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Improving Efficiency in SMD Simulations Through a Hybrid Differential Relaxation Algorithm

机译:通过混合微分松弛算法提高SMD仿真的效率

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The fundamental object for studying a (bio)- chemical reaction obtained from simulations is the free energy profile, which can be directly related to experimentally determined properties. Although quite accurate hybrid quantum (DFT based)-classical methods are available, achieving statistically accurate and well converged results at a moderate computational cost is still an open challenge. Here, we present and thoroughly test a hybrid differential relaxation algorithm (HyDRA), which allows faster equilibration of the classical environment during the nonequilibrium steering of a (bio)chemical reaction. We show and discuss why (in the context of Jarzynski's Relationship) this method allows obtaining accurate free energy profiles with smaller number of independent trajectories and/or faster pulling speeds, thus reducing the overall computational cost. Moreover, due to the availability and straightforward implementation of the method, we expect that it will foster theoretical studies of key enzymatic processes.
机译:研究通过模拟获得的(生物)化学反应的基本目的是自由能分布,它可以与实验确定的性质直接相关。尽管可以使用相当精确的混合量子(基于DFT)的经典方法,但以适度的计算成本获得统计上准确且收敛的结果仍然是一个开放的挑战。在这里,我们介绍并彻底测试了混合差分松弛算法(HyDRA),该算法可在(生物)化学反应的非平衡操纵过程中更快地平衡经典环境。我们展示并讨论了为什么(在Jarzynski关系的上下文中)此方法允许以较少的独立轨迹数量和/或更快的牵引速度获得准确的自由能曲线,从而降低了总体计算成本。此外,由于该方法的实用性和直接实施性,我们希望它将促进关键酶过程的理论研究。

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