The Gaussian Generalized Born model: application to small molecules

Grant, Jennifer; Pickup, Barry T.; Sykes, Matthew J.; Kitchen, C. A.; Nicholls, Anthony

doi:10.1039/b707574j

Cited by 57 publications

(67 citation statements)

References 40 publications

(55 reference statements)

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“…In addition to atomic radii, the user must specify the algorithm used to determine the shape of the solute-solvent interface. A variety of choices are available for these shape algorithms ranging from simple unions of spheres (Lee & Richards, 1971) or Gaussians (Grant, Pickup, Sykes, Kitchen & Nicholls, 2007) to heuristic molecular-accessible surfaces (Connolly, 1983) to thermodynamically defined self-consistent solute-solvent interface definitions (Cheng, Dzubiella, McCammon & Li, 2007; Chen, Baker & Wei, 2010, 2011). Additionally, the user must choose a function to define the ion-accessible regions around the protein; however, this interface is commonly chosen as an ion-accessible union of spheres with radii equal to the atomic radii plus a nominal ionic radius of 0.2 nm.…”

Section: Force Field and Parameter Choicesmentioning

confidence: 99%

Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins

Gunner

Baker

2016

Methods in Enzymology

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Proteins change their charge state through protonation and redox reactions as well as through binding charged ligands. The free energy of these reactions are dominated by solvation and electrostatic energies and modulated by protein conformational relaxation in response to the ionization state changes. Although computational methods for calculating these interactions can provide very powerful tools for predicting protein charge states, they include several critical approximations of which users should be aware. This chapter discusses the strengths, weaknesses, and approximations of popular computational methods for predicting charge states and understanding their underlying electrostatic interactions. The goal of this chapter is to inform users about applications and potential caveats of these methods as well as outline directions for future theoretical and computational research.

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Section: Force Field and Parameter Choicesmentioning

confidence: 99%

Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins

Gunner

Baker

2016

Methods in Enzymology

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“…Implicit solvent models that treat the solvent as a dielectric continuum, and describe the solute molecule as a static atomistic charge distribution 3,49,76,85,131,138,160,169 have become popular recently, due to their simplicity and efficiency. Generalized Born, 7,25,51,66,70,97,114,118,150,152,182 polarizable continuum, 6,18,38,45,82,113,147,151 Poisson-Boltzmann (PB) models 49,62,101,138 and nonlocal dielectric methods 171 are commonly used. Among them, the PB models are the most popular and can be formally derived from Maxwell's theories.…”

Section: Introductionmentioning

confidence: 99%

Multiscale, Multiphysics and Multidomain Models I: Basic Theory

Guo

2013

J. Theor. Comput. Chem.

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This work extends our earlier two-domain formulation of a differential geometry based multiscale paradigm into a multidomain theory, which endows us the ability to simultaneously accommodate multiphysical descriptions of aqueous chemical, physical and biological systems, such as fuel cells, solar cells, nanofluidics, ion channels, viruses, RNA polymerases, molecular motors and large macromolecular complexes. The essential idea is to make use of the differential geometry theory of surfaces as a natural means to geometrically separate the macroscopic domain of solvent from the microscopic domain of solute, and dynamically couple continuum and discrete descriptions. Our main strategy is to construct energy functionals to put on an equal footing of multiphysics, including polar (i.e., electrostatic) solvation, nonpolar solvation, chemical potential, quantum mechanics, fluid mechanics, molecular mechanics, coarse grained dynamics and elastic dynamics. The variational principle is applied to the energy functionals to derive desirable governing equations, such as multidomain Laplace-Beltrami (LB) equations for macromolecular morphologies, multidomain Poisson-Boltzmann (PB) equation or Poisson equation for electrostatic potential, generalized Nernst-Planck (NP) equations for the dynamics of charged solvent species, generalized Navier-Stokes (NS) equation for fluid dynamics, generalized Newton's equations for molecular dynamics (MD) or coarse-grained dynamics and equation of motion for elastic dynamics. Unlike the classical PB equation, our PB equation is an integral-differential equation due to solvent-solute interactions. To illustrate the proposed formalism, we have explicitly constructed three models, a multidomain solvation model, a multidomain charge transport model and a multidomain chemo-electro-fluid-MD-elastic model. Each solute domain is equipped with distinct surface tension, pressure, dielectric function, and charge density distribution. In addition to long-range Coulombic interactions, various non-electrostatic solvent-solute interactions are considered in the present modeling. We demonstrate the consistency between the non-equilibrium charge transport model and the equilibrium solvation model by showing the systematical reduction of the former to the latter at equilibrium. This paper also offers a brief review of the field.

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“…The AGBNP model has been re-implemented and adopted with minor modifications by other investigators 72,73. The main elements of the AGBNP non-polar and electrostatic models have been independently validated,39,40,74,75 and have been incorporated in recently proposed hydration free energy models 76,77…”

Section: Introductionmentioning

confidence: 99%

The AGBNP2 Implicit Solvation Model

Gallicchio

Paris

Levy

2009

J. Chem. Theory Comput.

114

222

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The AGBNP2 implicit solvent model, an evolution of the Analytical Generalized Born plus NonPolar (AGBNP) model we have previously reported, is presented with the aim of modeling hydration effects beyond those described by conventional continuum dielectric representations. A new empirical hydration free energy component based on a procedure to locate and score hydration sites on the solute surface is introduced to model first solvation shell effects, such as hydrogen bonding, which are poorly described by continuum dielectric models. This new component is added to the Generalized Born and non-polar AGBNP terms. Also newly introduced is an analytical Solvent Excluded Volume (SEV) model which improves the solute volume description by reducing the effect of spurious high-dielectric interstitial spaces present in conventional van der Waals representations. The AGBNP2 model is parametrized and tested with respect to experimental hydration free energies of small molecules and the results of explicit solvent simulations. Modeling the granularity of water is one of the main design principles employed for the the first shell solvation function and the SEV model, by requiring that water locations have a minimum available volume based on the size of a water molecule. It is shown that the new volumetric model produces Born radii and surface areas in good agreement with accurate numerical evaluations of these quantities. The results of molecular dynamics simulations of a series of mini-proteins show that the new model produces conformational ensembles in substantially better agreement with reference explicit solvent ensembles than the original AGBNP model with respect to both structural and energetics measures.

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The Gaussian Generalized Born model: application to small molecules

Cited by 57 publications

References 40 publications

Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins

Continuum Electrostatics Approaches to Calculating pKas and Ems in Proteins

Multiscale, Multiphysics and Multidomain Models I: Basic Theory

The AGBNP2 Implicit Solvation Model

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