Abstract

In this QSAR study, a large dataset of 1,3,4-oxadiazole derivatives was encoded with a variety of chemical descriptors to create a statistically sound, stable, and predictive quantitative structure–activity relationship (QSAR) model aimed at the transpeptidase enzyme. The creation of this statistically validated model offers a viable foundation for investigating descriptor-based manipulation of transpeptidase inhibitory mechanisms. Multiple statistical factors were used to execute strict internal and external validations, which showed that the     model was very reliable and not random. The validated QSAR model was subsequently utilized to forecast the biological activity of newly synthesized analogues, thereby pinpointing prospective lead compounds. To enhance the QSAR results, molecular docking simulations were performed on the highest-predicted active chemicals to clarify their binding orientations, interaction patterns, and structural compatibility within the enzyme's active site. Of the proposed series, chemicals M26 and M27 (after correcting for duplication) had the best docking scores of ?8.90 and ?9.44 kcal/mol, respectively. This means that they have a significant binding affinity and a strong ability to block the transpeptidase enzyme. These results suggest that the discovered compounds could function as viable scaffolds for the creation of novel antibacterial medicines and may signify a substantial progress in treatment techniques aimed at bacterial cell wall production. We did pharmacokinetic and drug-likeness tests (ADME profiling) to find out how well the developed compounds work and how well they can be absorbed by the body through the mouth. All of the compounds followed Lipinski's Rule of Five, which showed that they had good drug-like properties and could move on to preclinical testing. The results of QSAR modeling, molecular docking, and ADME analysis together show that the computational method is reliable and point to the 1,3,4-oxadiazole framework as a good structural motif for making new transpeptidase enzyme inhibitors.