pKa prediction in non-aqueous solvents

IF 3.4 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY Journal of Computational Chemistry Pub Date : 2024-12-11 DOI:10.1002/jcc.27517
Jonathan W. Zheng, Emad Al Ibrahim, Ivari Kaljurand, Ivo Leito, William H. Green
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Abstract

Acid dissociation constants ( p K a $$ \mathrm{p}{K}_{\mathrm{a}} $$ ) are widely measured and studied, most typically in water. Comparatively few datasets and models for non-aqueous p K a $$ \mathrm{p}{K}_{\mathrm{a}} $$ values exist. In this work, we demonstrate how the p K a $$ \mathrm{p}{K}_{\mathrm{a}} $$ in one solvent can be accurately determined using reference data in another solvent, corrected by solvation energy calculations from the COSMO-RS method. We benchmark this approach in 10 different solvents, and find that p K a $$ \mathrm{p}{K}_{\mathrm{a}} $$ values calculated in six solvents deviate from experimental data on average by less than 1 p K a $$ \mathrm{p}{K}_{\mathrm{a}} $$ unit. We observe comparable performance on a more diverse test set including amino acids and drug molecules, with higher error for large molecules. The model performance in four other solvents is worse, with one MAE exceeding 3 p K a $$ \mathrm{p}{K}_{\mathrm{a}} $$ units; we discuss how such errors arise due to both model error and inconsistency in obtaining experimental data. Finally, we demonstrate how this technique can be used to estimate the proton transfer energy between different solvents, and use this to report a value of the proton's solvation energy in formamide, a quantity that does not have a consensus value in literature.

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非水溶剂的pKa预测
酸解离常数(p²Ka $$ \mathrm{p}{K}_{\mathrm{a}} $$)被广泛测量和研究,最典型的是在水中。相对较少的非水p²Ka $$ \mathrm{p}{K}_{\mathrm{a}} $$值的数据集和模型存在。在这项工作中,我们展示了如何使用另一种溶剂中的参考数据准确地确定一种溶剂中的p²Ka $$ \mathrm{p}{K}_{\mathrm{a}} $$,并通过cosmos - rs方法的溶剂化能计算进行校正。我们在10种不同的溶剂中对这种方法进行了基准测试,发现在6种溶剂中计算的p²Ka $$ \mathrm{p}{K}_{\mathrm{a}} $$值与实验数据的平均偏差小于1 p²Ka $$ \mathrm{p}{K}_{\mathrm{a}} $$单位。我们在更多样化的测试集上观察到类似的性能,包括氨基酸和药物分子,大分子的误差更高。模型在其他四种溶剂中的性能较差,有一种MAE超过3 p²Ka $$ \mathrm{p}{K}_{\mathrm{a}} $$单位;我们讨论了这些误差是如何由于模型误差和实验数据的不一致而产生的。最后,我们演示了如何使用这种技术来估计不同溶剂之间的质子转移能,并使用它来报告质子在甲酰胺中的溶剂化能值,这个量在文献中没有一致的值。
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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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