Discrete Molecular Dynamics: An Efficient And Versatile Simulation Method For Fine Protein Characterization

Until now it has been impractical to observe protein
folding in
silico for proteins larger than 50 residues. Limitations of both force
field accuracy and computational efficiency make the folding problem
very challenging. Here we employ discrete molecular dynamics (DMD)
simulations with an all-atom force field to fold fast-folding proteins.
We extend the DMD force field by introducing long-range electrostatic
interactions to model salt-bridges and a sequence-dependent semiempirical
potential accounting for natural tendencies of certain amino acid
sequences to form specific secondary structures. We enhance the computational
performance by parallelizing the DMD algorithm. Using a small number
of commodity computers, we achieve sampling quality and folding accuracy
comparable to the explicit-solvent simulations performed on high-end
hardware. We demonstrate that DMD can be used to observe equilibrium
folding of villin headpiece and WW domain, study two-state folding
kinetics, and sample near-native states in ab initio folding of proteins
of ∼100 residues.