Abstract
Computer simulation provides an increasingly realistic picture of large-scale conformational change of proteins, but investigations remain fundamentally constrained by the femtosecond timestep of molecular dynamics simulations. For this reason, many biologically interesting questions cannot be addressed using accessible state-of-the-art computational resources. Here, we report the development of an all-atom Monte Carlo approach that permits the modelling of the large-scale conformational change of proteins using standard off-the-shelf computational hardware and standard all-atom force fields. We demonstrate extensive thermodynamic characterization of the folding process of the α-helical Trp-cage, the Villin headpiece and the β-sheet WW-domain. We fully characterize the free energy landscape, transition states, energy barriers between different states, and the per-residue stability of individual amino acids over a wide temperature range. We demonstrate that a state-of-the-art intramolecular force field can be combined with an implicit solvent model to obtain a high quality of the folded structures and also discuss limitations that still remain.
Highlights
Two important questions naturally arise in the use of Monte Carlo methods: (1) will the combination of an accurate intramolecular force field, developed for all-atom molecular dynamics (MD) simulations, together with the implicit solvent models yield to quantitative results, and (2) can the free-energy landscape be sampled sufficiently well, relying on simplified moves defined in MC protocols independently on the forces on the atoms?
We focus on the reproducing of their folding free energy landscapes, barriers, and transition states in order to demonstrate thermodynamic characterization of small proteins using Monte Carlo simulations with an all-atom force field
We start with the Trp-cage protein, being the smallest peptide investigated, and focus on the Villin headpiece and WW-domain to show transferability and efficiency of the all-atom force field in Monte Carlo approach
Summary
It is important to investigate whether state-of-the-art force fields, that were originally designed for explicit solvent simulations, can be employed in accurate and predictive MC In this context, two important questions naturally arise in the use of Monte Carlo methods: (1) will the combination of an accurate intramolecular force field, developed for all-atom MD simulations, together with the implicit solvent models yield to quantitative results, and (2) can the free-energy landscape be sampled sufficiently well, relying on simplified moves defined in MC protocols independently on the forces on the atoms?. We aim to answer these two questions by employing a Monte Carlo based p rotocol[54], using an accurate implicit solvent model and a transferable all-atom intramolecular AMBER99SB*-ILDN force field[55] This force field, in the most cases in the combination with explicit water, has been shown to perform well in mimicking experimental data using MD simulations of different peptides[24,55]. We focus on the reproducing of their folding free energy landscapes, barriers, and transition states in order to demonstrate thermodynamic characterization of small proteins using Monte Carlo simulations with an all-atom force field
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