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基于微分几何的溶剂化模型II:拉格朗日公式。

Differential geometry based solvation model II: Lagrangian formulation.

作者信息

Chen Zhan, Baker Nathan A, Wei G W

机构信息

Department of Mathematics, Michigan State University, Lansing, MI 48824, USA.

出版信息

J Math Biol. 2011 Dec;63(6):1139-200. doi: 10.1007/s00285-011-0402-z. Epub 2011 Jan 30.

Abstract

Solvation is an elementary process in nature and is of paramount importance to more sophisticated chemical, biological and biomolecular processes. The understanding of solvation is an essential prerequisite for the quantitative description and analysis of biomolecular systems. This work presents a Lagrangian formulation of our differential geometry based solvation models. The Lagrangian representation of biomolecular surfaces has a few utilities/advantages. First, it provides an essential basis for biomolecular visualization, surface electrostatic potential map and visual perception of biomolecules. Additionally, it is consistent with the conventional setting of implicit solvent theories and thus, many existing theoretical algorithms and computational software packages can be directly employed. Finally, the Lagrangian representation does not need to resort to artificially enlarged van der Waals radii as often required by the Eulerian representation in solvation analysis. The main goal of the present work is to analyze the connection, similarity and difference between the Eulerian and Lagrangian formalisms of the solvation model. Such analysis is important to the understanding of the differential geometry based solvation model. The present model extends the scaled particle theory of nonpolar solvation model with a solvent-solute interaction potential. The nonpolar solvation model is completed with a Poisson-Boltzmann (PB) theory based polar solvation model. The differential geometry theory of surfaces is employed to provide a natural description of solvent-solute interfaces. The optimization of the total free energy functional, which encompasses the polar and nonpolar contributions, leads to coupled potential driven geometric flow and PB equations. Due to the development of singularities and nonsmooth manifolds in the Lagrangian representation, the resulting potential-driven geometric flow equation is embedded into the Eulerian representation for the purpose of computation, thanks to the equivalence of the Laplace-Beltrami operator in the two representations. The coupled partial differential equations (PDEs) are solved with an iterative procedure to reach a steady state, which delivers desired solvent-solute interface and electrostatic potential for problems of interest. These quantities are utilized to evaluate the solvation free energies and protein-protein binding affinities. A number of computational methods and algorithms are described for the interconversion of Lagrangian and Eulerian representations, and for the solution of the coupled PDE system. The proposed approaches have been extensively validated. We also verify that the mean curvature flow indeed gives rise to the minimal molecular surface and the proposed variational procedure indeed offers minimal total free energy. Solvation analysis and applications are considered for a set of 17 small compounds and a set of 23 proteins. The salt effect on protein-protein binding affinity is investigated with two protein complexes by using the present model. Numerical results are compared to the experimental measurements and to those obtained by using other theoretical methods in the literature.

摘要

溶剂化是自然界中的一个基本过程,对于更复杂的化学、生物和生物分子过程至关重要。对溶剂化的理解是定量描述和分析生物分子系统的必要前提。这项工作提出了基于微分几何的溶剂化模型的拉格朗日公式。生物分子表面的拉格朗日表示有一些用途/优点。首先,它为生物分子可视化、表面静电势图和生物分子的视觉感知提供了重要基础。此外,它与隐式溶剂理论的传统设定一致,因此许多现有的理论算法和计算软件包可以直接使用。最后,拉格朗日表示在溶剂化分析中不需要像欧拉表示法那样经常求助于人为扩大的范德华半径。本工作的主要目标是分析溶剂化模型的欧拉形式和拉格朗日形式之间的联系、相似性和差异。这种分析对于理解基于微分几何的溶剂化模型很重要。本模型用溶剂 - 溶质相互作用势扩展了非极性溶剂化模型的标度粒子理论。非极性溶剂化模型由基于泊松 - 玻尔兹曼(PB)理论的极性溶剂化模型补充完整。表面的微分几何理论用于提供溶剂 - 溶质界面的自然描述。包含极性和非极性贡献的总自由能泛函的优化导致耦合的势驱动几何流和PB方程。由于拉格朗日表示中奇点和非光滑流形的出现,为了计算目的,将得到的势驱动几何流方程嵌入到欧拉表示中,这得益于两种表示中拉普拉斯 - 贝尔特拉米算子的等价性。用迭代过程求解耦合的偏微分方程(PDEs)以达到稳态,这为感兴趣的问题提供了所需的溶剂 - 溶质界面和静电势。这些量用于评估溶剂化自由能和蛋白质 - 蛋白质结合亲和力。描述了许多用于拉格朗日和欧拉表示相互转换以及求解耦合PDE系统的计算方法和算法。所提出的方法已得到广泛验证。我们还验证了平均曲率流确实产生了最小分子表面,并且所提出的变分过程确实提供了最小的总自由能。对一组17种小化合物和一组23种蛋白质进行了溶剂化分析和应用研究。使用本模型通过两种蛋白质复合物研究了盐对蛋白质 - 蛋白质结合亲和力的影响。将数值结果与实验测量值以及文献中使用其他理论方法获得的结果进行了比较。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8f08/3113640/96749aaef7e2/nihms215331f1.jpg

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