DefinePK

Abstract

A novel hybrid methodology combining Quantitative Structure–Activity Relationship (QSAR) and Structure-Based Drug Design (SBDD) methodologies has been established for the identification of new antitubercular medicines.  This comprehensive technique resulted in the development of a predictive QSAR model characterized by five essential parameters: the amino acid residues Glu65, Ala66, Phe69, the water molecule HOH2018, and an indicator variable.  Validation of the model using a structurally heterogeneous external dataset resulted in a correlation coefficient of 0.79, indicating robust prediction performance.  Structural and binding research highlighted the essential significance of stereochemistry in ligand-target interactions, with Glu65 identified as the most significant residue influencing both binding affinity and biological activity.  These findings underscore the efficacy of the QSAR-SBDD integration and offer a logical framework for the development of effective and selective antitubercular agents.