Enhanced sampling based on slow variables of trajectory mapping

Abstract

Most current enhanced sampling (ES) algorithms attempt to bias a potential energy surface based on preset slow collective variables to improve simulation efficiency. However, due to difficulty in obtaining slow variables in complex molecular systems, approximate slow variables are usually applied in ES, which often fail to achieve the expected high efficiency and sufficient accuracy when reconstructing equilibrium properties. In this paper, we demonstrate that the trajectory mapping (TM) technique has the potential to provide the required slow variables for ES.We illustrate the application of a typical ES algorithm (metadynamics) based on the slow variables constructed from the TM in a hairpin peptide system. In this system, both the equilibrium properties and slow dynamics are accurately obtained within approximately two to three orders of magnitude shorter simulation time than in regular molecular dynamics simulation.