Discovering free energy basins for macromolecular systems via guided multiscale simulation.
Discovering free energy basins for macromolecular systems via guided multiscale simulation.
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DOI：
10.1021/jp2126174
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发表时间：
2012-07-26
期刊：
影响因子：
--
通讯作者：
Ortoleva PJ
中科院分区：
文献类型：
--
作者：
Sereda YV;Singharoy AB;Jarrold MF;Ortoleva PJ
提出了一种自动发现大分子系统低自由能态的方法。该方法不涉及描绘整个自由能景观，而是进行顺序自由能最小化状态发现，即，它首先发现一个低自由能状态，然后自动寻找不同的相邻状态。这些状态和相关的原子配置集合的特征是捕获系统大规模结构的粗粒度变量。我们方法的一个关键方面是识别此类粗粒度变量。这些变量的演化受朗之万动力学控制，朗之万动力学由热平均力驱动并由扩散率介导，两者都是由短分子动力学运行的集合构建的。在本方法中，根据我们对已发现的自由能盆地的了解，对热平均力进行了修改，以考虑熵的变化。这些力引导系统远离已知的自由能最小值，越过自由能壁垒，到达新的自由能壁垒。该理论得到了乳铁蛋白的证明，已知乳铁蛋白具有多种能量最小化结构。该方法通过实验结构和传统分子动力学进行了验证。该方法可以推广到能够解释纳米表征数据（例如，离子淌度 - 质谱、原子力显微镜、化学标记和纳米孔测量）。
An approach for the automated discovery of low free energy states of macromolecular systems is presented. The method does not involve delineating the entire free energy landscape but proceeds in a sequential free energy minimizing state discovery, i.e., it first discovers one low free energy state and then automatically seeks a distinct neighboring one. These states and the associated ensembles of atomistic configurations are characterized by coarse-grained variables capturing the large-scale structure of the system. A key facet of our approach is the identification of such coarse-grained variables. Evolution of these variables is governed by Langevin dynamics driven by thermal-average forces and mediated by diffusivities, both of which are constructed by an ensemble of short molecular dynamics runs. In the present approach, the thermal-average forces are modified to account for the entropy changes following from our knowledge of the free energy basins already discovered. Such forces guide the system away from the known free energy minima, over free energy barriers, and to a new one. The theory is demonstrated for lactoferrin, known to have multiple energy-minimizing structures. The approach is validated using experimental structures and traditional molecular dynamics. The method can be generalized to enable the interpretation of nanocharacterization data (e.g., ion mobility – mass spectrometry, atomic force microscopy, chemical labeling, and nanopore measurements).
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影响因子：
64.8
作者：
LEE, C;LEVITT, M
通讯作者：
LEVITT, M
DOI：
10.1016/j.pbiomolbio.2011.07.006
发表时间：
2011-10
影响因子：
3.8
作者：
Joshi H;Singharoy A;Sereda YV;Cheluvaraja SC;Ortoleva PJ
通讯作者：
Ortoleva PJ
影响因子：
5.6
作者：
LEE, C
通讯作者：
LEE, C
影响因子：
3.4
作者：
Kim, MK;Jernigan, RL;Chirikjian, GS
通讯作者：
Chirikjian, GS
影响因子：
19.6
作者：
Keyser, Ulrich F.;Koeleman, Bernard N.;Dekker, Cees
通讯作者：
Dekker, Cees