Synthesis, Biological Evaluation, and Molecular Modeling Studies of New 1,3,4-Thiadiazole Derivatives as Potent Antimicrobial Agents

In this work, the synthesis, characterization, and biological activities of a new series of 1,3,4-thiadiazole derivatives were investigated. The structures of final compounds were identified using H-1-NMR, C-13-NMR, elemental analysis, and HRMS. All the new synthesized compounds were then screened for their antimicrobial activity against four types of pathogenic bacteria and one fungal strain, by application of the MIC assays, using Ampicilin, Gentamycin, Vancomycin, and Fluconazole as standards. Among the compounds, the MIC values of 4 and 8 mu g/mL of the compounds 3f and 3g, respectively, are remarkable and indicate that these compounds are good candidates for antifungal activity. The docking experiments were used to identify the binding forms of produced ligands with sterol 14-demethylase to acquire insight into relevant proteins. The MD performed about 100 ns simulations to validate selected compounds' theoretical studies. Finally, using density functional theory (DFT) to predict reactivity, the chemical characteristics and quantum factors of synthesized compounds were computed. These results were then correlated with the experimental data. Furthermore, computational estimation was performed to predict the ADME properties of the most active compound 3f.

Automated summary

In this study, a new series of 1,3,4-thiadiazole derivatives were synthesized, characterized, and evaluated for their biological activities. The structures of the final compounds were determined using various analytical techniques. The synthesized compounds were tested for their antimicrobial activity against bacteria and fungi, and compounds 3f and 3g showed remarkable antifungal activity. Docking experiments and molecular dynamics simulations were used to understand the binding forms and validate the theoretical studies of selected compounds. Density functional theory (DFT) calculations were performed to predict the reactivity and chemical characteristics of the compounds, and the results were correlated with experimental data. Additionally, computational estimation was carried out to predict the ADME properties of the most active compound 3f.