BAR‐Based Multi‐Dimensional Nonequilibrium Pulling for Indirect Construction of QM/MM Free Energy Landscapes: Varying the QM Region. Issue 10 (8th September 2021) - Sun, Zhaoxi; Liu, Zhirong
Abstract: The indirect free energy simulation at quantum mechanics (QM)/ molecular mechanics (MM) levels provides a feasible alternative to direct QM/MM simulations. The main idea under the indirect method is constructing a thermodynamic cycle, exploring the configurational space under a cheaper but less accurate QM level, and performing an alchemical correction to obtain the thermodynamics under an accurate but computationally demanding QM level. In the authors' previous works, a multi‐dimensional nonequilibrium free energy simulation framework was developed to obtain QM/MM free energy landscapes indirectly, where the QM theory is varied but the other details of the multi‐scale treatment remain unchanged. In this work, the possibility of changing the region for electronic structure calculations in the multi‐scale treatment is explored. Numerical tests are performed for the conformational change in a biologically relevant peptide in vacuo and in solution, and the QM region and QM level are varied simultaneously. Unidirectional and bidirectional equilibrium perturbations are also performed for comparison. The indirect estimates from the nonequilibrium perturbation framework are almost identical to the direct results, while the indirect equilibrium estimates show obvious deviations from the direct references. They further derive the acceleration ratio of the indirect scheme to understand when the indirect scheme prevails. Abstract : A general Bennett acceptance ratio (BAR)‐based multi‐dimensional nonequilibrium perturbation framework for Hamiltonian variations is introduced to change various details in the multi‐scale treatment. Numerical experiments show that the indirect nonequilibrium free energy scheme provides virtually identical results as direct simulations. The acceleration ratio of the indirect scheme is derived to understand its behavior and further guide the design of simulation protocols.