Exploring Free Energy Landscapes of Large Conformational Changes: Molecular Dynamics with Excited Normal Modes
Exploring Free Energy Landscapes of Large Conformational Changes: Molecular Dynamics with Excited Normal Modes
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DOI：
10.1021/acs.jctc.5b00003
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发表时间：
2015-06-01
影响因子：
5.5
通讯作者：
Perahia, David
中科院分区：
文献类型：
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作者：
Costa, Mauricio G. S.;Batista, Paulo R.;Perahia, David
蛋白质在溶液中作为处于动态平衡的构象集合体存在。通过分子动力学（MD）模拟探索微到毫秒时间尺度上发生的功能运动在计算上仍然具有挑战性。另外，正态模式 (NM) 分析是一种非常适合表征固有慢集体运动的方法，通常与蛋白质功能相关，但不存在非谐效应，无法正确表征多维 NM 空间中的构象分布。联合使用这两种方法似乎是一种有吸引力的方法，可以对构象空间进行扩展采样。根据这一观点，这里提出的 MDeNM（具有激发正常模式的分子动力学）方法由多个副本短 MD 模拟组成，其中给定的低频 NM 子集描述的运动受到动力学激发。这是通过沿着 NM 向量的几个随机确定的线性组合添加额外的原子速度来实现的，从而允许慢速运动和快速运动之间的有效耦合。通过标准 MD 模拟，MDeNM 生成的相对高能构象得到进一步松弛，从而能够确定自由能景观。选择两种广泛研究的蛋白质作为例子：鸡蛋溶菌酶和 HIV-1 蛋白酶。在这两种情况下，MDeNM 在几纳秒内提供了更大范围的采样，优于长标准 MD 模拟。观察到与从实验来源（X 射线、EPR 和 NMR）推断的运动以及通过元动力学获得的自由能估计具有高度相关性。最后，通过 MDeNM 获得的大量构象可用于更好地表征相关动态群体，从而更好地解释 SAXS 曲线和 NMR 谱等实验数据。
Proteins are found in solution as ensembles of conformations in dynamic equilibrium. Exploration of functional motions occurring on micro- to millisecond time scales by molecular dynamics (MD) simulations still remains computationally challenging. Alternatively, normal mode (NM) analysis is a well-suited method to characterize intrinsic slow collective motions, often associated with protein function, but the absence of anharmonic effects preclude a proper characterization of conformational distributions in a multidimensional NM space. Using both methods jointly appears to be an attractive approach that allows an extended sampling of the conformational space. In line with this view, the MDeNM (molecular dynamics with excited normal modes) method presented here consists of multiple-replica short MD simulations in which motions described by a given subset of low-frequency NMs are kinetically excited. This is achieved by adding additional atomic velocities along several randomly determined linear combinations of NM vectors, thus allowing an efficient coupling between slow and fast motions. The relatively high-energy conformations generated with MDeNM are further relaxed with standard MD simulations, enabling free energy landscapes to be determined. Two widely studied proteins were selected as examples: hen egg lysozyme and HIV-1 protease. In both cases, MDeNM provides a larger extent of sampling in a few nanoseconds, outperforming long standard MD simulations. A high degree of correlation with motions inferred from experimental sources (X-ray, EPR, and NMR) and with free energy estimations obtained by metadynamics was observed. Finally, the large sets of conformations obtained with MDeNM can be used to better characterize relevant dynamical populations, allowing for a better interpretation of experimental data such as SAXS curves and NMR spectra.