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: | sc34 | |
|---|---|---|
| Name: | Diflorasone Diacetate | |
| Description: | ||
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C26H32F2O7/c1-13-8-17-18-10-20(27)19-9-16(31)6-7-23(19,4)25(18,28)21(32)11-24(17,5)26(13,35-15(3)30)22(33)12-34-14(2)29/h6-7,9,13,17-18,20-21,32H,8,10-12H2,1-5H3/t13-,17-,18-,20-,21-,23-,24-,25-,26-/m0/s1 |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -4.82 |
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 |
| -3.828 |
M1: Model with Dragon descriptors from training set 1 (Tight test set) |
| -3.828 |
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 |
|---|---|
| -4.82 |
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 |
| -4.672 |
M2: Model with RDKit descriptors from training set 2 (Tight test set) |
| -4.672 |
M2: Model with RDKit descriptors from training set 2 (Test sets together) |
| -3.698 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Tight test set) |
| -3.698 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Test sets together) |
| -4.066 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Tight test set) |
| -4.066 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Test sets together) |