Physics-driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy

Various physics- and data-driven sequence-dependent protein coarse-grained models have been developed to study biomolecular phase separation and elucidate the dominant physicochemical driving forces. Here we present Mpipi, a multiscale coarse-grained model that describes almost quantitatively the change in protein critical temperatures as a function of amino acid sequence. The model is parameterized from both atomistic simulations and bioinformatics data and accounts for the dominant role of pi-pi and hybrid cation-pi/pi-pi interactions and the much stronger attractive contacts established by arginines than lysines. We provide a comprehensive set of benchmarks for Mpipi and seven other residue-level coarse-grained models against experimental radii of gyration and quantitative in vitro phase diagrams, demonstrating that Mpipi predictions agree well with experiments on both fronts. Moreover, Mpipi can account for protein-RNA interactions, correctly predicts the multiphase behavior of a charge-matched poly-arginine/poly-lysine/RNA system, and recapitulates experimental liquid-liquid phase separation trends for sequence mutations on FUS, DDX4 and LAF-1 proteins.

Automated summary

Mpipi is a multiscale coarse-grained protein model that quantitatively describes the change in protein critical temperatures with respect to amino acid sequence, considering the dominant role of pi-pi and hybrid cation-pi/pi-pi interactions, and the stronger attractive contacts of arginines compared to lysines. Experimental benchmarks demonstrate that Mpipi predictions are in good agreement with experimental results, and the model can accurately predict protein-RNA interactions and liquid-liquid phase separation trends of proteins with sequence mutations.