ArticleJournal of chemical information and modeling2009
Comparison of nine programs predicting pK(a) values of pharmaceutical substances.
Article in Journal of chemical information and modeling, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.
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Who cites it
36 citing papers in PubMed.
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- In Silico Characterization of Glycan Ions from IM-MS Collision Cross Section.Journal of the American Society for Mass Spectrometry · 2025Article
- Interpretable Deep-Learning pJournal of chemical information and modeling · 2025Article
- Comprehensive benchmarking of computational tools for predicting toxicokinetic and physicochemical properties of chemicals.Journal of cheminformatics · 2024Article
- Design, synthesis, and pharmacological evaluation of indazole carboxamides of N-substituted pyrrole derivatives as soybean lipoxygenase inhibitors.Molecular diversity · 2024Article
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- Stability and pJournal of agricultural and food chemistry · 2023Article
- Computational Estimation of the Acidities of Pyrimidines and Related Compounds.Molecules (Basel, Switzerland) · 2022Article
- Improving Small Molecule pKFrontiers in chemistry · 2022Article
- Evaluation of Clove Phytochemicals as Potential Antiviral Drug Candidates Targeting SARS-CoV-2 Main Protease: Computational Docking, Molecular Dynamics Simulation, and Pharmacokinetic Profiling.Frontiers in molecular biosciences · 2022Article
- Evaluation of log P, pKJournal of computer-aided molecular design · 2021Article
- Enhancing Carbon Acid pKMolecules (Basel, Switzerland) · 2021Article
- Overview of the SAMPL6 pKJournal of computer-aided molecular design · 2021Article
- Machine learning meets pKF1000Research · 2020Article
- Open-source QSAR models for pKa prediction using multiple machine learning approaches.Journal of cheminformatics · 2019Article
- One-step Heck Reaction Generates Nonimmunosuppressive FK506 Analogs for Pharmacological BMP Activation.ACS medicinal chemistry letters · 2019Article
- Drug-Membrane Permeability across Chemical Space.ACS central science · 2019Article
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2 authors.
Funding
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.
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