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Reliable Computer Simulation Methods for Electrostatic Biomolecular Models Based on the Poisson–Boltzmann Equation

Johannes Kraus ORCID logo EMAIL logo , Svetoslav Nakov and Sergey Repin


The paper is concerned with the reliable numerical solution of a class of nonlinear interface problems governed by the Poisson–Boltzmann equation. Arising in electrostatic biomolecular models these problems typically contain measure-type source terms and their solution often exposes drastically different behaviour in different subdomains. The interface conditions reflect the requirement that the potential and its normal derivative must be continuous. In the first part of the paper, we discuss an appropriate weak formulation of the problem that guarantees existence and uniqueness of the generalized solution. In the context of the considered class of nonlinear equations, this question is not trivial and requires additional analysis, which is based on a special splitting of the problem into simpler subproblems whose weak solutions can be defined in standard Sobolev spaces. This splitting also suggests a rational numerical solution strategy and a way of deriving fully guaranteed error bounds. These bounds (error majorants) are derived for each subproblem separately and, finally, yield a fully computable majorant of the difference between the exact solution of the original problem and any energy-type approximation of it.

The efficiency of the suggested computational method is verified in a series of numerical tests related to real-life biophysical systems.

Funding source: Austrian Science Fund

Award Identifier / Grant number: W1250

Funding statement: The second author is grateful for the financial support received from the Doctorate College program Nano-Analytics of Cellular Systems (NanoCell) of the Austrian Science Fund (FWF) (grant number: W1250) and from the project LIT-JKU-2017-04-SEE-004 of the Linz Institute of Technology.


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Received: 2020-02-23
Revised: 2020-08-31
Accepted: 2020-09-09
Published Online: 2020-09-27
Published in Print: 2020-10-01

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