Joseph Jerelle A, Reinhardt Aleks, Aguirre Anne, Chew Pin Yu, Russell Kieran O, Espinosa Jorge R, Garaizar Adiran, Collepardo-Guevara Rosana
Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, CB2 1EW, UK.
Department of Physics, University of Cambridge, Cambridge, CB3 0HE, UK.
Nat Comput Sci. 2021 Nov;1(11):732-743. doi: 10.1038/s43588-021-00155-3. Epub 2021 Nov 22.
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.
为了研究生物分子相分离并阐明主要的物理化学驱动力，人们已经开发了各种基于物理和数据驱动的、依赖于序列的蛋白质粗粒度模型。在此，我们提出了Mpipi，这是一种多尺度粗粒度模型，它几乎可以定量地描述蛋白质临界温度随氨基酸序列的变化。该模型由原子模拟和生物信息学数据进行参数化，考虑了阳离子-π和混合阳离子-π相互作用的主导作用，以及精氨酸比赖氨酸形成的更强的吸引性接触。我们针对Mpipi和其他七个残基水平的粗粒度模型，根据实验回转半径和定量体外相图提供了一套全面的基准测试；Mpipi在这两方面的预测都与实验结果吻合良好。此外，它可以解释蛋白质与RNA的相互作用，正确预测电荷匹配的聚精氨酸/聚赖氨酸/RNA系统的多相行为，并概括了FUS、DDX4和LAF-1蛋白序列突变的实验LLPS趋势。
