Benchmarking residue-resolution protein coarse-grained models for simulations of biomolecular condensates.

Intracellular liquid-liquid phase separation (LLPS) of proteins and nucleic acids is a fundamental mechanism by which cells compartmentalize their components and perform essential biological functions. Molecular simulations play a crucial role in providing microscopic insights into the physicochemical processes driving this phenomenon. In this study, we systematically compare six state-of-the-art sequence-dependent residue-resolution models to evaluate their performance in reproducing the phase behaviour and material properties of condensates formed by seven variants of the low-complexity domain (LCD) of the hnRNPA1 protein (A1-LCD)-a protein implicated in the pathological liquid-to-solid transition of stress granules.

Mechano-dependent sorbitol accumulation supports biomolecular condensate.

Condensed droplets of protein regulate many cellular functions, yet the physiological conditions regulating their formation remain largely unexplored. Increasing our understanding of these mechanisms is paramount, as failure to control condensate formation and dynamics can lead to many diseases. Here, we provide evidence that matrix stiffening promotes biomolecular condensation in vivo.

DomiRank Centrality reveals structural fragility of complex networks via node dominance.

Determining the key elements of interconnected infrastructure and complex systems is paramount to ensure system functionality and integrity. This work quantifies the dominance of the networks' nodes in their respective neighborhoods, introducing a centrality metric, DomiRank, that integrates local and global topological information via a tunable parameter. We present an analytical formula and an efficient parallelizable algorithm for DomiRank centrality, making it applicable to massive networks.