Gaussian accelerated molecular dynamics with the weighted ensemble method: a hybrid method improves thermodynamics and kinetics sampling

Abstract

Gaussian accelerated molecular dynamics (GaMD) is a well-established enhanced sampling method for molecular dynamics (MD) simulations that effectively samples the potential energy landscape of the system by adding a boost potential, which smoothens the surface and lowers energy barriers between states. Although equilibrium properties can be recovered exactly in principle, GaMD is unable to give time-dependent properties such as kinetics directly. On the other hand, the weighted ensemble (WE) method can efficiently sample transitions between states with its many weighted trajectories, which directly yield rates and pathways. However, the performance of the WE method (i.e., convergence and efficiency) depends heavily on its initial conditions or initial sampling of the potential energy landscape. Hence, we have developed a hybrid method that combines the two methods, wherein GaMD is first used to sample the potential energy landscape of the system, and the WE method is subsequently used to further sample the potential energy landscape and kinetic properties of interest. We show that the hybrid method can sample both thermodynamic and kinetic properties more accurately and quickly compared to using either method alone.