Center for Computational Sciences , University of Tsukuba , 1-1-1 Tennodai , Tsukuba , Ibaraki 305-8577 , Japan.
Institute of Chemistry - Centre for Glycomics , Dubravska cesta 9 , 84538 Bratislava , Slovakia.
J Chem Theory Comput. 2019 Sep 10;15(9):5144-5153. doi: 10.1021/acs.jctc.9b00489. Epub 2019 Aug 27.
Nontargeted parallel cascade selection molecular dynamics (nt-PaCS-MD) is an enhanced conformational sampling method of proteins, which does not rely on knowledge of the target structure. It makes use of cyclic resampling from some relevant initial structures to expand the searched conformational subspace. The efficiency of nt-PaCS-MD depends on the selections of these initial structures. They are usually stochastically occurring perturbed structures at which larger conformation transitions are about to happen. Reliable identification of these is the key to using nt-PaCS-MD. Two new parameters, the moving root-mean-square deviation (mRMSD) and the inner products of the backbone dihedral angles Φ and Ψ, are introduced as indicators of conformational outliers in MD trajectories. Both are based on the analysis of a time-localized set of coordinates, overcoming the need for a target structure while still capturing the complexity of the conformational transition. The reference to which the mRMSD relates is the close surrounding of the -th conformation, often the (-1)st one. Hence the name "time-localized" analysis. In this work, we focus on its interplay with nt-PaCS-MD and show that it increases its effectiveness compared to older versions. The target system is the midsized protein T4 lysozyme (in explicit water) on which we demonstrate the open-closed transition without referring to any target configuration. Additionally, we show that the short MD trajectories can be used for the construction of a free energy landscape of the conformational transition based on the Markov state model.
非靶向平行级联选择分子动力学(nt-PaCS-MD)是一种增强的蛋白质构象采样方法,它不依赖于目标结构的知识。它利用从一些相关初始结构的循环重采样来扩展搜索的构象子空间。nt-PaCS-MD 的效率取决于这些初始结构的选择。它们通常是随机发生的扰动结构,即将发生较大的构象转变。可靠地识别这些结构是使用 nt-PaCS-MD 的关键。引入了两个新参数,即移动均方根偏差(mRMSD)和主链二面角 Φ 和 Ψ 的内积,作为 MD 轨迹中构象离群值的指标。这两个参数都是基于对局部时间坐标的分析,克服了对目标结构的需求,同时仍能捕捉构象转变的复杂性。mRMSD 所参考的是第 -th 构象的紧密周围,通常是第 (-1) 个构象。因此,它被称为“局部时间”分析。在这项工作中,我们重点研究了它与 nt-PaCS-MD 的相互作用,并表明它比旧版本更有效。目标系统是中型蛋白 T4 溶菌酶(在显式水中),我们在没有参考任何目标构象的情况下演示了它的开-闭转变。此外,我们还表明,短 MD 轨迹可用于基于马氏态模型构建构象转变的自由能景观。