@article{61,
  author = {Jerelle Joseph and Aleks Reinhardt and Anne Aguirre and Pin Chew and Kieran Russell and Jorge Espinosa and Adiran Garaizar and Rosana Collepardo-Guevara},
  title = {Physics-driven coarse-grained model for biomolecular phase separation with near-quantitative accuracy.},
  abstract = {<p>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 parameterised from both atomistic simulations and bioinformatics data and accounts for the dominant role of - and hybrid cation-/- 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; Mpipi predictions agree well with experiment on both fronts. Moreover, it can account for protein-RNA interactions, correctly predicts the multiphase behaviour of a charge-matched poly-arginine/poly-lysine/RNA system, and recapitulates experimental LLPS trends for sequence mutations on FUS, DDX4 and LAF-1 proteins.</p>
},
  year = {2021},
  journal = {Nature computational science},
  volume = {1},
  pages = {732-743},
  issn = {2662-8457},
  doi = {10.1038/s43588-021-00155-3},
  language = {eng},
}