  Methods that combine collective variable (CV) based enhanced sampling and
global tempering approaches are used in speeding-up the conformational sampling
and free energy calculation of large and soft systems with a plethora of energy
minima. In this paper, a new method of this kind is proposed in which the
well-sliced metadynamics approach (WSMTD) is united with Replica Exchange with
Solute Tempering (REST2) method. WSMTD employs a divide-and-conquer strategy
wherein high-dimensional slices of a free energy surface are independently
sampled and combined. The method enables one to accomplish a controlled
exploration of the CV-space with a restraining bias as in umbrella sampling
(US), and enhance-sampling of one or more orthogonal CVs using a metadynamics
(MTD) like bias. The new hybrid method proposed here enables boosting the
sampling of more slow degrees of freedom in WSMTD simulations, without the need
to specify associated CVs, through a replica exchange scheme within the
framework of REST2. The high-dimensional slices of the probability
distributions of CVs computed from the united WSMTD and REST2 simulations are
subsequently combined using the weighted histogram analysis method (WHAM) to
obtain the free energy surface. We show that the new method proposed here is
accurate, improves the conformational sampling, and achieves quick convergence
in free energy estimates. We demonstrate this by computing the conformational
free energy landscapes of solvated alanine tripeptide and Trp-cage mini protein
in explicit water.
