Efficiently finding the minimum free energy path from steepest descent path
Efficiently finding the minimum free energy path from steepest descent path
复制标题
从最陡下降路径有效找到最小自由能路径
DOI：
10.1063/1.4799236
复制
发表时间：
2013-04-28
影响因子：
4.4
通讯作者：
Xiao, Yi
中科院分区：
文献类型：
--
作者：
Chen, Changjun;Huang, Yanzhao;Xiao, Yi
最小自由能路径（MFEP）在计算生物学和计算化学中具有重要的意义。路径中的势垒与反应速率有关，并且起始到结束的差异给出了反应物和产物之间的相对稳定性。这些信息对实验和实际应用具有重要意义。但找到MMEP并不是一件容易的事。大量的自由度使得计算非常复杂和耗时。在本文中，我们使用最陡下降路径（SDP），以加快采样的MFEP。SHAKE算法和拉格朗日乘子用于控制SDP和MFEP的优化。这些策略简单而有效。对于前者，它更有趣。因为我们知道，SHAKE算法过去是为处理分子动力学中的约束而设计的，从来没有被用于几何优化。最后对ALA二肽和10-ALA肽的优化结果表明，该方法具有较好的优化效果。利用SDP中的信息，初始路径可以达到更优的MFEP。因此，可以得到更准确的自由能，并可以节省大量的计算时间。(C)2013年美国物理学会。
Minimum Free Energy Path (MFEP) is very important in computational biology and chemistry. The barrier in the path is related to the reaction rate, and the start-to-end difference gives the relative stability between reactant and product. All these information is significant to experiment and practical application. But finding MFEP is not an easy job. Lots of degrees of freedom make the computation very complicated and time consuming. In this paper, we use the Steepest Descent Path (SDP) to accelerate the sampling of MFEP. The SHAKE algorithm and the Lagrangian multipliers are used to control the optimization of both SDP and MFEP. These strategies are simple and effective. For the former, it is more interesting. Because as we known, SHAKE algorithm was designed to handle the constraints in molecular dynamics in the past, has never been used in geometry optimization. Final applications on ALA dipeptide and 10-ALA peptide show that this combined optimization method works well. Use the information in SDP, the initial path could reach the more optimal MFEP. So more accurate free energies could be obtained and the amount of computation time could be saved. (C) 2013 American Institute of Physics.