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: | sc78 | |
|---|---|---|
| Name: | Prednisolone,Methyl- | |
| Description: | ||
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C22H30O5/c1-12-8-14-15-5-7-22(27,18(26)11-23)21(15,3)10-17(25)19(14)20(2)6-4-13(24)9-16(12)20/h4,6,9,12,14-15,17,19,23,25,27H,5,7-8,10-11H2,1-3H3/t12-,14-,15-,17-,19+,20-,21-,22-/m0/s1 |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -3.33 |
Avdeef, A. Prediction of aqueous intrinsic solubility of druglike molecules using Random Forest regression trained with Wiki-pS0 database. ADMET DMPK 2020, 8, 29–77. https://doi.org/http://doi.org/10.5599/admet.766 |
| -3.141 |
M1: Model with Dragon descriptors from training set 1 (Tight test set) |
| -3.141 |
M1: Model with Dragon descriptors from training set 1 (Test sets together) |
logS0a: Intrinsic aqueous solubility from multiple sources [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -3.33 |
Avdeef, A. Prediction of aqueous intrinsic solubility of druglike molecules using Random Forest regression trained with Wiki-pS0 database. ADMET DMPK 2020, 8, 29–77. https://doi.org/http://doi.org/10.5599/admet.766 |
| -3.467 |
M2: Model with RDKit descriptors from training set 2 (Tight test set) |
| -3.467 |
M2: Model with RDKit descriptors from training set 2 (Test sets together) |
| -3.64 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Tight test set) |
| -3.64 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Test sets together) |
| -3.416 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Tight test set) |
| -3.416 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Test sets together) |