Avoiding non-equilibrium effects in adaptive biasing force calculations. Issue 5 (24th March 2021) - Miao, Mengyao; Fu, Haohao; Zhang, Hong; Shao, Xueguang; Chipot, Christophe; Cai, Wensheng
ABSTRACT: When using the adaptive biasing force (ABF) algorithm in free-energy calculations, unbiased sampling is performed across the transition coordinate to estimate the biasing force ( F bias ). In practice, however, setting the number of molecular dynamics steps ( N samples ) that precede the application of the time-dependent bias is arbitrary. In this paper, we find that N samples has a significant effect on the outcome of the free-energy calculation. When N samples is too small, marked non-equilibrium effects may occur, conducive to slow convergence, or possibly erroneous results. This phenomenon is observed in a variety of prototypical cases. Conversely, setting arbitrarily N samples to an exaggeratedly large value implies extra computational efforts. To avoid possible non-equilibrium artifacts while maintaining computational effectiveness, we propose a reliable scheme to make an appropriate choice of N samples in ABF-based free-energy calculations, resting on the evolution F bias as a function of N samples . Monitoring the latter, a value of N samples that minimises the computational cost while guaranteeing convergence of F bias can be determined. This method offers a safeguard for reliable free-energy calculations using ABF-based algorithms.