纳米技术
生物系统
功能(生物学)
物理
统计物理学
明细余额
分子动力学
过程(计算)
生物物理学
粒子(生态学)
衣壳
化学
分子机器
序列(生物学)
化学物理
动力学
计算机科学
设计要素和原则
分子生物物理学
复杂系统
大规模运输
能源景观
分子马达
表征(材料科学)
作者
Roi Asor,Dan Loewenthal,Diana Melnyk,Tiong Kit Tan,Philipp Kukura
出处
期刊:Nature
[Nature Portfolio]
日期:2026-09-16
卷期号:657 (8132): 653-660
被引量:1
标识
DOI:10.1038/s41586-026-10948-z
摘要
Abstract Biomolecular assembly is a cornerstone of cellular organization. Revealing its underlying principles is essential for understanding biological function 1,2 and malfunction in disease 3,4 . Viral capsid assembly is the archetypal self-assembly system 5–7 , which has been central in establishing the fundamental principles underpinning biomolecular assembly and the development of new biomaterials 8–10 and therapeutics 11,12 . Yet, despite decades of experimental efforts, observation and quantification of virus self-assembly pathways and dynamics have remained elusive 13 . Here we combine mass photometry (MP) 14 with a single-molecule trapping method to monitor the real-time assembly of individual virus-like particles (VLPs) with molecular resolution. We show that weak and reversible multivalent interactions control the assembly process by facilitating stochastic selection of a limited set of on-path, topologically closed intermediate structures. Assembly is finely tuned by the transition rates between these intermediates, proceeding through a sequence of effectively irreversible first-passage events. The corresponding first-passage times arise from the VLP symmetry, creating temporal separation between the formation of the first topologically closed intermediate and subsequent elongation. This results in a nucleation-and-growth mechanism that yields an equilibrium distribution consistent with the law of mass action, despite the overall irreversibility of assembly. Characterization of the thermodynamics and kinetics of the process reveals how the system specifically assembles into one final structure with high fidelity despite thousands of available assembly intermediates. More broadly, our approach provides a general framework for visualizing and quantifying the dynamics of multimeric biological machines at the molecular level.
科研通智能强力驱动
Strongly Powered by AbleSci AI