate state-of-the-art accuracy for predicting χ1 rotamer states while consuming only milliseconds of CPU time. Our method enables rapidly equilibrating coarse-grained simulations that can nonetheless contain significant molecular detail. We also show that the resulting free energies of the side chains are sufficiently accurate for de novo folding of some proteins.
Highlights
Two major challenges must be overcome in order to accurately simulate protein dynamics
To address the large gap between time scales that can be reached by molecular simulations and those required to understand protein dynamics, we present a rapid self-consistent approximation of the side chain free energy at every integration step
To address the large gap between time scales that can be reached by molecular simulations and those required to understand protein dynamics, we propose a new methodology that computes a self-consistent approximation of the side chain free energy at every integration step
Summary
Two major challenges must be overcome in order to accurately simulate protein dynamics. The sampling challenge is addressed here by integrating out the side chain degrees of freedom to produce a coarse-grained configuration defined just in terms of the backbone N, Cα, and C atoms. Backbone motions evolve on a smoother free energy surface with greatly reduced side chain rattling (molecular friction) compared to that for standard all-atom molecular dynamics simulations. We do not follow the customary process of matching the energies of the coarse-grained model to approximate the already inexact energies of atomistic force fields or try to interpret raw statistics for the distribution of interatomic distances in the Protein Data Bank (PDB) [1] along with a reference state [2]. Our side chain interaction energies are determined as those that best reproduce the side chain conformations observed in the PDB, given the native-state backbone configurations. We search for an energy function that assigns on average the highest probability to the native χ1 rotamer
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
