Some challenges of diffused interfaces in implicit-solvent models

Abstract

The standard Poisson-Boltzmann model for molecular electrostatics assumes a sharp variation of the permittivity and salt concentration along the solute-solvent interface. The discontinuous field parameters are not only difficult numerically, but also are not a realistic physical picture, as it forces the dielectric constant and ionic strength of bulk in the near-solute region. An alternative to alleviate some of these issues is to represent the molecular surface as a diffuse interface, however, this also presents challenges. In this work we analysed the impact of the shape of the interfacial variation of the field parameters in solvation and binding energy. However we used a hyperbolic tangent function ($\tanh (k_{p}x)$) to couple the internal and external regions, our analysis is valid for other definitions. Our methodology was based on a coupled finite element (FEM) and boundary element (BEM) scheme that allowed us to have a special treatment of the permittivity and ionic strength in a bounded FEM region near the interface, while maintaining BEM elsewhere. Our results suggest that the shape of the function (represented by $k_p$) has a large impact on solvation and binding energy. We saw that high values of $k_p$ induce a high gradient on the interface, to the limit of recovering the sharp jump when $k_p\to \infty$, presenting a numerical challenge where careful meshing is key. Using the FreeSolv database to compare with molecular dynamics, our calculations indicate that an optimal value of $k_p$ for solvation energies was around 3. However, more challenging binding free energy tests make this conclusion more difficult, as binding showed to be very sensitive to small variations of $k_p$. In that case, optimal values of $k_p$ ranged from 2 to 20.

References in corpus (10)

• Improvements to the APBS biomolecular solvation software suite
• Anomalously low dielectric constant of confined water
• DOLFIN: Automated Finite Element Computing
• A biomolecular electrostatics solver using Python, GPUs and boundary elements that can handle solvent-filled cavities and Stern layers
• An Open Source Mesh Generation Platform for Biophysical Modeling Using Realistic Cellular Geometries
• Arbitrarily Accurate Analytical Approximations for the Error Function
• Linear scaling computation of forces for the domain-decomposition linear Poisson--Boltzmann method
• Coupling finite and boundary element methods to solve the Poisson--Boltzmann equation for electrostatics in molecular solvation
• Accurate, robust and reliable calculations of Poisson-Boltzmann binding energies
• Domain Decomposition Method for Poisson--Boltzmann Equations based on Solvent Excluded Surface

Cited by in corpus (1)

• NextGenPB: an analytically-enabled super resolution and local (de)refinement Poisson-Boltzmann Equation solver