Enriching stabilizing mutations through automated analysis of molecular dynamics simulations using BoostMut.

ABSTRACT: Thermostability is a critical goal in protein engineering for applications of biocatalysts and biomedicines. Despite striking advances in biomolecular predictive modeling, reliably identifying stabilizing mutations remains challenging. Previously, molecular dynamics (MD) simulations and visual inspection have been used as a secondary filter to improve the success rate of mutations pre-selected by thermostability algorithms. However, this approach suffers from low throughput and subjectivity. Here, we introduce Biophysical Overview of Optimal Stabilizing Mutations (BoostMut), a computational tool that standardizes and automates mutation filtering by analyzing dynamic structural features from MD. BoostMut formalizes the principles guiding manual verification, providing a consistent and repro

SUBMITTER: Korbeld KT 

PROVIDER: S-EPMC12514941 | biostudies-literature | 2025 Nov

REPOSITORIES: biostudies-literature