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: | t34 | |
|---|---|---|
| Name: | Dibucaine | |
| Description: | ||
| Labels: | ||
| CAS: | 85-79-0 | |
| InChi Code: | InChI=1S/C20H29N3O2/c1-4-7-14-25-19-15-17(16-10-8-9-11-18(16)22-19)20(24)21-12-13-23(5-2)6-3/h8-11,15H,4-7,12-14H2,1-3H3,(H,21,24) |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -4.2 |
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 |
| -4.429 |
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 |
|---|---|
| -4.2 |
experimental value |
| -4.224 |
M2: Model with RDKit descriptors from training set 2 (Training set) |
| -4.607 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Training set) |
| -4.42 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Training set) |