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: | t56 | |
|---|---|---|
| Name: | Cyproheptadine | |
| Description: | ||
| Labels: | ||
| CAS: | 129-03-3 | |
| InChi Code: | InChI=1S/C21H21N/c1-22-14-12-18(13-15-22)21-19-8-4-2-6-16(19)10-11-17-7-3-5-9-20(17)21/h2-11H,12-15H2,1H3 |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -5 |
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 |
| -4.914 |
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 |
|---|---|
| -5.02 |
experimental value |
| -4.402 |
M2: Model with RDKit descriptors from training set 2 (Training set) |
| -4.894 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Training set) |
| -4.737 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Training set) |