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: | t37 | |
|---|---|---|
| Name: | Metoclopramide | |
| Description: | ||
| Labels: | ||
| CAS: | 364-62-5 | |
| InChi Code: | InChI=1S/C14H22ClN3O2/c1-4-18(5-2)7-6-17-14(19)10-8-11(15)12(16)9-13(10)20-3/h8-9H,4-7,16H2,1-3H3,(H,17,19) |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -3.58 |
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 |
| -2.65 |
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 |
|---|---|
| -3.57 |
experimental value |
| -3.183 |
M2: Model with RDKit descriptors from training set 2 (Training set) |
| -2.601 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Training set) |
| -2.811 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Training set) |