Acceleration of generalized replica exchange with solute tempering simulations of large biological systems on massively parallel supercomputer

Abstract

AbstractGeneralized replica exchange with solute tempering (gREST) is one of the enhanced sampling algorithms for proteins or other systems with rugged energy landscapes. Unlike the replica‐exchange molecular dynamics (REMD) method, solvent temperatures are the same in all replicas, while solute temperatures are different and are exchanged frequently between replicas for exploring various solute structures. Here, we apply the gREST scheme to large biological systems containing over one million atoms using a large number of processors in a supercomputer. First, communication time on a multi‐dimensional torus network is reduced by matching each replica to MPI processors optimally. This is applicable not only to gREST but also to other multi‐copy algorithms. Second, energy evaluations, which are necessary for the multistate bennet acceptance ratio (MBAR) method for free energy estimations, are performed on‐the‐fly during the gREST simulations. Using these two advanced schemes, we observed 57.72 ns/day performance in 128‐replica gREST calculations with 1.5 million atoms system using 16,384 nodes in Fugaku. These schemes implemented in the latest version of GENESIS software could open new possibilities to answer unresolved questions on large biomolecular complex systems with slow conformational dynamics.