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. 2018 Jan;27(1):112-128.
doi: 10.1002/pro.3280. Epub 2017 Oct 24.

Improvements to the APBS biomolecular solvation software suite

Affiliations

Improvements to the APBS biomolecular solvation software suite

Elizabeth Jurrus et al. Protein Sci. 2018 Jan.

Abstract

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that have provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses the three key technology challenges for understanding solvation and electrostatics in biomedical applications: accurate and efficient models for biomolecular solvation and electrostatics, robust and scalable software for applying those theories to biomolecular systems, and mechanisms for sharing and analyzing biomolecular electrostatics data in the scientific community. To address new research applications and advancing computational capabilities, we have continually updated APBS and its suite of accompanying software since its release in 2001. In this article, we discuss the models and capabilities that have recently been implemented within the APBS software package including a Poisson-Boltzmann analytical and a semi-analytical solver, an optimized boundary element solver, a geometry-based geometric flow solvation model, a graph theory-based algorithm for determining pKa values, and an improved web-based visualization tool for viewing electrostatics.

Keywords: electrostatics; pKa; software; solvation; titration.

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Figures

Figure 1
Figure 1
Workflow for biomolecular electrostatics calculations using the APBS‐PDB2PQR software suite. This workflow is supported by the APBS tool suite with specific support by PDB2PQR for preparing biomolecular structures (see the section “Preparing Biomolecular Structures”) and support by APBS for performing electrostatics calculations (see the section “Solving the Poisson–Boltzmann and Related Solvation Equations”).
Figure 2
Figure 2
Electrostatic potential visualization of protein with PDB ID 3app for (A) APBS multigrid and (B) TABI‐PB. VMD64 was used to generate the figure in (A), and VTK to generate the figure in (B). The potentials are on a [4,4] red–white–blue color map in units of kJ/mol/e. Calculations were performed at 0.15 M ionic strength in monovalent salt, 298.15 K, protein dielectric 2, and solvent dielectric 78.
Figure 3
Figure 3
Comparison of APBS, PB‐AM, and PB‐SAM results (A–C) and electrostatic potential visualization for APBS PB‐AM and PB‐SAM (D–E). VMD64 isosurface of barnase molecule generated using (A) APBS boundary element method, (B) APBS PB‐AM method, and (C) APBS PB‐SAM method. (A–C) atoms colored according to their charge and isosurfaces are drawn at 1.0 (blue) and −1.0 (red) kT/e electrostatic potential. (D) APBS PB‐AM potential on the coarse‐grain surface of the barnase molecule, (E) APBS PB‐SAM potential in a 2D plane surrounding the barstar molecule, and (F) APBS PB‐SAM potential over range [1,1] on the coarse‐grain surface of the barnase molecule (blue region is the location of positive electrostatic potential and barstar association). All calculations were performed at 0.0 M ionic strength, 300 Kelvin, pH 7, protein dielectric 2, and solvent dielectric 78. All electrostatic potentials are given in units of kT/e.
Figure 4
Figure 4
3Dmol.js interface displaying a rendering of fasciculin‐2 (1FAS) protein with translucent, solvent‐accessible surface using a stick model and red–green–blue color scheme.
Figure 5
Figure 5
Renderings of three different proteins: actinidin (2ACT) (top), fasciculin‐2 (1FAS) (center), and pepsin‐penicillium (2APP) (bottom). To demonstrate the different visualization options. From left to right: solvent‐accessible surface, solvent‐excluded surface, van der Waals surface, and cartoon models are shown all using red–white–blue color scheme (excluding cartoon model), where red and blue correspond to negative and positive electrostatic potentials, respectively.
Figure A1
Figure A1
APBS TABI‐PB electrostatic potential results for PDB ID 1a63. Surfaces were generated with (A) 20228 triangles via MSMS,62 (B) 20744 triangles via NanoShaper SES, and (C) 21084 triangles via NanoShaper Skin.63 These discretizations resulted in surface potentials (with units kT/e) of (D) MSMS in range [8.7,8.6], (E) NanoShaper SES in range [13.4,7.5], and (F) NanoShaper Skin in range [33.8,8.0]. All calculations were performed at 0.15 M ionic strength in 1:1 salt, with protein dielectric 1, solvent dielectric 80, and temperature 300 K. Red and blue surface colors correspond to negative and positive electrostatic surface potentials, respectively.

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