In silico study of 2,4,5-trisubstituted thiazoles as inhibitors of tuberculosis using 3D-QSAR, molecular docking, and ADMET analysis

Abstract

In order to discover new efficient drug used as inhibitor of tuberculosis, three-dimensional quantitative structure-activity relationship (3D-QSAR) was executed on set of eighteen 2,4,5-trisubstituted thiazoles compounds. CoMFA and CoMSIA models were molded using 14 molecules as training set. They give a significant coefficient of R2 (0.995 and 0.982 respectively) and important values of Q2 (0.533 and 0.601, respectively). The robust of these models was checked by an external validation using a test set of 4 molecules, affords significant R2test values of 0.654 and 0.648 for CoMFA and CoMSIA models, respectively. CoMFA and CoMSIA contour maps provided much valuable information to identify the main regions impacting (decreasing or increasing) the antituberculosis activity. These outcomes guided us to design new entities with important activities. Molecular docking was put into effect to guess the types and modes of interactions between 2,4,5-trisubstituted thiazoles molecules and receptor (PDB: 4ZDJ). In silico ADMET analysis was executed to measure the pharmacokinetic properties of newly designed molecules.

Keywords

• Molecular docking
• 3D-QSAR
• anti-tuberculosis
• thiazoles
• ADMET

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