Efficient and reproducible folding simulations of the Trp-cage protein with multiscale molecular dynamics

Abstract

Folding simulations are often time-consuming or highly sensitive to the initial conformation of the simulation even for mini protein like the Trp-cage. Here, we present a multiscale molecular dynamics method which appears to be both efficient and insensitive to the starting conformation based on the testing results from the Trp-cage protein. In this method the simulated system is simultaneously modeled on atoms and coarse-grained particles with incremental coarsening levels. The dynamics of coarse-grained particles are adapted to the recent trajectories of finer-grained particles instead of fixed and parameterized energy functions as used in previous coarse-grained models. In addition, the compositions of coarse-grained particles are allowed to be updated automatically based on the coherence during its history. Starting from the fully extended conformation and other several different conformations of the Trp-cage protein, our method successfully finds out the native-like conformations of the Trp-cage protein in the largest cluster of the trajectories in all of the eight performed simulations within at most 10 ns simulation time. The results show that approaches based on multiscale modeling are promising for ab initio protein structure prediction.