ArticleJournal of computational chemistry2017
Accurate, robust, and reliable calculations of Poisson-Boltzmann binding energies.
Article in Journal of computational chemistry, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Implicit Solvent Models and Their Applications in Biophysics.Biomolecules · 2025Review
- Poisson-Boltzmann-based machine learning model for electrostatic analysis.Biophysical journal · 2024Article
- Bridging Eulerian and Lagrangian Poisson-Boltzmann solvers by ESES.Journal of computational chemistry · 2024Article
- Developing an Implicit Solvation Machine Learning Model for Molecular Simulations of Ionic Media.Journal of chemical theory and computation · 2024Article
- A Closed-Form, Analytical Approximation for Apparent Surface Charge and Electric Field of Molecules.ACS omega · 2022Article
- MLIMC: Machine Learning-Based Implicit-Solvent Monte Carlo.Chinese journal of chemical physics · 2021Article
- Computational modeling of protein conformational changes - Application to the opening SARS-CoV-2 spike.Journal of computational physics · 2021Article
- Molecular Dynamics of Cobalt Protoporphyrin Antagonism of the Cancer Suppressor REV-ERBβ.Molecules (Basel, Switzerland) · 2021Article
- The de Rham-Hodge Analysis and Modeling of Biomolecules.Bulletin of mathematical biology · 2020Article
- An efficient second-order poisson-boltzmann method.Journal of computational chemistry · 2019Article
- Combining the polarizable Drude force field with a continuum electrostatic Poisson-Boltzmann implicit solvation model.Journal of computational chemistry · 2018Article
- Grid-Based Surface Generalized Born Model for Calculation of Electrostatic Binding Free Energies.Journal of chemical information and modeling · 2017Article
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3 authors.
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Abstract
Poisson-Boltzmann (PB) model is one of the most popular implicit solvent models in biophysical modeling and computation. The ability of providing accurate and reliable PB estimation of electrostatic solvation free energy, ΔGel, and binding free energy, ΔΔGel, is important to computational biophysics and biochemistry. In this work, we investigate the grid dependence of our PB solver (MIBPB) with solvent excluded surfaces for estimating both electrostatic solvation free energies and electrostatic binding free energies. It is found that the relative absolute error of ΔGel obtained at the grid spacing of 1.0 Å compared to ΔGel at 0.2 Å averaged over 153 molecules is less than 0.2%. Our results indicate that the use of grid spacing 0.6 Å ensures accuracy and reliability in ΔΔGel calculation. In fact, the grid spacing of 1.1 Å appears to deliver adequate accuracy for high throughput screening. © 2017 Wiley Periodicals, Inc.
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