Mechanistic insights into mode of action of novel natural cathepsin L inhibitors

BACKGROUND: Development of a cancerous cell takes place when it ceases to respond to growth-inhibiting signals and multiplies uncontrollably and can detach and move to other parts of the body; the process called as metastasis. A particular set of cysteine proteases are very active during cancer metastasis, Cathepsins being one of them. They are involved in tumor growth and malignancy and have also been reported to be overexpressed in tumor cell lines. In the present study, a combinatorial approach comprising three-dimensional quantitative structure-activity relationship (3D QSAR), ligand-based pharmacophore modelling and search followed by cathepsin L structure-based high throughput screening was carried out using an initial set of 28 congeneric thiosemicarbazone derivatives as cathepsin L inhibitors. A 3D QSAR was derived using the alignment of a common thiosemicarbazone substructure. Essential structural features responsible for biological activity were taken into account for development of a pharmacophore model based on 29 congeneric thiosemicarbazone derivatives. This model was used to carry out an exhaustive search on a large dataset of natural compounds. A further cathepsin L structure-based screen identified two top scoring compounds as potent anti-cancer leads. RESULTS: The generated 3D QSAR model showed statistically significant results with an r(2 )value of 0.8267, cross-validated correlation coefficient q(2 )of 0.7232, and a pred_r(2 )(r(2 )value for test set) of 0.7460. Apart from these, a high F test value of 30.2078 suggested low probability of the model's failure. The pharmacophoric hypothesis chosen for searching the natural compound libraries was identified as DDHRR, where two Ds denote 2 hydrogen donors, H represents a hydrophobic group and two Rs represent aromatic rings, all of which are essential for the biological activity. We report two potential drug leads ZINC08764437 (NFP) and ZINC03846634 (APQ) obtained after a combined approach of pharmacophore-based search and structure-based virtual screen. These two compounds displayed extra precision docking scores of -7.972908 and -7.575686 respectively suggesting considerable binding affinity for cathepsin L. High activity values of 5.72 and 5.75 predicted using the 3D QSAR model further substantiated the inhibitory potential of these identified leads. CONCLUSION: The present study attempts to correlate the structural features of thiosemicarbazone group with their biological activity by development of a robust 3D QSAR model. Being statistically valid, this model provides near accurate values of the activities predicted for the congeneric set on which it is based. These predicted activities are good for the test set compounds making it indeed a statistically sound 3D QSAR model. The identified pharmacophore model DDHRR.8 comprised of all the essential features required to interact with the catalytic triad of cathepsin L. A search for natural compounds based on this pharmacophore followed by docking studies further screened out two top scoring candidates: NFP and AFQ. The high binding affinity and presence of essential structural features in these two compounds make them ideal for consideration as natural anti-tumoral agents. Activity prediction using 3D QSAR model further validated their potential as worthy drug candidates against cathepsin L for treatment of cancer.