QSAR, Pharmacophore Mapping and Molecular Docking of 2,4-Diaminoquinazoline as Antitubercular Scaffold: A Computational Hybrid Approach

Abstract

The 2,4-diaminoquinazoline is a well-known scaffold with a great potential to generate a library. In the following research work different computational strategies were applied on 2,4-diaminoquinazoline moiety to estimate its efficiency as an antitubercular scaffold among its other versatile biological activities reported in several published studies. Each data has defined specific substitution mode on the scaffold to be active on different protein site or for disease condition. The following experiment regards of 2D-QSAR, 3D-QSAR, active site and blind docking, structural orientation, pharmacophore mapping and further designing of the data set with possible real active moiety. 2D-QSAR has shown good reliability with r2 = 0.8190, q2_LOO = 0.7711 and external pred_r2 = 0.5321, along with 3D-QSAR has good predictability, q2 (r2cv) = 0.7601, pred_r2 = 0.5567. Further ligand based pharmacophore mapping was carried out for estimating atomic contribution to chemical feature for the compound. The generated hypothesis established that hydrogen accepter, donor and aromatic ring with electronegative atom are the important features. Finally, outcomes of all results were recapitulated to design new compounds. Some compounds also were designed depending on the computational finding and concludes the suitability of the scaffold to be antiTB active.