Partition coefficients quantify a molecule’s distribution between two immiscible liquid phases. While there are many methods to compute them, there is not yet a method based on the free energy of each system in terms of energy and entropy, where entropy depends on the probability distribution of all quantum states of the system. Here we test a method in this class called Energy Entropy Multiscale Cell Correlation (EE-MCC) for the calculation of octanol–water logP values for 22 N-acyl sulfonamides in the SAMPL7 Physical Properties Challenge (Statistical Assessment of the Modelling of Proteins and Ligands). EE-MCC logP values have a mean error of 1.8 logP units versus experiment and a standard error of the mean of 1.0 logP units for three separate calculations. These errors are primarily due to getting sufficiently converged energies to give accurate differences of large numbers, particularly for the large-molecule solvent octanol. However, this is also an issue for entropy, and approximations in the force field and MCC theory also contribute to the error. Unique to MCC is that it explains the entropy contributions over all the degrees of freedom of all molecules in the system. A gain in orientational entropy of water is the main favourable entropic contribution, supported by small gains in solute vibrational and orientational entropy but offset by unfavourable changes in the orientational entropy of octanol, the vibrational entropy of both solvents, and the positional and conformational entropy of the solute.

分配系数量化了分子在两个不混溶液相之间的分布。虽然计算它们的方法有很多，但还没有一种基于每个系统在能量和熵方面的自由能的方法，其中熵取决于系统所有量子态的概率分布。在这里，我们测试了此类中称为能量熵多尺度单元相关性 (EE-MCC) 的方法，用于计算 SAMPL7 物理性质挑战赛（蛋白质和配体建模的统计评估）中 22 个 N-酰基磺酰胺的辛醇-水 logP 值）。对于三个单独的计算，EE-MCC logP 值与实验相比的平均误差为 1.8 logP 单位，标准误差为 1.0 logP 单位的平均值。这些误差主要是由于获得足够收敛的能量以给出大数的精确差异，特别是对于大分子溶剂辛醇。然而，这也是熵的一个问题，力场和 MCC 理论中的近似也会导致误差。 MCC 的独特之处在于它解释了系统中所有分子的所有自由度的熵贡献。水的取向熵的增加是主要有利的熵贡献，由溶质振动和取向熵的小幅增加支持，但被辛醇的取向熵、两种溶剂的振动熵以及溶剂的位置和构象熵的不利变化所抵消。溶质。