ArticleJournal of computational chemistry2019
An efficient second-order poisson-boltzmann method.
Article in Journal of computational chemistry, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Molecular Dynamics Workflows to Compute Large-Scale Sets of Absolute Binding Free Energies Aiding Drug Candidate and Binding Pose Selection.Journal of chemical theory and computation · 2026Article
- AmberTools.Journal of chemical information and modeling · 2023Article
- Machine-Learned Molecular Surface and Its Application to Implicit Solvent Simulations.Journal of chemical theory and computation · 2021Article
- Estimating the Roles of Protonation and Electronic Polarization in Absolute Binding Affinity Simulations.Journal of chemical theory and computation · 2021Article
- Recent Developments in Free Energy Calculations for Drug Discovery.Frontiers in molecular biosciences · 2021Review
- Molecular Basis for Polyketide Ketoreductase-Substrate Interactions.International journal of molecular sciences · 2020Article
- Improved Poisson-Boltzmann Methods for High-Performance Computing.Journal of chemical theory and computation · 2019Article
- Heterogeneous Dielectric Implicit Membrane Model for the Calculation of MMPBSA Binding Free Energies.Journal of chemical information and modeling · 2019Article
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Authors and funding
3 authors.
Funding
Abstract
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.
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