Mean force based temperature accelerated sliced sampling: Efficient reconstruction of high dimensional free energy landscapes.

Abstract

Temperature accelerated sliced sampling (TASS) is an efficient method to compute high dimensional free energy landscapes. The original TASS method employs the weighted histogram analysis method (WHAM) which is an iterative post-processing to reweight and stitch high dimensional probability distributions in sliced windows that are obtained in the presence of restraining biases. The WHAM necessitates that TASS windows lie close to each other for proper overlap of distributions and span the collective variable space of interest. On the other hand, increase in number of TASS windows implies more number of simulations, and thus it affects the efficiency of the method. To overcome this problem, we propose herein a new mean-force (MF) based reweighting scheme called TASS-MF, which enables accurate computation with a fewer number of windows devoid of the WHAM post-processing. Application of the technique is demonstrated for alanine di- and tripeptides in vacuo to compute their two- and four-dimensional free energy landscapes, the latter of which is formidable in conventional umbrella sampling and metadynamics. The landscapes are computed within a kcal mol-1 accuracy, ensuring a safe usage for broad applications in computational chemistry.