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For the therapeutic optimization of various cancers such as breast cancer, prostate cancer, thyroid carcinoma, lung
adenocarcinoma targeting the predominant papain-like cysteine protease Cathepsin K is found to be dominant strategy.
In current study, designing of Cathepsin K inhibitors through pharmacophore and virtual screening methodology displayed
promising number of scaffolds. A five point pharmacophore with two hydrogen bond acceptors (A), one hydrogen bond donor
(D), one hydrophobic feature (H) and one ring feature (R) as pharmacophoric features were developed to understand active
scaffolds with specific functional groups. Validation of the pharmacophore hypothesis was carried out with enrichment statistical
calculation. The best pharmacophore model has shown best fitness against 100 active molecules with PIC
50
values greater than
8 among 254 active molecules. Further, it yielded a statistically significant 3D-QSAR model with a correlation coefficient of R
2
= 0.901 for training set compounds and with test set correlation coefficient of Q
2
= 0.823, the generated model showed excellent
contour map predictions. The model was then employed as 3D search query to screen against private and public compound
libraries (BITS, Asinex database) followed by virtual screening which resulted in 322 molecule hits. Inhibitors having above 50
percent oral bioavailability predicted through Qikprop were chosen for biological activity assays. Molecules which have shown
enzyme inhibition at nano-molar concentration were considered as potential selective non-covalent inhibitors for Cathepsin K.
Biography
Sridevi Kondepudi is pursuing her B.Pharmacy (Hons.) from BITS-Pilani, Hyderabad campus. Currently she is working on a lab oriented project in Computer-aided drug discovery lab at BITS Hyderabad. She has been placed as Trainee in Mylan laboratories Ltd.
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