Speaker: Pilar Cossio, Ph.D.,
Tandem Group Leader, Max Planck Institute of Biophysics & and University of Antioquia
Topic: Recovering the rates from metadynamics simulations
Abstract: Metadynamics enables the efficient exploration of the conformational space of a system. However, the dynamic information of the system is lost due to the bias acceleration. Recovering the transition rates from these simulations is possible using infrequent metadynamics, where the average time of escape is, typically, estimated from a fit to a Poisson distribution using rescaled times. Here, we propose an alternative method for extracting the rate coefficients based on a maximum likelihood formalism when the unbinding times following Poisson statistics. However, when the dynamics is not Poissonian (e.g., because of the use of a poor collective variable), we propose a correction to the average rescaled time based on Kramers’ theory using Jarzynski’s equality to estimate the barrier. An additional approximation allows us to correct the individual rescaled times for recovering a Poissonian behavior. We tested the methods over a variety of systems, finding that the transition rates have equal or better accuracy than those extracted with other methods. In the cases where Poissonian statistics fail, we find that the corrections greatly improve the estimated rate.