We applied the COSMO-RS method to predict the partition coefficient logP between water and 1-octanol for 22 small drug like molecules within the framework of the SAMPL7 blind challenge. We carefully collected a set of thermodynamically meaningful microstates, including tautomeric forms of the neutral species, and calculated the logP using the current COSMOtherm implementation on the most accurate level. With this approach, COSMO-RS was ranked as the 6st most accurate method (Measured by the mean absolute error (MAE) of 0.57) over all 17 ranked submissions. We achieved a root mean square deviation (RMSD) of 0.78. The largest deviations from experimental values are exhibited by five SAMPL molecules (SM), which seem to be shifted in most SAMPL7 contributions. In context with previous SAMPL challenges, COSMO-RS demonstrates a wide range of applicability and one of the best in class reliability and accuracy among the physical methods.

我们应用 COSMO-RS 方法来预测 SAMPL7 盲挑战框架内 22 种小药物样分子的水和 1-辛醇之间的分配系数 logP。我们仔细收集了一组具有热力学意义的微状态，包括中性物种的互变异构形式，并使用当前 COSMOtherm 实现在最准确的水平上计算了 logP。使用这种方法，COSMO-RS 在所有 17 个排名提交的提交中被评为第 6 位最准确的方法（通过 0.57 的平均绝对误差 (MAE) 衡量）。我们实现了 0.78 的均方根偏差 (RMSD)。五个 SAMPL 分子 (SM) 表现出与实验值的最大偏差，它们似乎在大多数 SAMPL7 贡献中发生了变化。在之前的 SAMPL 挑战中，