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An efficient second‐order poisson–boltzmann method
Author(s) -
Wei Haixin,
Luo Ray,
Qi Ruxi
Publication year - 2019
Publication title -
journal of computational chemistry
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.907
H-Index - 188
eISSN - 1096-987X
pISSN - 0192-8651
DOI - 10.1002/jcc.25783
Subject(s) - solver , convergence (economics) , bottleneck , interface (matter) , computer science , quadratic equation , stability (learning theory) , poisson–boltzmann equation , mathematics , instability , rate of convergence , poisson distribution , linear system , mathematical optimization , computational science , physics , parallel computing , mathematical analysis , mechanics , geometry , channel (broadcasting) , economic growth , ion , computer network , maximum bubble pressure method , embedded system , bubble , quantum mechanics , machine learning , statistics , economics
Immersed interface method (IIM) is a promising high‐accuracy numerical scheme for the Poisson–Boltzmann model that has been widely used to study electrostatic interactions in biomolecules. However, the IIM suffers from instability and slow convergence for typical applications. In this study, we introduced both analytical interface and surface regulation into IIM to address these issues. The analytical interface setup leads to better accuracy and its convergence closely follows a quadratic manner as predicted by theory. The surface regulation further speeds up the convergence for nontrivial biomolecules. In addition, uncertainties of the numerical energies for tested systems are also reduced by about half. More interestingly, the analytical setup significantly improves the linear solver efficiency and stability by generating more precise and better‐conditioned linear systems. Finally, we implemented the bottleneck linear system solver on GPUs to further improve the efficiency of the method, so it can be widely used for practical biomolecular applications. © 2019 Wiley Periodicals, Inc.