Feito Alejandro, Sanchez-Burgos Ignacio, Tejero Ignacio, Sanz Eduardo, Rey Antonio, Collepardo-Guevara Rosana, Tejedor Andrés R, Espinosa Jorge R
Department of Physical-Chemistry, Complutense University of Madrid, Madrid, Spain.
Maxwell Centre, Cavendish Laboratory, Department of Physics, University of Cambridge, Cambridge, United Kingdom.
PLoS Comput Biol. 2025 Jan 13;21(1):e1012737. doi: 10.1371/journal.pcbi.1012737. eCollection 2025 Jan.
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. Specifically, we assess the HPS, HPS-cation-π, HPS-Urry, CALVADOS2, Mpipi, and Mpipi-Recharged models in their predictions of the condensate saturation concentration, critical solution temperature, and condensate viscosity of the A1-LCD variants. Our analyses demonstrate that, among the tested models, Mpipi, Mpipi-Recharged, and CALVADOS2 provide accurate descriptions of the critical solution temperatures and saturation concentrations for the multiple A1-LCD variants tested. Regarding the prediction of material properties for condensates of A1-LCD and its variants, Mpipi-Recharged stands out as the most reliable model. Overall, this study benchmarks a range of residue-resolution coarse-grained models for the study of the thermodynamic stability and material properties of condensates and establishes a direct link between their performance and the ranking of intermolecular interactions these models consider.
蛋白质和核酸的细胞内液-液相分离（LLPS）是细胞对其成分进行区室化并执行基本生物学功能的一种基本机制。分子模拟在深入了解驱动这一现象的物理化学过程方面发挥着关键作用。在本研究中，我们系统地比较了六种最先进的序列依赖性残基分辨率模型，以评估它们在再现由hnRNPA1蛋白（A1-LCD）的低复杂性结构域（LCD）的七个变体形成的凝聚物的相行为和材料特性方面的性能，A1-LCD是一种与应激颗粒的病理性液体-固体转变有关的蛋白质。具体而言，我们评估了HPS、HPS-阳离子-π、HPS-Urry、CALVADOS2、Mpipi和Mpipi-Recharged模型对A1-LCD变体的凝聚物饱和浓度、临界溶解温度和凝聚物粘度的预测。我们的分析表明，在测试的模型中，Mpipi、Mpipi-Recharged和CALVADOS2对测试的多个A1-LCD变体的临界溶解温度和饱和浓度提供了准确的描述。关于A1-LCD及其变体凝聚物的材料特性预测，Mpipi-Recharged是最可靠的模型。总体而言，本研究对一系列用于研究凝聚物的热力学稳定性和材料特性的残基分辨率粗粒度模型进行了基准测试，并建立了它们的性能与这些模型所考虑的分子间相互作用排名之间的直接联系。
