ArticleJournal of chemical theory and computation2011
A Fast and Robust Poisson-Boltzmann Solver Based on Adaptive Cartesian Grids.
Article in Journal of chemical theory and computation, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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Who cites it
13 citing papers in PubMed.
- Article
- Computational modeling of protein conformational changes - Application to the opening SARS-CoV-2 spike.Journal of computational physics · 2021Article
- An efficient second-order poisson-boltzmann method.Journal of computational chemistry · 2019Article
- Accuracy Comparison of Generalized Born Models in the Calculation of Electrostatic Binding Free Energies.Journal of chemical theory and computation · 2018Article
- Problems of robustness in Poisson-Boltzmann binding free energies.Journal of chemical theory and computation · 2015Article
- Features of CPB: a Poisson-Boltzmann solver that uses an adaptive Cartesian grid.Journal of computational chemistry · 2015Article
- Poisson-Boltzmann versus Size-Modified Poisson-Boltzmann Electrostatics Applied to Lipid Bilayers.The journal of physical chemistry. B · 2014Article
- Excluded volume and ion-ion correlation effects on the ionic atmosphere around B-DNA: theory, simulations, and experiments.The Journal of chemical physics · 2014Article
- Sensitivities to parameterization in the size-modified Poisson-Boltzmann equation.The Journal of chemical physics · 2014Article
- Influence of Grid Spacing in Poisson-Boltzmann Equation Binding Energy Estimation.Journal of chemical theory and computation · 2013Article
- Progress in developing Poisson-Boltzmann equation solvers.Molecular based mathematical biology · 2013Article
- Formulation of a new and simple nonuniform size-modified Poisson-Boltzmann description.Journal of computational chemistry · 2012Article
- The ionic atmosphere around A-RNA: Poisson-Boltzmann and molecular dynamics simulations.Biophysical journal · 2012Article
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2 authors.
Funding
Abstract
An adaptive Cartesian grid (ACG) concept is presented for the fast and robust numerical solution of the 3D Poisson-Boltzmann Equation (PBE) governing the electrostatic interactions of large-scale biomolecules and highly charged multi-biomolecular assemblies such as ribosomes and viruses. The ACG offers numerous advantages over competing grid topologies such as regular 3D lattices and unstructured grids. For very large biological molecules and multi-biomolecule assemblies, the total number of grid-points is several orders of magnitude less than that required in a conventional lattice grid used in the current PBE solvers thus allowing the end user to obtain accurate and stable nonlinear PBE solutions on a desktop computer. Compared to tetrahedral-based unstructured grids, ACG offers a simpler hierarchical grid structure, which is naturally suited to multigrid, relieves indirect addressing requirements and uses fewer neighboring nodes in the finite difference stencils. Construction of the ACG and determination of the dielectric/ionic maps are straightforward, fast and require minimal user intervention. Charge singularities are eliminated by reformulating the problem to produce the reaction field potential in the molecular interior and the total electrostatic potential in the exterior ionic solvent region. This approach minimizes grid-dependency and alleviates the need for fine grid spacing near atomic charge sites. The technical portion of this paper contains three parts. First, the ACG and its construction for general biomolecular geometries are described. Next, a discrete approximation to the PBE upon this mesh is derived. Finally, the overall solution procedure and multigrid implementation are summarized. Results obtained with the ACG-based PBE solver are presented for: (i) a low dielectric spherical cavity, containing interior point charges, embedded in a high dielectric ionic solvent - analytical solutions are available for this case, thus allowing rigorous assessment of the solution accuracy; (ii) a pair of low dielectric charged spheres embedded in a ionic solvent to compute electrostatic interaction free energies as a function of the distance between sphere centers; (iii) surface potentials of proteins, nucleic acids and their larger-scale assemblies such as ribosomes; and (iv) electrostatic solvation free energies and their salt sensitivities - obtained with both linear and nonlinear Poisson-Boltzmann equation - for a large set of proteins. These latter results along with timings can serve as benchmarks for comparing the performance of different PBE solvers.
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