蒙特卡罗方法
大正则系综
统计物理学
正则系综
成核
动力学蒙特卡罗方法
动态蒙特卡罗方法
蒙特卡罗分子模拟
物理
计算机科学
马尔科夫蒙特卡洛
热力学
数学
统计
作者
Aliasghar Sepehri,Gül H. Zerze
出处
期刊:
[Cold Spring Harbor Laboratory]
日期:2025-06-09
标识
DOI:10.1101/2025.06.06.658304
摘要
Abstract We present a Monte Carlo framework for simulating the nucleation of biomolecular condensates in the grand canonical ensemble, which overcomes the limitations of fixed particle number and allows direct control of the dilute-phase concentration. Our approach combines conformation sampling with bias-enhanced cluster size sampling, enabling accurate sampling of individual cluster sizes in various conformations. Our method resolves nucleation free energy surfaces and is capable of capturing both classical and nonclassical nucleation mechanisms. We validated our method by reproducing structural properties of disordered proteins across a diverse benchmark set and by applying it to study nucleation in two phase-separating proteins, FUS-LC and NDDX4, using both HPS and MPIPI coarse-grained force fields. While both proteins exhibit classical nucleation behavior under the HPS model, only FUS-LC remains classical with MPIPI. In contrast, NDDX4 shows a distinctly nonclassical nucleation pathway under MPIPI, characterized by a metastable intermediate state near the cluster size of 53 protein chains. Morphological analysis reveals that clusters up to this point are compact and spherical, whereas larger clusters adopt a nonspherical, two-lobed geometry indicative of frustrated coalescence. These findings underscore the critical role of sequence composition and force field parameterization in shaping nucleation pathways and demonstrate the utility of our framework for uncovering complex, mechanism-rich free energy landscapes in biomolecular condensation.
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