StateWeaver: Tracing State Changes in Adaptive Molecular Dynamics

Abstract

Adaptive molecular dynamics produces many short simulations that begin from frames of earlier runs. This branching improves sampling, but it makes a simple question hard to answer: when a state-transition probability changes, which simulations produced the change? StateWeaver joins a transition comparison with the simulation lineage. It covers the supplied state assignments for free Aβ42, Aβ42 with tramiprosate, and Aβ42 with 3-sulfopropanoic acid: 955 simulations and 1,899,875 assigned frames in each of three Markov-state models. Selecting a transition shows the treatment and baseline probabilities, their difference, a descriptive standard error, event counts, and the runs in which the transition occurs. For example, in the 3-state model, the SPA 0→1 selection reduces 319 simulations to 16 runs containing 209 observed transitions. The difference is +0.10 percentage points with a standard error of 0.18, so it remains uncertain. StateWeaver also disables molecular explanations when trajectory coordinates are absent. The result is a focused way to move from an ensemble-level difference back to the simulations behind it without claiming more than the available data show