Progress in developing Poisson-Boltzmann equation
solvers

Li, Chuan; Li, Lin; Petukh, Marharyta; Alexov, Emil

doi:10.2478/mlbmb-2013-0002

Cited by 38 publications

(48 citation statements)

References 179 publications

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“…From computational stand‐point, the electrostatics in molecular biology is modeled via various approaches roughly classified as explicit and implicit approaches . A particular case of implicit modeling is utilizing Poisson–Boltzmann equation (PBE) to deliver the potential distribution and the corresponding electrostatic energy components . A number of computational packages devoted exclusively for solving the PBE have been developed such as DelPhi, MIBPB, PBSA, and APBS .…”

Section: Introductionmentioning

confidence: 99%

“…A number of computational packages devoted exclusively for solving the PBE have been developed such as DelPhi, MIBPB, PBSA, and APBS . The continuum approaches have been successfully used for pH‐dependent simulations, end‐point free energy calculations, calculation of electrostatic components of interaction energy of molecules and effects of mutations, determination of protein pKa values, solving electrostatics of nucleic acids, and numerous other examples …”

Section: Introductionmentioning

confidence: 99%

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Electrostatic component of binding energy: Interpreting predictions from poisson–boltzmann equation and modeling protocols

Chakavorty

Alexov

2016

J Comput Chem

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Macromolecular interactions are essential for understanding numerous biological processes and are typically characterized by the binding free energy. Important component of the binding free energy is the electrostatics, which is frequently modeled via the solutions of the Poisson-Boltzmann Equations (PBE). However, numerous works have shown that the electrostatic component (ΔΔGelec) of binding free energy is very sensitive to the parameters used and modeling protocol. This prompted some researchers to question the robustness of PBE in predicting ΔΔGelec. We argue that the sensitivity of the absolute ΔΔGelec calculated with PBE using different input parameters and definitions does not indicate PBE deficiency, rather this is what should be expected. We show how the apparent sensitivity should be interpreted in terms of the underlying changes in several numerous and physical parameters. We demonstrate that PBE approach is robust within each considered force field (CHARMM-27, AMBER-94 and OPLS-AA) once the corresponding structures are energy minimized. This observation holds despite of using two different molecular surface definitions, pointing again that PBE delivers consistent results within particular force field. The fact that PBE delivered ΔΔGelec values may differ if calculated with different modeling protocols is not a deficiency of PBE, but natural results of the differences of the force field parameters and potential functions for energy minimization. In addition, while the absolute ΔΔGelec values calculated with different force field differ, their ordering remains practically the same allowing for consistent ranking despite of the force field used.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Electrostatic component of binding energy: Interpreting predictions from poisson–boltzmann equation and modeling protocols

Chakavorty

Alexov

2016

J Comput Chem

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“…However, these calculations cannot be done analytically for irregularly shaped objects and numerical methods must be applied. The methods can be grouped into two categories, explicit models and implicit models 6 . Explicit models treat water as individual molecules; in contrast, implicit models average the effect of water phase as continuum media 7-12 .…”

Section: Introductionmentioning

confidence: 99%

On the modeling of polar component of solvation energy using smooth Gaussian-based dielectric function

Alexov

2014

J. Theor. Comput. Chem.

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Traditional implicit methods for modeling electrostatics in biomolecules use a two-dielectric approach: a biomolecule is assigned low dielectric constant while the water phase is considered as a high dielectric constant medium. However, such an approach treats the biomolecule-water interface as a sharp dielectric border between two homogeneous dielectric media and does not account for inhomogeneous dielectric properties of the macromolecule as well. Recently we reported a new development, a smooth Gaussian-based dielectric function which treats the entire system, the solute and the water phase, as inhomogeneous dielectric medium (J Chem Theory Comput. 2013 Apr 9; 9(4): 2126-2136.). Here we examine various aspects of the modeling of polar solvation energy in such inhomogeneous systems in terms of the solute-water boundary and the inhomogeneity of the solute in the absence of water surrounding. The smooth Gaussian-based dielectric function is implemented in the DelPhi finite-difference program, and therefore the sensitivity of the results with respect to the grid parameters is investigated, and it is shown that the calculated polar solvation energy is almost grid independent. Furthermore, the results are compared with the standard two-media model and it is demonstrated that on average, the standard method overestimates the magnitude of the polar solvation energy by a factor 2.5. Lastly, the possibility of the solute to have local dielectric constant larger than of a bulk water is investigated in a benchmarking test against experimentally determined set of pKa's and it is speculated that side chain rearrangements could result in local dielectric constant larger than 80.

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“…Explicit solvent modeling requires significant computational resources, takes a long time, and faces questions about the convergence. Alternatives are offered by implicit solvent models such as Poisson Boltzmann (PB) and Generalized Born approaches . Particularly, PB approach has been explored by many researchers resulting into various software such as DelPhi, PBSA, MIBPB, APBS, and others …”

Section: Introductionmentioning

confidence: 99%

DelPhi Suite: New Developments and Review of Functionalities

Jia

Chakravorty

et al. 2019

J Comput Chem

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Electrostatic potential, energies, and forces affect virtually any process in molecular biology, however, computing these quantities is a difficult task due to irregularly shaped macromolecules and the presence of water. Here, we report a new edition of the popular software package DelPhi along with describing its functionalities. The new DelPhi is a C++ object‐oriented package supporting various levels of multiprocessing and memory distribution. It is demonstrated that multiprocessing results in significant improvement of computational time. Furthermore, for computations requiring large grid size (large macromolecular assemblages), the approach of memory distribution is shown to reduce the requirement of RAM and thus permitting large‐scale modeling to be done on Linux clusters with moderate architecture. The new release comes with new features, whose functionalities and applications are described as well. © 2019 The Authors. Journal of Computational Chemistry published by Wiley Periodicals, Inc.

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Progress in developing Poisson-Boltzmann equation solvers

Cited by 38 publications

References 179 publications

Electrostatic component of binding energy: Interpreting predictions from poisson–boltzmann equation and modeling protocols

Electrostatic component of binding energy: Interpreting predictions from poisson–boltzmann equation and modeling protocols

On the modeling of polar component of solvation energy using smooth Gaussian-based dielectric function

DelPhi Suite: New Developments and Review of Functionalities

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