分子动力学
乙状窦函数
计算机科学
高斯分布
工作(物理)
均方根
采样(信号处理)
加速度
平均力势
生物系统
统计物理学
化学
物理
计算化学
人工智能
热力学
经典力学
滤波器(信号处理)
生物
人工神经网络
计算机视觉
量子力学
作者
Yihao Zhao,Jintu Zhang,Haotian Zhang,Shukai Gu,Yafeng Deng,Yaoquan Tu,Tingjun Hou,Yu Kang
标识
DOI:10.1021/acs.jpclett.2c03688
摘要
Gaussian accelerated molecular dynamics (GaMD) is recognized as a popular enhanced sampling method for tackling long-standing challenges in biomolecular simulations. Inspired by GaMD, Sigmoid accelerated molecular dynamics (SaMD) is proposed in this work by adding a Sigmoid boost potential to improve the balance between the highest acceleration and accurate reweighting. Compared with GaMD, SaMD extends the accessible time scale and improves the computational efficiency as tested in three tasks. In the alanine dipeptide task, SaMD can produce the free energy landscape with better accuracy and efficiency. In the chignolin folding task, the estimated Gibbs free energy difference can converge to the experimental value ∼30% faster. In the protein-ligand binding task, the bound conformations are closer to the crystal structure with a minimal ligand root-mean-square deviation of 1.7 Å. The binding of the ligand XK263 to the HIV protease is reproduced by SaMD in ∼60% less simulation time.
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