Improving the desolvation penalty in empirical protein pKa modeling

Abstract

Unlike atomistic and continuum models, empirical pk(a) predicting methods need to include desolvation contributions explicitly. This study describes a new empirical desolvation method based on the Born solvation model. The new desolvation model was evaluated by high-level Poisson-Boltzmann calculations, and discussed and compared with the current desolvation model in PROPKA-one of the most widely used empirical protein pK(a) predictors. The new desolvation model was found to remove artificial erratic behavior due to discontinuous jumps from man-made first-shell cutoffs, and thus improves the desolvation description significantly.