ACD/pKa
Predict accurate acid/base dissociation constants from structure—the industry standard
The acid dissociation constant, Ka, is a measure of the tendency of a molecule or ion to keep a proton (H+) at its ionization center(s). It is
related to the ionization ability of a chemical species and is a core property that defines chemical and biological behaviour. The pKa prediction module in
ACD/Percepta offers a number of useful features depending on the selected prediction algorithm, however, all provide:
- Calculation of accurate acid and base pKa constants (pKa = -logKa) under standard conditions (25°C and zero ionic strength)
in aqueous solutions for every ionizable group within organic structures
- Confidence intervals for all predicted pKa values, indicating their accuracy
- Explicit insight into the prediction protocol for each ionization stage
pKa Algorithms
The pKa prediction module offers two different predictive algorithms within ACD/Percepta software—Classic and GALAS
Classic
The ACD/pKa Classic calculation algorithm is a widely accepted as the industry standard for pKa prediction:
- Liao CZ, Nicklaus MC. Comparison of nine programs predicting pK(a) values of pharmaceutical substances. J. Chem. Inform. Model. 49(12):2801–2812,
2009
- Meloun M, Bordovska S. Benchmarking and validating algorithms that estimate pK(a) values of drugs based on their molecular structures. Anal. Bioanal. Chem.
389(4):1267–1281, 2007
- D.J. Adams and L.R. Morgan. Tumor Physiology and Charge Dynamics of Anticancer Drugs: Implications for Camptothecin-based Drug Development. Curr Med Chem.
18(9):1367–1372, 2011
The algorithm uses Hammet-type equations and electronic substituent constants (σ) to predict pKa values for ionisable groups. Effects considered
by the software include tautomeric equilibria, covalent hydration, and resonance effects in α, β-unsaturated systems.
Hammet-Type Equations—every ionizable group is characterized by several Hammet-type equations that have been parameterized to cover the most
popular ionizable functional groups.
Sigma Constants—the internal training set contains >3000 derived experimental electronic constants. When the required substituent constant is not
available from the experimental database, one of four algorithms are used to describe electronic effect transmissions through the molecular system.
Specific features of this algorithm include:
- Number of compounds in the internal training set: 15,932 (>30,000 pKa values). Data sources: various articles from peer-reviewed scientific journals
- Presentation of a detailed calculation protocol on how prediction has been carried out (including Hammett-type equations, substituent constants, and literature
references where available)
GALAS
Estimation of ionization constants using the GALAS (Global, Adjusted Locally According to Similarity) algorithm is a multi-step procedure involving estimation of pKa microconstants for all possible ionization centers
in the hypothetical state of an uncharged molecule ("fundamental microconstants"), with numerous corrections to these initial pKa values according to the chemical
environment of the reaction center, and calculation of charge influences of ionized groups to neighbouring ionization centers. The Calculation routine utilizes a database of 4600
ionization centers, a set of ca. 500 various interaction constants and four interaction calculation methods for different types of interactions, producing a full range of microconstants
from which pKa macroconstants are obtained. This allows for the simulation of a complete distribution plot of all protonation states of the molecule under different
pH conditions.
Specific features of this algorithm include:
- Number of compounds in the internal training set: 17,593 (>20,000 ionization centers). Data sources:
- Reference books:
- The Merck Index. An Encyclopedia of Chemicals, Drugs, and Biologicals, O'Neil, M.J., Smith, A., Heckelman, P.E., Budavari, S., Eds.
13th Edition, Merck & Co., Inc., Whitehouse Station, NJ, 2001
- Therapeutic Drugs, Dolery, C., Ed. 2nd Edition, Churchill Livingstone, New York, NY, 1999
- Clarke's Isolation and Identification of Drugs, Moffat, A.C., Jackson, J.V., Moss, M.S., Widdop, B., Eds. 2nd Edition,
The Pharmaceutical Press, London, 1986
- Various articles from peer-reviewed scientific journals
- Provides graphical/tabular representation of the obtained predictions in the form of pH dependency of:
- Net molecular charge
- Distribution of protonation states
- Average charge of each ionization centre
Internal pKa Database
A reference database containing high quality experimental data compiled from the literature for nearly 16,000 individual chemical compounds is also available.
Check pKa values that have been reported for molecules in related chemical space.
ACD/Labs Product Suites
The Percepta prediction modules are available as bundles to offer cost savings for multiple modules, and provide related modules as a package.
