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. However, GaMD is unable to directly give time-dependent properties like kinetics. On the other hand, the weighted ensemble (WE) method can efficiently sample transitions between states with its many weighted trajectories, which directly gives us rates and pathways. However, the WE method's performance (i.e., convergence and efficiency) is heavily dependent on its initial conditions or initial sampling of the potential energy landscape. Hence, we have developed a hybrid method that combines the two methods. GaMD is first used to sample the potential energy landscape of the system and then the WE method is used to further sample the potential energy landscape and kinetic properties of interest. We demonstrate the effectiveness of the hybrid method with alanine dipeptide and chignolin, which show that the hybrid method is able to sample both thermodynamic and kinetic properties of biomolecules more accurately and quickly compared to using one method by itself. This new hybrid enhanced sampling method will also allow the state-of-the-art force fields to be efficiently tested and will speed up the development of these force fields, which will ultimately be used to predict and validate experimental results.

Gaussian accelerated molecular dynamics (GaMD) with the weighted ensemble (WE) method: Improved enhanced sampling of thermodynamics and kinetics

ACS Fall 2021

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