The SAMPL8 blind prediction challenge, which addresses the acid/base dissociation constants (pKa) and the distribution coefficients (logD), was addressed by the Conductor like Screening Model for Realistic Solvation (COSMO-RS). Using the COSMOtherm implementation of COSMO-RS together with a rigorous conformational sampling, yielded logD predictions with a root mean square deviation (RMSD) of 1.36 log units over all 11 compounds and seven bi-phasic systems of the data set, which was the most accurate of all contest submissions (logD).

For the SAMPL8 pKa competition, participants were asked to report the standard state free energies of all microstates, which were then used to calculate the macroscopic pKa. We have used COSMO-RS based linear free energy fit models to calculate the requested energies. The assignment of the calculated and experimental pKa values was made on the basis of the popular transitions, i.e. the transition hat was predicted by the majority of the submissions. With this assignment and a model that covers both, pKa and base pKa, we achieved an RMSD of 3.44 log units (18 pKa values of 14 molecules), which is the second place of the six ranked submissions. By changing to an assignment that is based on the experimental transition curves, the RMSD reduces to 1.65. In addition to the ranked contribution, we submitted two more data sets, one for the standard pKa model and one or the standard base pKa model of COSMOtherm. Using the experiment based assignment with the predictions of the two sets we received a RMSD of 1.42 log units (25 pKa values of 20 molecules). The deviation mainly arises from a single outlier compound, the omission of which leads to an RMSD of 0.89 log units.

SAMPL8 盲预测挑战解决了酸/碱解离常数 (pKa) 和分配系数 (logD)，由类似导体的现实溶剂化筛选模型 (COSMO-RS) 解决。使用 COSMO-RS 的 COSMOtherm 实现以及严格的构象采样，对数据集的所有 11 种化合物和 7 个双相系统产生了均方根偏差 (RMSD) 为 1.36 个对数单位的 logD 预测，这是最所有竞赛提交内容的准确性 (logD)。

在 SAMPL8 pKa 竞赛中，参与者被要求报告所有微观态的标准态自由能，然后将其用于计算宏观 pKa。我们使用基于 COSMO-RS 的线性自由能拟合模型来计算所需的能量。计算和实验 pKa 值的分配是根据流行的转变进行的，即转变帽子是由大多数提交的内容预测的。通过这项任务以及涵盖 pKa 和基础 pKa 的模型，我们获得了 3.44 个对数单位的 RMSD（14 个分子的 18 个 pKa 值），在六份排名提交的作品中排名第二。通过更改为基于实验转换曲线的分配，RMSD 降至 1.65。除了排名贡献之外，我们还提交了两个数据集，一种为标准 pKa 模型，一种为 COSMotherm 的标准基础 pKa 模型。使用基于实验的分配和两组预测，我们得到的 RMSD 为 1.42 个对数单位（20 个分子的 25 个 pKa 值）。偏差主要源自单个离群化合物，遗漏该离群化合物会导致 RMSD 为 0.89 对数单位。