Biomolecular condensates, formed through the phase separation of intrinsically disordered proteins (IDPs), underpin a wide range of cellular processes. Many of these proteins contain prion-like domains (PLDs), low-complexity sequence regions enriched in aromatic residues, which assemble into condensates with viscoelastic properties. Beyond their thermal stability, condensates display a continuum of material states whose mechanical properties are thought to be crucial in regulating biological function. Notably, certain PLDs can undergo aging, where liquid-like droplets transition into solid- or glass-like states, a transformation associated with neurodegenerative disease. Characterizing the molecular determinants of these material properties is therefore critical to linking condensate behavior with function and pathology. To address this, computer simulations can serve as a useful tool in looking at material properties from a molecular perspective. In this work, we employ residue-resolution coarse-grained molecular dynamics simulations to explore the material properties of condensates formed by 140 PLD mutants spanning six proteins (hnRNPA1, TDP43, FUS, EWSR1, RBM14, and TIA1). Our simulations reveal scaling relationships between condensate viscosity and interfacial tension with the number/nature of sequence mutations. Interestingly, condensate viscosity scales with changes in critical temperature in a non-linear manner, indicating a complex coupling between sequence perturbations and macroscopic behavior. To uncover the mechanistic basis of these trends, we analyze the organization of residue-residue contacts within the dense phase, quantifying both interaction connectivity and density of condensate-stabilizing contacts, as well as chain dynamics and contact lifetimes. This integrated picture highlights the distinct molecular contributions that tune condensate material properties. By bridging sequence-level perturbations with emergent material properties, our framework provides new insights into the molecular code governing condensate behavior and offers a path toward predictive, experimentally consistent simulations.
Chew et al. (2026) studied this question.