Predicting the morphology of multiphase biomolecular condensates from protein interaction networks

TL;DR

This paper presents a computational framework to predict the morphology of multiphase biomolecular condensates based on protein interaction networks, highlighting the role of a shared protein species as a surfactant.

Contribution

It introduces a novel numerical approach combining Monte Carlo simulations and density functional theory to predict condensate interfaces from interaction networks.

Findings

Shared protein species can act as a tunable surfactant.

Low concentrations of shared species can trigger wetting transitions.

Wetting phase diagrams can be explained by simple adsorption models.

Abstract

Phase-separated biomolecular condensates containing proteins and RNAs can assemble into higher-order structures by forming thermodynamically stable interfaces between immiscible phases. Using a minimal model of a protein/RNA interaction network, we demonstrate how a "shared" protein species that partitions into both phases of a multiphase condensate can function as a tunable surfactant that modulates the interfacial properties. We use Monte Carlo simulations and free-energy calculations to identify conditions under which a low concentration of this shared species is sufficient to trigger a wetting transition. We also describe a numerical approach based on classical density functional theory to predict concentration profiles and surface tensions directly from the model protein/RNA interaction network. Finally, we show that the wetting phase diagrams that emerge from our calculations can be understood in terms of a simple model of selective adsorption to a fluctuating interface. Our work shows how a low-concentration protein species might function as a biological switch for regulating multiphase condensate morphologies.