DEVELOPMENT OF 2D AND 3D QSAR MODELS OF THIAZOLE DERIVATIVES FOR ANTIMICROBIAL ACTIVITY

Abstract

A series of 20 molecules of Aryl Thiazole derivatives reported in literature Khan M S et al (2009) were used for development of 2D and 3D QSAR models. The data set of 20 molecules were divided into training and test set in the ratio of 70:30, The biological activity was converted to logarithmic scale (pIC50) in mathematical operation mode of the software. The statistically significant 2D-QSAR models for G+ inhibition activity are r2 =0.9521 and q2 = 0.8619 and 3D QSAR results for internal (q2 = 0.8283,) and external (predictive r2 = 0.4868,) validation criteria. Thus, 3D QSAR models showed that electrostatic effects dominantly determine the binding affinities. 2D QSAR studies revealed that T_C_C_4 descriptors were major contributing descriptor in case of G+ inhibition activity. 3D QSAR Methods were performed using kNN-MFA method. The results derived may be useful in further designing novel more potent agents.