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: | sc95 | |
|---|---|---|
| Name: | Tetracycline | |
| Description: | ||
| Labels: | ||
| CAS: | ||
| InChi Code: | InChI=1S/C22H24N2O8/c1-21(31)8-5-4-6-11(25)12(8)16(26)13-9(21)7-10-15(24(2)3)17(27)14(20(23)30)19(29)22(10,32)18(13)28/h4-6,9-10,15,25,27-28,31-32H,7H2,1-3H3,(H2,23,30)/t9-,10-,15-,21+,22-/m0/s1 |
Properties
logS0: Intrinsic aqueous solubility from single source [log(mol/L)]
| Value | Source or prediction |
|---|---|
| -3.22 |
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 |
| -3.854 |
M1: Model with Dragon descriptors from training set 1 (Tight test set) |
| -3.854 |
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 |
|---|---|
| -3.22 |
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 |
| -3.195 |
M2: Model with RDKit descriptors from training set 2 (Tight test set) |
| -3.195 |
M2: Model with RDKit descriptors from training set 2 (Test sets together) |
| -2.484 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Tight test set) |
| -2.484 |
M3: Model with PaDEL and XLOGS descriptors from training set 2 (Test sets together) |
| -3.178 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Tight test set) |
| -3.178 |
M_cons: Consensus model (average of predictions from M1, M2 and M3) (Test sets together) |