域分解线性泊松-玻尔兹曼方法中力的线性缩放计算。

Linear scaling computation of forces for the domain-decomposition linear Poisson-Boltzmann method.

作者信息

Jha Abhinav, Nottoli Michele, Mikhalev Aleksandr, Quan Chaoyu, Stamm Benjamin

机构信息

Institute of Applied Analysis and Numerical Simulation, Universität Stuttgart, Pfaffenwaldring 57, 70569 Stuttgart, Germany.

Applied and Computational Mathematics, RWTH Aachen University, Schinkelstraße 2, 52062 Aachen, Germany.

出版信息

J Chem Phys. 2023 Mar 14;158(10):104105. doi: 10.1063/5.0141025.

DOI:10.1063/5.0141025

PMID:36922147

Abstract

The Linearized Poisson-Boltzmann (LPB) equation is a popular and widely accepted model for accounting solvent effects in computational (bio-) chemistry. In the present article, we derive the analytical forces using the domain-decomposition-based LPB-method with a van-der Waals or solvent-accessible surface. We present an efficient strategy to compute the forces and its implementation, allowing linear scaling of the method with respect to the number of atoms using the fast multipole method. Numerical tests illustrate the accuracy of the computation of the analytical forces and compare the efficiency with other available methods.

摘要

线性化泊松-玻尔兹曼（LPB）方程是计算（生物）化学中用于考虑溶剂效应的一种流行且被广泛接受的模型。在本文中，我们使用基于域分解的LPB方法，结合范德华力或溶剂可及表面来推导解析力。我们提出了一种计算这些力的有效策略及其实现方法，通过快速多极子方法使该方法在原子数量方面实现线性缩放。数值测试说明了解析力计算的准确性，并将其效率与其他可用方法进行了比较。