Replica state exchange metadynamics for improving the convergence of free energy estimates.
Metadynamics (MTD) is a powerful enhanced sampling method for systems with rugged energy landscapes. It constructs a bias potential in a predefined collective variable (CV) space to overcome barriers between metastable states. In bias-exchange MTD (BE-MTD), multiple replicas approximate the CV space by exchanging bias potentials (replica conditions) with the Metropolis-Hastings (MH) algorithm. We demonstrate that the replica-exchange rates and the convergence of free energy estimates of BE-MTD are improved by introducing the infinite swapping (IS) or the Suwa-Todo (ST) algorithms. Conceptually, IS and ST perform transitions in a replica state space rather than exchanges in a replica condition space. To emphasize this, the proposed scheme is called the replica state exchange MTD (RSE-MTD). Benchmarks were performed with alanine polypeptides in vacuum and water. For the systems tested in this work, there is no significant performance difference between IS and ST.
['Galvelis|Raimondas|R|', 'Sugita|Yuji|Y|']
D000409:Alanine D000465:Algorithms D056004:Molecular Dynamics Simulation D009010:Monte Carlo Method D010455:Peptides D013816:Thermodynamics
metadynamics free energy enhanced sampling infinite swapping Metropolis-Hastings algorithm Suwa-Todo algorithm