Improving Efficiency in SMD Simulations Through a Hybrid Differential Relaxation Algorithm

Abstract

The fundamental object for studying a (bio)chemical reaction obtained from simulations is the free energy profile, which can be directly related to experimentally determined properties. Although quite accurate hybrid quantum (DFT based)-classical methods are available, achieving statistically accurate and well converged results at a moderate computational cost is still an open challenge. Here, we present and thoroughly test a hybrid differential relaxation algorithm (HyDRA), which allows faster equilibration of the classical environment during the nonequilibrium steering of a (bio)chemical reaction. We show and discuss why (in the context of Jarzynski’s Relationship) this method allows obtaining accurate free energy profiles with smaller number of independent trajectories and/or faster pulling speeds, thus reducing the overall computational cost. Moreover, due to the availability and straightforward implementation of the method, we expect that it will foster theoretical studies of key enzymatic processes.