Improvements to the APBS biomolecular solvation software suite

The Adaptive Poisson-Boltzmann Solver (APBS) software was developed to solve the equations of continuum electrostatics for large biomolecular assemblages that has provided impact in the study of a broad range of chemical, biological, and biomedical applications. APBS addresses 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 manuscript, 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 p$K_a$ values, and an improved web-based visualization tool for viewing electrostatics

Molecular theory of solvation: Methodology summary and illustrations

Integral equation theory of molecular liquids based on statistical mechanics is quite promising as an essential part of multiscale methodology for chemical and biomolecular nanosystems in solution. Beginning with a molecular interaction potential force field, it uses diagrammatic analysis of the solvation free energy to derive integral equations for correlation functions between molecules in solution in the statistical-mechanical ensemble. The infinite chain of coupled integral equations for many-body correlation functions is reduced to a tractable form for 2- or 3-body correlations by applying the so-called closure relations. Solving these equations produces the solvation structure with accuracy comparable to molecular simulations that have converged but has a critical advantage of readily treating the effects and processes spanning over a large space and slow time scales, by far not feasible for explicit solvent molecular simulations. One of the versions of this formalism, the three-dimensional reference interaction site model (3D-RISM) integral equation complemented with the Kovalenko-Hirata (KH) closure approximation, yields the solvation structure in terms of 3D maps of correlation functions, including density distributions, of solvent interaction sites around a solute (supra)molecule with full consistent account for the effects of chemical functionalities of all species in the solution. The solvation free energy and the subsequent thermodynamics are then obtained at once as a simple integral of the 3D correlation functions by performing thermodynamic integration analytically.Comment: 24 pages, 10 figures, Revie

Progress in the Prediction of pKa Values in Proteins

The pKa-cooperative aims to provide a forum for experimental and theoretical researchers interested in protein pKa values and protein electrostatics in general. The first round of the pKa-cooperative, which challenged computational labs to carry out blind predictions against pKas experimentally determined in the laboratory of Bertrand Garcia-Moreno, was completed and results discussed at the Telluride meeting (July 6–10, 2009). This article serves as an introduction to the reports submitted by the blind prediction participants that will be published in a special issue of PROTEINS: Structure, Function and Bioinformatics. Here, we briefly outline existing approaches for pKa calculations, emphasizing methods that were used by the participants in calculating the blind pKa values in the first round of the cooperative. We then point out some of the difficulties encountered by the participating groups in making their blind predictions, and finally try to provide some insights for future developments aimed at improving the accuracy of pKa calculations