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In this paper, we present a parallel higher-order boundary integral method to solve the linear Poisson-Boltzmann (PB) equation. In our method, a well-posed boundary integral formulation is used to ensure the fast convergence of Krylov…

Numerical Analysis · Mathematics 2015-06-12 Weihua Geng

In this paper, we present a GPU-accelerated direct-sum boundary integral method to solve the linear Poisson-Boltzmann (PB) equation. In our method, a well-posed boundary integral formulation is used to ensure the fast convergence of Krylov…

Numerical Analysis · Mathematics 2015-06-12 Weihua Geng , Ferosh Jacob

The Poisson-Boltzmann model is an effective and popular approach for modeling solvated biomolecules in continuum solvent with dissolved electrolytes. In this paper, we report our recent work in developing a Galerkin boundary integral method…

Computational Physics · Physics 2021-10-27 Jiahui Chen , Johannes Tausch , Weihua Geng

Electrostatic interactions play crucial roles in biophysical processes such as protein folding and molecular recognition. Poisson-Boltzmann equation (PBE)-based models have emerged as widely used in modeling these important processes.…

Computational Physics · Physics 2017-04-11 Ruxi Qi , Wesley M. Botello-Smith , Ray Luo

The Poisson-Boltzmann equation offers an efficient way to study electrostatics in molecular settings. Its numerical solution with the boundary element method is widely used, as the complicated molecular surface is accurately represented by…

Numerical Analysis · Mathematics 2021-08-25 Stefan D. Search , Christopher D. Cooper , Elwin van't Wout

The Poisson-Fermi model is an extension of the classical Poisson-Boltzmann model to include the steric and correlation effects of ions and water treated as nonuniform spheres in aqueous solutions. Poisson-Boltzmann electrostatic…

Computational Physics · Physics 2018-07-04 Jen-Hao Chen , Ren-Chuen Chen , Jinn-Liang Liu

Developing accurate solvers for the Poisson Boltzmann (PB) model is the first step to make the PB model suitable for implicit solvent simulation. Reducing the grid size influence on the performance of the solver benefits to increasing the…

Numerical Analysis · Mathematics 2016-07-18 Bao Wang , Guowei Wei

Implicit-solvent models are widely used to study the electrostatics in dissolved biomolecules, which are parameterized using force fields. Standard force fields treat the charge distribution with point charges, however, other force fields…

Computational Physics · Physics 2018-10-10 Christopher D. Cooper

In computational biochemistry and biophysics, understanding the role of electrostatic interactions is crucial for elucidating the structure, dynamics, and function of biomolecules. The Poisson-Boltzmann (PB) equation is a foundational tool…

Biomolecules · Quantitative Biology 2024-10-08 Yongxian Wu , Qiang Zhu , Ray Luo

Biomolecular electrostatics is key in protein function and the chemical processes affecting it. Implicit-solvent models via the Poisson-Boltzmann (PB) equation provide insights with less computational cost than atomistic models, making…

Computational Physics · Physics 2022-12-27 Tingyu Wang , Christopher D. Cooper , Timo Betcke , Lorena A. Barba

The continuum theory applied to bimolecular electrostatics leads to an implicit-solvent model governed by the Poisson-Boltzmann equation. Solvers relying on a boundary integral representation typically do not consider features like…

Computational Physics · Physics 2013-11-08 Christopher D. Cooper , Jaydeep P. Bardhan , L. A. Barba

The Poisson-Boltzmann (PB) implicit solvent model is a popular framework for studying the electrostatics of biomolecules immersed in water with dissolved salt. In this model the dielectric interface between the biomolecule and solvent is…

Computational Physics · Physics 2020-10-22 Leighton Wilson , Robert Krasny

A numerical method using implicit surface representations is proposed to solve the linearized Poisson-Boltzmann equations that arise in mathematical models for the electrostatics of molecules in solvent. The proposed method used an implicit…

Numerical Analysis · Mathematics 2018-04-04 Yimin Zhong , Kui Ren , Richard Tsai

Interactions between surfaces and proteins occur in many vital processes and are crucial in biotechnology: the ability to control specific interactions is essential in fields like biomaterials, biomedical implants and biosensors. In the…

Computational Physics · Physics 2016-04-20 Christopher D. Cooper , Lorena A. Barba

This paper presents the design, implementation, and performance analysis of a parallel and GPU-accelerated Poisson solver based on the Preconditioned Bi-Conjugate Gradient Stabilized (Bi-CGSTAB) method. The implementation utilizes the MPI…

Distributed, Parallel, and Cluster Computing · Computer Science 2025-03-13 Luca Pennati , Måns I. Andersson , Klaus Steiniger , Rene Widera , Tapish Narwal , Michael Bussmann , Stefano Markidis

The Poisson-Boltzmann equation (PBE) is a relevant partial differential equation commonly used in biophysical applications to estimate the electrostatic energy of biomolecular systems immersed in electrolytic solutions. A conventional mean…

In this paper, we solve the linearized Poisson-Boltzmann equation, used to model the electric potential of macromolecules in a solvent. We derive a corrected trapezoidal rule with improved accuracy for a boundary integral formulation of the…

Numerical Analysis · Mathematics 2022-10-10 Federico Izzo , Yimin Zhong , Olof Runborg , Richard Tsai

The Poisson--Boltzmann equation is widely used to model electrostatics in molecular systems. Available software packages solve it using finite difference, finite element, and boundary element methods, where the latter is attractive due to…

Computational Physics · Physics 2025-12-24 Michal Bosy , Matthew W. Scroggs , Timo Betcke , Erik Burman , Christopher D. Cooper

The Poisson-Boltzmann equation (PBE) is an implicit solvent continuum model for calculating the electrostatic potential and energies of ionic solvated biomolecules. However, its numerical solution remains a significant challenge due strong…

Numerical Analysis · Mathematics 2023-06-13 Cleophas Kweyu , Venera Khoromskaia , Boris Khoromskij , Matthias Stein , Peter Benner

Physics-informed neural networks (PINN) is a machine learning (ML)-based method to solve partial differential equations that has gained great popularity due to the fast development of ML libraries in the last few years. The…

Chemical Physics · Physics 2024-12-31 Martin A. Achondo , Jehanzeb H. Chaudhry , Christopher D. Cooper
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