Jan H. Jensen

TL;DR: A description of the ab initio quantum chemistry package GAMESS, which can be treated with wave functions ranging from the simplest closed‐shell case up to a general MCSCF case, permitting calculations at the necessary level of sophistication.

TL;DR: The rules and parameters for one of the most commonly used empirical pKa predictors, PROPKA, are revised based on better physical description of the desolvation and dielectric response for the protein, and a new and consistent approach to interpolate the description between the previously distinct classifications into internal and surface residues is introduced.

TL;DR: A very fast empirical method is presented for structure‐based protein pKa prediction and rationalization and unusual pKa values at buried active sites are predicted very well with the empirical method.

TL;DR: The significantly expanded PDB2PQR is reported that includes robust standalone command line support, improved pKa estimation via the PROPKA framework, ligand parameterization via PEOE_PB charge methodology, expanded set of force fields and easily incorporated user-defined parameters via XML input files, and improvement of atom addition and optimization code.

TL;DR: A novel algorithm is presented that identifies noncovalently coupled ionizable groups, where pKa prediction may be especially difficult, which is a general improvement to PROPKA and is applied to proteins with and without ligands.