Robust Automated Truncation Point Selection for Molecular Simulations.

ABSTRACT: Quantities calculated from molecular simulations are often subject to an initial bias due to unrepresentative starting configurations. Initial data are usually discarded to reduce bias. Chodera's method for automated truncation point selection [J. Chem. Theory Comput. 2016, 12, 4, 1799-1805] is popular but has not been thoroughly assessed. We reformulate White's marginal standard error rule to provide a spectrum of truncation point selection heuristics that differ in their treatment of autocorrelation. These include a method effectively equivalent to Chodera's. We test these methods on ensembles of synthetic time series modeled on free energy change estimates from long absolute binding free energy calculations. Methods that more thoroughly account for autocorrelation often show late and va

SUBMITTER: Clark F 

PROVIDER: S-EPMC11736681 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature