Abstract:
Kinases are one of the major players in cancer development and progression. Serine threonine kinases such as human checkpoint kinase-1(Chk1), Mek1 and cyclin-dependent kinases (CDKs) have been identified as promising targets for cancer treatment. Chk1 is an important kinase with vital role in cell cycle arrest and many potent inhibitors targeted to Chk1 have been reported and few are currently in clinical trials. Considering the emerging importance of Chk1 inhibitors in cancer treatment there is a need to widen the chemical space of Chk1 inhibitors. In this study, we are reporting an integrated in silico approach to identify novel competitive Chk1 inhibitors. A 4-features pharmacophore model was derived from a co-crystallized structure of known potent Chk1 inhibitor and subjected to screen Maybridge compound library. Hits obtained from the screening were docked into the Chk1 active site and filtered on the basis of docking score and the number of pharmacophoric features showing conserved interaction within the active site of Chk1. Further, 5 compounds from the top ranking hits were subjected to in vitro evaluation as Chk1 inhibitor. After the kinase assay, four compounds were found to be active against human Chk1 (Ic50 range from 4.2 µM -12.5 µM). Subsequent study using the cdc25-22 mutant yeast cells revealed that one of compound (SPB07479; Ic50 = 4.24µM) promoted the formation of multinucleated cells, therefore overriding the cell cycle checkpoint. Validation studies using normal and human cancer cell lines, indicated that SPB07479 significantly inhibited proliferation of cervical cancer cells as a single agent and chemosensitized glioma and pancreatic cancer cell lines to standard chemotherapy while sparing normal cells. Additionally SPB07479 did not show significant cytotoxity in normal cells. In conclusion we report that SPB07479 appear promising for further development of Chk1 inhibitors. This study also highlights the role of conserved water molecules in the active site of Chk1 for the successful identification of novel inhibitors.
