Comparison of Nine Programs Predicting p Ka Values of Pharmaceutical Substances

Abstract

Knowledge of the possible ionization states of a pharmaceutical substance, embodied in the pK(a) values (logarithm of the acid dissociation constant), is vital for understanding many properties essential to drug development. We compare nine commercially available or free programs for predicting ionization constants. Eight of these programs are based on empirical methods: ACD/pK(a) DB 12.0, ADME Boxes 4.9, ADMET Predictor 3.0, Epik 1.6, Marvin 5.1.4, Pallas pKalc Net 2.0, Pipeline Pilot 5.0, and SPARC 4.2; one program is based on a quantum chemical method: Jaguar 7.5. We compared their performances by applying them to 197 pharmaceutical substances with 261 carefully determined and highly reliable experimental pK(a) values from a literature source. The programs ADME Boxes 4.9, ACD/pK(a) DB 12.0, and SPARC 4.2 ranked as the top three with mean absolute deviations of 0.389, 0.478, and 0.651 and r(2) values of 0.944, 0.908, and 0.894, respectively. ACD/pK(a) DB 12.0 predicted all sites, whereas ADME Boxes 4.9 and SPARC 4.2 failed to predict 5 and 18 sites, respectively. The performance of the quantum chemical-based program Jaguar 7.5 was not as expected, with a mean absolute deviation of 1.283 and an r(2) value of 0.579, indicating the potential for further development of this type of approach to pK(a) prediction.