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RNA/Peptide Binding Driven by Electrostatics-Insight from Bidirectional Pulling Simulations

机译:静电学驱动的RNA /肽结合-双向拉动模拟

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摘要

RNA/protein interactions play crucial roles in controlling gene expression. They are becoming important targets for pharmaceutical applications. Due to RNA flexibility and to the strength of electrostatic interactions, standard docking methods are insufficient. We here present a computational method which allows studying the binding of RNA molecules and charged peptides with atomistic, explicit-solvent molecular dynamics. In our method, a suitable estimate of the electrostatic interaction is used as an order parameter (collective variable) which is then accelerated using bidirectional pulling simulations. Since the electrostatic interaction is only used to enhance the sampling, the approximations used to compute it do not affect the final accuracy. The method is employed to characterize the binding of TAR RNA from HIV-1 and a small cyclic peptide. Our simulation protocol allows blindly predicting the binding pocket and pose as well as the binding affinity. The method is general and could be applied to study other electrostatics-driven binding events.
机译:RNA /蛋白质相互作用在控制基因表达中起关键作用。它们正在成为制药应用的重要目标。由于RNA的灵活性和静电相互作用的强度,标准的对接方法不足。我们在这里提出一种计算方法,该方法可以研究具有原子性,显式溶剂分子动力学的RNA分子和带电肽的结合。在我们的方法中,将静电相互作用的适当估计值用作有序参数(集合变量),然后使用双向拉动仿真对其进行加速。由于静电相互作用仅用于增强采样,因此用于计算它的近似值不会影响最终精度。该方法用于表征HIV-1与小环肽的TAR RNA的结合。我们的模拟方案允许盲目预测结合口袋和姿势以及结合亲和力。该方法是通用的,可用于研究其他静电驱动的结合事件。

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