Oja, M.; Sild, S.; Piir, G.; Maran, U. Intrinsic aqueous solubility: mechanistically transparent data-driven modeling of drug substances. Pharmaceutics 2022, 14, 2248.
Compound
| ID: | t64 | |
|---|---|---|
| Name: | Metoprolol | |
| Description: | ||
| Labels: | ||
| CAS: | 51384-51-1 | |
| InChi Code: | InChI=1/C15H25NO3/c1-12(2)16-10-14(17)11-19-15-6-4-13(5-7-15)8-9-18-3/h4-7,12,14,16-17H,8-11H2,1-3H3 |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -1.22 |
Avdeef, A. Multi-lab intrinsic solubility measurement reproducibility in CheqSol and shake-flask methods. ADMET DMPK 2019, 7, 210–219. https://doi.org/http://doi.org/10.5599/admet.698 |
| -1.979 |
M1: Model with Dragon descriptors from training set 1 (Training set) |
logS0a: Intrinsic aqueous solubility from multiple sources [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -1.265 |
experimental value |
| -2.572 |
M2: Model with RDKit descriptors from training set 2 (Training set) |
| -2.319 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Training set) |
| -2.29 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Training set) |