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: | sc106 | |
|---|---|---|
| Name: | Buprenorphine | |
| Description: | ||
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C29H41NO4/c1-25(2,3)26(4,32)20-15-27-10-11-29(20,33-5)24-28(27)12-13-30(16-17-6-7-17)21(27)14-18-8-9-19(31)23(34-24)22(18)28/h8-9,17,20-21,24,31-32H,6-7,10-16H2,1-5H3/t20-,21-,24-,26?,27-,28+,29-/m1/s1 |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -6.07 |
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 |
| -5.06 |
M1: Model with Dragon descriptors from training set 1 (Loose test set) |
| -5.06 |
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 |
|---|---|
| -6.07 |
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 |
| -5.14 |
M2: Model with RDKit descriptors from training set 2 (Loose test set) |
| -5.14 |
M2: Model with RDKit descriptors from training set 2 (Test sets together) |
| -4.929 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Loose test set) |
| -4.929 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Test sets together) |
| -5.043 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Loose test set) |
| -5.043 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Test sets together) |