Sandberg Lars
Division of Biological Chemistry and Drug Discovery College of Life Sciences, University of Dundee, Dundee, UK,
J Comput Aided Mol Des. 2014 Mar;28(3):211-9. doi: 10.1007/s10822-014-9725-3. Epub 2014 Feb 19.
An implicit solvent model described by a non-simple dielectric medium is used for the prediction of hydration free energies on the dataset of 47 molecules in the SAMPL4 challenge. The solute is represented by a minimal parameter set model based on a new all atom force-field, named the liquid simulation force-field. The importance of a first solvation shell correction to the hydration free energy prediction is discussed and two different approaches are introduced to address it: either with an empirical correction to a few functional groups (alcohol, ether, ester, amines and aromatic nitrogen), or an ab initio correction based on the formation of a solute/explicit water complex. Both approaches give equally good predictions with an average unsigned error <1 kcal/mol. Chemical accuracy is obtained.
一种由非简单介电介质描述的隐式溶剂模型被用于预测SAMPL4挑战中47个分子数据集的水化自由能。溶质由基于一种名为液体模拟力场的新全原子力场的最小参数集模型表示。讨论了第一溶剂化层校正对水化自由能预测的重要性，并介绍了两种不同的方法来解决这个问题：一种是对少数官能团（醇、醚、酯、胺和芳香氮）进行经验校正，另一种是基于溶质/显式水络合物形成的从头算校正。两种方法都给出了同样好的预测，平均无符号误差<1千卡/摩尔。达到了化学精度。
