Department of Chemistry, University of Copenhagen, Universitetsparken 5, 2100 Copenhagen, Denmark.
J Mol Model. 2012 Mar;18(3):1097-106. doi: 10.1007/s00894-011-1141-1. Epub 2011 Jun 14.
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.
与原子模型和连续体模型不同，经验性 pk(a)预测方法需要明确包括去溶剂化贡献。本研究描述了一种基于 Born 溶剂化模型的新经验性去溶剂化方法。通过高级泊松-玻尔兹曼计算对新的去溶剂化模型进行了评估，并与 PROPKA 中最广泛使用的经验性蛋白质 pk(a)预测器之一的当前去溶剂化模型进行了讨论和比较。新的去溶剂化模型消除了由于人为第一壳层截止值不连续跳跃而产生的人为不规则行为，从而大大改善了去溶剂化描述。
