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

• Published in: Chemistry & biodiversity Vol. 20; no. 3; pp. e202201146 - n/a
• Main Authors: Acar Çevik, Ulviye, Celik, Ismail, İnce, Ufuk, Maryam, Zahra, Ahmad, Iqrar, Patel, Harun, Özkay, Yusuf, Asım Kaplancıklı, Zafer
• Format: Journal Article
• Language: English
• Published: Switzerland Wiley Subscription Services, Inc 01.03.2023
• Subjects: Anti-Infective Agents - chemistry; Antibiotics; Antifungal activity; Antifungal Agents - chemistry; Antiinfectives and antibacterials; antimicrobial; Antimicrobial activity; Antimicrobial agents; Chemical synthesis; Computer applications; Density functional theory; DFT; Fluconazole; Fungicides; Gentamicin; MD simulation; Microbial Sensitivity Tests; Minimum inhibitory concentration; molecular docking; Molecular Docking Simulation; Molecular modelling; Molecular Structure; NMR; Nuclear magnetic resonance; Structure-Activity Relationship; thiadiazole; Thiadiazoles; Thiadiazoles - chemistry; Vancomycin; MD simulation; thiadiazole; antimicrobial; DFT; molecular docking
• ISSN: 1612-1872; 1612-1880
• DOI: 10.1002/cbdv.202201146

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 1H‐NMR, 13C‐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 μg/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.