Department of Nutrition, Food Sciences and Gastronomy, Faculty of Pharmacy and Food Sciences, Institute of Biomedicine (IBUB), and Institute of Theoretical and Computational Chemistry (IQTC-UB), University of Barcelona (UB), Avda. Prat de La Riba, 171, 08921, Santa Coloma de Gramenet, Spain.
Institute of Exact and Natural Sciences, Federal University of Pará, Belém, Pará, 66075-110, Brazil.
J Comput Aided Mol Des. 2021 Jul;35(7):803-811. doi: 10.1007/s10822-021-00394-6. Epub 2021 Jul 10.
Within the scope of SAMPL7 challenge for predicting physical properties, the Integral Equation Formalism of the Miertus-Scrocco-Tomasi (IEFPCM/MST) continuum solvation model has been used for the blind prediction of n-octanol/water partition coefficients and acidity constants of a set of 22 and 20 sulfonamide-containing compounds, respectively. The log P and pK were computed using the B3LPYP/6-31G(d) parametrized version of the IEFPCM/MST model. The performance of our method for partition coefficients yielded a root-mean square error of 1.03 (log P units), placing this method among the most accurate theoretical approaches in the comparison with both globally (rank 8th) and physical (rank 2nd) methods. On the other hand, the deviation between predicted and experimental pK values was 1.32 log units, obtaining the second best-ranked submission. Though this highlights the reliability of the IEFPCM/MST model for predicting the partitioning and the acid dissociation constant of drug-like compounds compound, the results are discussed to identify potential weaknesses and improve the performance of the method.
在 SAMPL7 挑战范围内,用于预测物理性质,Miertus-Scrocco-Tomasi (IEFPCM/MST)连续体溶剂化模型的积分方程形式已分别用于盲预测一组 22 种和 20 种含磺酰胺化合物的正辛醇/水分配系数和酸度常数。使用 IEFPCM/MST 模型的 B3LPYP/6-31G(d)参数化版本计算了 log P 和 pK。对于分配系数,我们方法的性能产生了 1.03 的均方根误差(log P 单位),这使得该方法在与全球(排名第 8)和物理(排名第 2)方法的比较中处于最准确的理论方法之列。另一方面,预测和实验 pK 值之间的偏差为 1.32 个 log 单位,获得了第二好的提交结果。虽然这突出了 IEFPCM/MST 模型在预测药物类似物化合物的分配和酸离解常数方面的可靠性,但讨论了结果以确定方法的潜在弱点并提高性能。