Efficient use of non-equilibrium measurement to estimate free energy differences for molecular systems

TL;DR

This paper introduces an improved method for estimating free energy differences in molecular systems using non-equilibrium data, significantly reducing data requirements by analyzing statistical properties of Jarzynski's equality.

Contribution

The authors develop an automated analysis technique that leverages the statistical behavior of Jarzynski's equality to obtain accurate free energy estimates with less data.

Findings

Achieves accurate free energy estimates with 6-15 times less data

Systematic analysis of bias due to finite sample size

Enhanced use of raw data improves estimate reliability

Abstract

A promising method for calculating free energy differences Delta F is to generate non-equilibrium data via ``fast-growth'' simulations or experiments -- and then use Jarzynski's equality. However, a difficulty with using Jarzynski's equality is that Delta F estimates converge very slowly and unreliably due to the nonlinear nature of the calculation -- thus requiring large, costly data sets. Here, we present new analyses of non-equilibrium data from various simulated molecular systems exploiting statistical properties of Jarzynski's equality. Using a fully automated procedure, with no user-input parameters, our results suggest that good estimates of Delta F can be obtained using 6-15 fold less data than was previously possible. Systematizing and extending previous work [1], the new results exploit the systematic behavior of bias due to finite sample size. A key innovation is better use of the more statistically reliable information available from the raw data.