QSAR STUDIES & DESIGNING OF POTENT HETEROCYCLIC COMPOUNDS AS γ-SECRETASE INHIBITORS

Quantitative structure activity relationship (QSAR) studies ware performed on series of structurally similar heterocyclic sulfonamide with enzyme gamma secretase inhibitor activity. The compounds were divided into training and test set and generated different QSAR models using V-Life MDS 3.5 software multiple linear regression (MLR) method. Best QSAR models were selected on the basis of various statistical parameters like square correlation coefficient (r2), cross validated square correlation coefficient (q2), pred_r2, standard error of estimation (SE) and sequential Failure test (F). 2D QSAR study reveals that gamma secretase inhibitor activity is governed by physicochemical Alignment Independent (AI) descriptors and design new compounds, with more potent activity. The best models were found to be Model–I model-II and model-III. Model-I having 5 descriptors, r² ₌ 0.8582, q² ₌ 0.5701, Failure test = 22.9812 and predicted r² ₌ 0.7513. Model-II having 4 descriptors, r² ₌ 0.8170, q² ₌ 0.6780, Failure test = 18.9765 and predicted r² ₌ 0.6193. Model-III having 4 descriptors, r² ₌ 0.8248, q² ₌ 0.7006, Failure test = 20.0027 and predicted r² ₌ 0.7791. On the basis of 2D descriptors we designed many compounds in which compound J49 have the highest potency (EC₅₀ = 0.010 nM) in the design molecules as well as reported series.