Department of Physics and Astronomy, University of California, Los Angeles, California, United States of America.
Department of Chemistry and Biochemistry, University of California, Los Angeles, California, United States of America.
PLoS Comput Biol. 2022 Apr 1;18(4):e1009913. doi: 10.1371/journal.pcbi.1009913. eCollection 2022 Apr.
The paper presents a statistical-mechanics model for the kinetic selection of viral RNA molecules by packaging signals during the nucleation stage of the assembly of small RNA viruses. The effects of the RNA secondary structure and folding geometry of the packaging signals on the assembly activation energy barrier are encoded by a pair of characteristics: the wrapping number and the maximum ladder distance. Kinetic selection is found to be optimal when assembly takes place under conditions of supersaturation and also when the concentration ratio of capsid protein and viral RNA concentrations equals the stoichiometric ratio of assembled viral particles. As a function of the height of the activation energy barrier, there is a form of order-disorder transition such that for sufficiently low activation energy barriers, kinetic selectivity is erased by entropic effects associated with the number of assembly pathways.
本文提出了一个统计力学模型,用于在小 RNA 病毒组装的成核阶段通过包装信号对病毒 RNA 分子进行动力学选择。包装信号的 RNA 二级结构和折叠几何形状对组装激活能垒的影响由一对特征编码:包裹数和最大梯级距离。当组装在过饱和条件下进行,并且衣壳蛋白的浓度与病毒 RNA 浓度的浓度比等于组装病毒颗粒的化学计量比时,发现动力学选择是最佳的。作为激活能垒高度的函数,存在一种有序-无序转变的形式,使得对于足够低的激活能垒,与组装途径数量相关的熵效应会消除动力学选择性。