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A Newton-like iterative method implemented in the DelPhi for solving the nonlinear Poisson-Boltzmann equation
DelPhi is a popular scientific program which numerically solves the Poisson-Boltzmann equation (PBE) for electrostatic potentials and energies of biomolecules immersed in water via finite difference method. It is well known for its accuracy, reliability, flexibility, and efficiency. In this work, a...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883664/ https://www.ncbi.nlm.nih.gov/pubmed/33378855 http://dx.doi.org/10.3934/mbe.2020331 |
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author | Li, Chuan McGowan, Mark Alexov, Emil Zhao, Shan |
author_facet | Li, Chuan McGowan, Mark Alexov, Emil Zhao, Shan |
author_sort | Li, Chuan |
collection | PubMed |
description | DelPhi is a popular scientific program which numerically solves the Poisson-Boltzmann equation (PBE) for electrostatic potentials and energies of biomolecules immersed in water via finite difference method. It is well known for its accuracy, reliability, flexibility, and efficiency. In this work, a new edition of DelPhi that uses a novel Newton-like method to solve the nonlinear PBE, in addition to the already implemented Successive Over Relaxation (SOR) algorithm, is introduced. Our tests on various examples have shown that this new method is superior to the SOR method in terms of stability when solving the nonlinear PBE, being able to converge even for problems involving very strong nonlinearity. |
format | Online Article Text |
id | pubmed-9883664 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-98836642023-01-28 A Newton-like iterative method implemented in the DelPhi for solving the nonlinear Poisson-Boltzmann equation Li, Chuan McGowan, Mark Alexov, Emil Zhao, Shan Math Biosci Eng Article DelPhi is a popular scientific program which numerically solves the Poisson-Boltzmann equation (PBE) for electrostatic potentials and energies of biomolecules immersed in water via finite difference method. It is well known for its accuracy, reliability, flexibility, and efficiency. In this work, a new edition of DelPhi that uses a novel Newton-like method to solve the nonlinear PBE, in addition to the already implemented Successive Over Relaxation (SOR) algorithm, is introduced. Our tests on various examples have shown that this new method is superior to the SOR method in terms of stability when solving the nonlinear PBE, being able to converge even for problems involving very strong nonlinearity. 2020-09-21 /pmc/articles/PMC9883664/ /pubmed/33378855 http://dx.doi.org/10.3934/mbe.2020331 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0 (https://creativecommons.org/licenses/by/4.0/) ) |
spellingShingle | Article Li, Chuan McGowan, Mark Alexov, Emil Zhao, Shan A Newton-like iterative method implemented in the DelPhi for solving the nonlinear Poisson-Boltzmann equation |
title | A Newton-like iterative method implemented in the DelPhi for solving the nonlinear Poisson-Boltzmann equation |
title_full | A Newton-like iterative method implemented in the DelPhi for solving the nonlinear Poisson-Boltzmann equation |
title_fullStr | A Newton-like iterative method implemented in the DelPhi for solving the nonlinear Poisson-Boltzmann equation |
title_full_unstemmed | A Newton-like iterative method implemented in the DelPhi for solving the nonlinear Poisson-Boltzmann equation |
title_short | A Newton-like iterative method implemented in the DelPhi for solving the nonlinear Poisson-Boltzmann equation |
title_sort | newton-like iterative method implemented in the delphi for solving the nonlinear poisson-boltzmann equation |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9883664/ https://www.ncbi.nlm.nih.gov/pubmed/33378855 http://dx.doi.org/10.3934/mbe.2020331 |
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