论文标题

来自自适应偏差的罕见事件动力学增强了采样

Rare Event Kinetics from Adaptive Bias Enhanced Sampling

论文作者

Ray, Dhiman, Ansari, Narjes, Rizzi, Valerio, Invernizzi, Michele, Parrinello, Michele

论文摘要

我们引入了一种新型增强的采样方法,名为Opes洪水,用于计算原子分子动力学模拟中罕见事件的动力学。此方法源自现有性增强的采样(OPES)方法[Invernizzi和Parrinello,JPC Lett。 2020年],最近已开发用于计算复杂系统的融合自由能表面。在本文中,我们描述了OPES洪水技术的理论细节,并证明了对增加复杂性的三个系统的应用:在二维双重井中的屏障交叉,在气相中丙氨酸二肽中的构象转变,以及在水中环境中易肽肽多肽的折叠和展开。从广泛的测试中,我们表明,准确动力学的计算不仅需要过渡状态是无偏见的,而且沉积的偏差量也不应超过沿所选集体变量测量的有效屏障高度。在这种情况下,还探讨了从偏置次优阶参数计算速率的可能性。此外,我们描述了最佳参数组合的选择,以从有限的计算工作中获得准确的结果。

We introduce a novel enhanced sampling approach named OPES flooding for calculating the kinetics of rare events from atomistic molecular dynamics simulation. This method is derived from the On-the-fly-Probability-Enhanced-Sampling (OPES) approach [Invernizzi and Parrinello, JPC Lett. 2020], which has been recently developed for calculating converged free energy surfaces for complex systems. In this paper, we describe the theoretical details of the OPES flooding technique and demonstrate the application on three systems of increasing complexity: barrier crossing in a two-dimensional double well potential, conformational transition in the alanine dipeptide in gas phase, and the folding and unfolding of the chignolin polypeptide in aqueous environment. From extensive tests, we show that the calculation of accurate kinetics not only requires the transition state to be bias-free, but the amount of bias deposited should also not exceed the effective barrier height measured along the chosen collective variables. In this vein, the possibility of computing rates from biasing suboptimal order parameters has also been explored. Furthermore, we describe the choice of optimum parameter combinations for obtaining accurate results from limited computational effort.

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