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• W2547611602 endingPage "707" @default.
• W2547611602 startingPage "699" @default.
• W2547611602 abstract "Rapid yet accurate pKa prediction for druglike molecules is a key challenge in computational chemistry. This study uses PM6-DH+/COSMO, PM6/COSMO, PM7/COSMO, PM3/COSMO, AM1/COSMO, PM3/SMD, AM1/SMD, and DFTB3/SMD to predict the pKa values of 53 amine groups in 48 druglike compounds. The approach uses an isodesmic reaction where the pKa value is computed relative to a chemically related reference compound for which the pKa value has been measured experimentally or estimated using a standard empirical approach. The AM1- and PM3-based methods perform best with RMSE values of 1.4–1.6 pH units that have uncertainties of ±0.2–0.3 pH units, which make them statistically equivalent. However, for all but PM3/SMD and AM1/SMD the RMSEs are dominated by a single outlier, cefadroxil, caused by proton transfer in the zwitterionic protonation state. If this outlier is removed, the RMSE values for PM3/COSMO and AM1/COSMO drop to 1.0 ± 0.2 and 1.1 ± 0.3, whereas PM3/SMD and AM1/SMD remain at 1.5 ± 0.3 and 1.6 ± 0.3/0.4 pH units, making the COSMO-based predictions statistically better than the SMD-based predictions. For pKa calculations where a zwitterionic state is not involved or proton transfer in a zwitterionic state is not observed, PM3/COSMO or AM1/COSMO is the best pKa prediction method; otherwise PM3/SMD or AM1/SMD should be used. Thus, fast and relatively accurate pKa prediction for 100–1000s of druglike amines is feasible with the current setup and relatively modest computational resources." @default.
• W2547611602 created "2016-11-11" @default.
• W2547611602 creator A5002139604 @default.
• W2547611602 creator A5053685425 @default.
• W2547611602 creator A5071409001 @default.
• W2547611602 date "2017-01-12" @default.
• W2547611602 modified "2023-10-14" @default.
• W2547611602 title "Prediction of p<i>K</i>_a Values for Druglike Molecules Using Semiempirical Quantum Chemical Methods" @default.
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• W2547611602 doi "https://doi.org/10.1021/acs.jpca.6b10990" @default.
• W2547611602 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/28054775" @default.
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