Crowding effects on biomolecular processes: Computational advances and challenges.

Abstract

Macromolecular crowding is a fundamental feature of the cellular environment that strongly influences biomolecular structure, dynamics, and phase behavior. Despite its significance, it has been a challenge to represent and capture the effects of the crowded environment accurately and sufficiently in molecular simulations. This review discusses the challenges and recent progress in the development of computational approaches for modelling and simulating biomolecular processes in a crowded milieu. The review focuses on the new view of crowding, which highlights the interplay of entropic and enthalpic effects. Emerging data-driven strategies are discussed for improving force-field representations and predicting biomolecular behavior in crowded media, with particular emphasis on generating synthetic datasets, using simulation-derived descriptors, and employing combinatorial frameworks for unravelling microscopic origins of crowding.