Quantitative prediction of biomolecular condensate kinetics and thermodynamics from finite-size molecular dynamics simulation

Abstract

Biomolecular condensates (condensates) are complex subcellular structures that emerge from the liquid-liquid phase separation of intrinsically disordered proteins (IDPs). Condensates have been implicated across both normal cellular function and disease. Given that the processes by which biomolecular condensates form are not fully understood, it is of interest to elucidate how the sequence composition of constituent IDPs influence their material properties and underlying physical behavior. However, modeling condensate systems via standard molecular dynamics (MD) techniques is challenging, as simulating under the canonical ensemble induces finite-size effects (FSE) which alter system thermodynamics and make accurately reproducing in vivo conditions difficult. In this thesis, I propose a methodology for predicting relevant kinetic and thermodynamic parameters of condensates in the macroscopic limit by applying the modified liquid droplet (MLD) framework to ensembles of finite-size MD simulation trajectories. To this end, I simulated three variants of heterogeneous nuclear ribonucleoprotein A1 low-complexity domain (HNRNPA1-LCD) across multiple system densities and volumes to calculate FSE-resolved nucleation barrier height, critical nucleus size, surface tension, and dilute phase density. I find that the emergent properties of HNRNPA1-LCD condensates are modulated by sequence variation, and that their observed behavior can be rationalized from the physicochemical properties of the introduced mutations. In addition, I find that the performance of the MLD framework is sensitive to simulation conditions, as high-density, low-volume regimes yield especially severe FSE that are difficult to resolve.