Mammen Regy Roshan, Zheng Wenwei, Mittal Jeetain
Department of Chemical and Biomolecular Engineering, Lehigh University, Bethlehem, PA, United States.
College of Integrative Sciences and Arts, Arizona State University, Mesa, AZ, United States.
Methods Enzymol. 2021;646:1-17. doi: 10.1016/bs.mie.2020.07.009. Epub 2020 Aug 17.
The formation of membraneless organelles (MLOs) via liquid-liquid phase separation (LLPS) of biomolecules is a topic that has garnered significant attention in the scientific community recently. Experimental studies have revealed that intrinsically disordered proteins (IDPs) may play a major role in driving the formation of these droplets via LLPS by forming multivalent interactions between amino acids. To quantify these interactions is an arduous task as it is difficult to investigate these interactions at the amino acid level using currently available experimental tools. It becomes necessary to complement experimental studies using appropriate computational methods such as coarse-grained models of IDPs that can allow one to simulate biomolecular LLPS using general-purpose hardware. Here, we summarize our coarse-grained modeling framework that uses a single bead per amino acid resolution and the co-existence sampling technique to study sequence-specific protein phase separation using molecular dynamics simulations. We further discuss the caveats and technicalities, which one must consider while using this method to obtain thermodynamic phase diagrams. To ease the learning curve, we provide our implementations of the coarse-grained potentials in the HOOMD-Blue simulation package and associated python scripts to run such simulations.
通过生物分子的液-液相分离(LLPS)形成无膜细胞器(MLOs)是近年来科学界备受关注的一个话题。实验研究表明,内在无序蛋白(IDP)可能通过氨基酸之间形成多价相互作用,在驱动LLPS形成这些液滴过程中发挥主要作用。量化这些相互作用是一项艰巨的任务,因为使用现有的实验工具很难在氨基酸水平上研究这些相互作用。因此,有必要使用适当的计算方法(如IDP的粗粒度模型)来补充实验研究,这些模型可以让人们使用通用硬件模拟生物分子的LLPS。在这里,我们总结了我们的粗粒度建模框架,该框架使用每个氨基酸分辨率的单个珠子和共存采样技术,通过分子动力学模拟研究序列特异性蛋白质相分离。我们进一步讨论了在使用此方法获得热力学相图时必须考虑的注意事项和技术细节。为了降低学习难度,我们在HOOMD-Blue模拟包中提供了粗粒度势的实现以及运行此类模拟的相关Python脚本。