2D QSAR ANALYSIS OF DIPEPTIDE NITRILE BASED CATHEPSIN S INHIBITORS

Cathepsin S enzyme has been considered as an evolving target for the development of novel therapeutic agents for the treatment of numerous autoimmune disorders and other inflammatory diseases. Using TSAR 3.3 2D QSAR has been performed on a series of dipeptide nitrile nucleus. Attempts have been made to derive and comprehend a correlation between biological activity and the generated descriptors. The study was carried out using 37 compounds by division into training and test set by a random selection method. A final QSAR model was generated from a set of 28 compounds with the Leave-out one row (LOO) method of cross-validation to estimate the model’s predictive ability. The most significant model with n = 28, r = 0.969, r² = 0.939, r²cv = 0.801, s value = 0.35, f value = 89.07 was developed using MLR analysis. For PLS, the fraction of variance explained = 0.928 was observed. A comparable PLS model with r² = 0.928 and Neural model with r² = 0.962 indicated good internal predictability of the model. External test set validation provided r² values of 0.721 and 0.821 for MLR and PLS analysis, respectively. QSAR model indicated the importance of Steric [Verloop B1 (Subs. 4)], Geometrical [Inertia moment 1 length (Subs. 4), topological [kier Chi V0 (atoms) index (Subs. 2)], and [Kier Chi 4 (path) index (Subs.4)] descriptors for the activity of Cathepsin S inhibitors. This study will be effective in the design of novel and more potent Cathepsin S inhibitors.