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迈向生物分子凝聚物的预测性粗粒度模拟。

Toward Predictive Coarse-Grained Simulations of Biomolecular Condensates.

作者信息

Liu Shuming, Wang Cong, Zhang Bin

机构信息

Department of Chemistry, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States.

出版信息

Biochemistry. 2025 Apr 15;64(8):1750-1761. doi: 10.1021/acs.biochem.4c00737. Epub 2025 Apr 2.

Abstract

Phase separation is a fundamental process that enables cellular organization by forming biomolecular condensates. These assemblies regulate diverse functions by creating distinct environments, influencing reaction kinetics, and facilitating processes such as genome organization, signal transduction, and RNA metabolism. Recent studies highlight the complexity of condensate properties, shaped by intrinsic molecular features and external factors such as temperature and pH. Molecular simulations serve as an effective approach to establishing a comprehensive framework for analyzing these influences, offering high-resolution insights into condensate stability, dynamics, and material properties. This review evaluates recent advancements in biomolecular condensate simulations, with a particular focus on coarse-grained 1-bead-per-amino-acid (1BPA) protein models, and emphasizes OpenABC, a tool designed to simplify and streamline condensate simulations. OpenABC supports the implementation of various coarse-grained force fields, enabling their performance evaluation. Our benchmarking identifies inconsistencies in phase behavior predictions across force fields, even though these models accurately capture single-chain statistics. This finding underscores the need for enhanced force field accuracy, achievable through enriched training data sets, many-body potentials, and advanced optimization techniques. Such refinements could significantly improve the predictive capacity of coarse-grained models, bridging molecular details with emergent condensate behaviors.

摘要

相分离是一种基本过程,通过形成生物分子凝聚物实现细胞组织化。这些聚集体通过创造独特环境、影响反应动力学以及促进基因组组织、信号转导和RNA代谢等过程来调节多种功能。最近的研究突出了凝聚物性质的复杂性,其受内在分子特征以及温度和pH等外部因素影响。分子模拟是建立分析这些影响的综合框架的有效方法,能提供关于凝聚物稳定性、动力学和材料性质的高分辨率见解。本综述评估了生物分子凝聚物模拟的最新进展,特别关注每个氨基酸一个珠子的粗粒度(1BPA)蛋白质模型,并强调了OpenABC,这是一种旨在简化和优化凝聚物模拟的工具。OpenABC支持各种粗粒度力场的实现,从而能够对其性能进行评估。我们的基准测试发现,尽管这些模型能准确捕捉单链统计数据,但不同力场的相行为预测存在不一致性。这一发现强调了提高力场准确性的必要性,可通过丰富训练数据集、多体势和先进优化技术来实现。这些改进可显著提高粗粒度模型的预测能力,弥合分子细节与凝聚物涌现行为之间的差距。

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