Zukic, S.; Ivanova, L.; Zusinaite, E.; Merits, A.; Maran, U. Discovery of a Novel Phthalazine-Based VEGFR-2 Inhibitor by Machine Learning Analysis of Diverse Chemical Space with Favorable Pharmacophores and Its Evaluation in Glioblastoma Cell Lines. Results in Chemistry, Under revision
Compound
| ID: | 95 | |
|---|---|---|
| Name: | Compound 95 | |
| Description: | Original numeration in publication: 6a | |
| Labels: | Training_set, Thiourea | |
| CAS: | ||
| InChi Code: | InChI=1S/C21H20N4O5S3/c1-2-22-20(31)24-33(29,30)16-10-8-15(9-11-16)23-18(26)13-25-19(27)17(32-21(25)28)12-14-6-4-3-5-7-14/h3-12H,2,13H2,1H3,(H,23,26)(H2,22,24,31)/b17-12- |
Properties
pIC50: Negative logarithm of half-maximal inhibitory concentration [-log(uM)]
| Value | Source or prediction |
|---|---|
| 6.77 |
Abdelgawad, M. A.; El-Adl, K.; El-Hddad, S. S. A.; Elhady, M. M.; Saleh, N. M. a. K., M. M.; Khedr, F.; Alswah, M. a. N., A. A.; Ghoneim, M. M.; Abd El-Sattar, N. E. A. Design, molecular docking, synthesis, anticancer and anti-hyperglycemic assessments of thiazolidine-2,4-diones bearing sulfonylthiourea moieties as potent VEGFR-2 inhibitors and PPARy agonists. Pharmaceuticals (Basel) 2022, 15, 226. https://doi.org/10.3390/ph15020226 |
| 7.13986 |
Eq1: VEGFR-2 inhibition (Data used to train model) |