Department of Chemistry, Northwestern University, 2145 Sheridan Road, Evanston, IL, 60208, USA.
Nat Commun. 2022 Apr 22;13(1):2204. doi: 10.1038/s41467-022-29393-3.
Most computer simulations of molecular dynamics take place under equilibrium conditions-in a closed, isolated system, or perhaps one held at constant temperature or pressure. Sometimes, extra tensions, shears, or temperature gradients are introduced to those simulations to probe one type of nonequilibrium response to external forces. Catalysts and molecular motors, however, function based on the nonequilibrium dynamics induced by a chemical reaction's thermodynamic driving force. In this scenario, simulations require chemostats capable of preserving the chemical concentrations of the nonequilibrium steady state. We develop such a dynamic scheme and use it to observe cycles of a particle-based classical model of a catenane-like molecular motor. Molecular motors are frequently modeled with detailed-balance-breaking Markov models, and we explicitly construct such a picture by coarse graining the microscopic dynamics of our simulations in order to extract rates. This work identifies inter-particle interactions that tune those rates to create a functional motor, thereby yielding a computational playground to investigate the interplay between directional bias, current generation, and coupling strength in molecular information ratchets.
大多数分子动力学的计算机模拟都是在平衡条件下进行的——在一个封闭、孤立的系统中，或者在恒温或恒压下。有时，会向这些模拟中引入额外的张力、剪切或温度梯度，以探测对外部力的一种非平衡响应。然而，催化剂和分子马达是基于化学反应的热力学驱动力所引起的非平衡动力学来工作的。在这种情况下，模拟需要恒化器来保持非平衡稳态的化学浓度。我们开发了这样一种动态方案，并使用它来观察一种类似索链的分子马达的基于粒子的经典模型的循环。分子马达通常用打破详细平衡的马尔可夫模型来建模，我们通过粗粒化模拟的微观动力学来明确构建这样一个图像，以提取速率。这项工作确定了粒子间相互作用，这些相互作用可以调节这些速率，从而创建一个功能化的马达，从而提供了一个计算平台来研究分子信息棘轮中的定向偏差、电流产生和耦合强度之间的相互作用。
