Department of Chemistry , Wichita State University , 1845 Fairmount Street , Wichita , Kansas 67260-0051 , United States.
J Chem Inf Model. 2019 May 28;59(5):2407-2422. doi: 10.1021/acs.jcim.9b00009. Epub 2019 Mar 22.
The solvation layer surrounding a protein is clearly an intrinsic part of protein structure-dynamics-function, and our understanding of how the hydration dynamics influences protein function is emerging. We have recently reported simulations indicating a correlation between regional hydration dynamics and the structure of the solvation layer around different regions of the enzyme Candida antarctica lipase B, wherein the radial distribution function (RDF) was used to calculate the pairwise entropy, providing a link between dynamics (diffusion) and thermodynamics (excess entropy) known as Rosenfeld scaling. Regions with higher RDF values/peaks in the hydration layer (the first peak, within 6 Å of the protein surface) have faster diffusion in the hydration layer. The finding thus hinted at a handle for rapid evaluation of hydration dynamics at different regions on the protein surface in molecular dynamics simulations. Such an approach may move the analysis of hydration dynamics from a specialized venture to routine analysis, enabling an informatics approach to evaluate the role of hydration dynamics in biomolecular function. This paper first confirms that the correlation between regional diffusive dynamics and hydration layer structure (via water center of mass around protein side-chain atom RDF) is observed as a general relationship across a set of proteins. Second, it seeks to devise an approach for rapid analysis of hydration dynamics, determining the minimum amount of information and computational effort required to get a reliable value of hydration dynamics from structural data in MD simulations based on the protein-water RDF. A linear regression model using the integral of the hydration layer in the water-protein RDF was found to provide statistically equivalent apparent diffusion coefficients at the 95% confidence level for a set of 92 regions within five different proteins. In summary, RDF analysis of 10 ns of data after simulation convergence is sufficient to accurately map regions of fast and slow hydration dynamics around a protein surface. Additionally, it is anticipated that a quick look at protein-water RDFs, comparing peak heights, will be useful to provide a qualitative ranking of regions of faster and slower hydration dynamics at the protein surface for rapid analysis when investigating the role of solvent dynamics in protein function.
蛋白质周围的溶剂化层显然是蛋白质结构-动力学-功能的固有部分,我们对水动力学如何影响蛋白质功能的理解正在出现。我们最近报告的模拟表明,不同区域的酶 Candida antarctica lipase B 的溶剂化层的局部水动力学和结构之间存在相关性,其中径向分布函数 (RDF) 用于计算对熵,在动力学(扩散)和热力学(过剩熵)之间建立联系,称为罗森菲尔德缩放。水合层中 RDF 值/峰较高的区域(第一层,距离蛋白质表面 6Å 以内)在水合层中的扩散速度较快。这一发现暗示了一种快速评估蛋白质表面不同区域水动力学的方法,这可能使水动力学分析从分子动力学模拟中的专门活动转变为常规分析,从而使信息学方法能够评估水动力学在生物分子功能中的作用。本文首先证实,区域性扩散动力学与水合层结构(通过蛋白质侧链原子 RDF 周围的水分子质心)之间的相关性是一种普遍关系,适用于一组蛋白质。其次,它试图设计一种快速分析水动力学的方法,确定从 MD 模拟中的结构数据获得水动力学可靠值所需的最少信息量和计算工作量,方法是基于蛋白质-水 RDF。发现使用水-蛋白质 RDF 中的水合层积分的线性回归模型可以在 95%置信水平下为 5 种不同蛋白质中的 92 个区域提供统计学等效的表观扩散系数。总之,模拟收敛后对 10 ns 数据进行 RDF 分析足以准确绘制蛋白质表面周围快速和缓慢水动力学区域的图谱。此外,预计快速查看蛋白质-水 RDF,比较峰高,将有助于在研究溶剂动力学在蛋白质功能中的作用时,对蛋白质表面上更快和更慢水动力学区域进行快速定性排序。