1,2,3-Triazole-Based Hybrids as Emerging Therapeutic Agents: Advances in Drug Design, Computational Studies, and Biological Applications
Mausin Khan, Mohammad Ajmal, Nithya Shanthi, Arun Kumar MahatoIntroduction::
The 1,2,3-triazole scaffold is a privileged heterocyclic motif in medicinal chemistry owing to its chemical stability, click-chemistry accessibility, and broad biological activity. This review examines advances in 1,2,3-triazole-based hybrids, emphasizing antitubercular activity against drug-sensitive and drug-resistant Mycobacterium tuberculosis, as well as applications in cancer, diabetes, and drug-resistant bacterial infections. Attention is given to structure-activity relationships and computational drug-design approaches.
Methods::
Recent literature on the design, synthesis, biological evaluation, and mechanisms of 1,2,3- triazole hybrids was assessed. Molecular hybridization, biological targets, SAR trends, molecular docking, molecular dynamics simulations, and ADMET analysis were evaluated alongside experimental findings.
Results::
Triazole hybrids demonstrated activity across all four therapeutic areas. Antitubercular derivatives targeted InhA, DprE1, CYP51, and ATP synthase, whereas anticancer compounds modulated EGFR, VEGFR2, Bcl-2, carbonic anhydrases, and tubulin. Antidiabetic derivatives mainly inhibited α-glucosidase and α-amylase, while antibacterial hybrids targeted DNA gyrase and bacterial ribosomal machinery. Compounds 7, 24, 33, and 37 showed strong activity. Computational studies supported experimental findings by identifying ligand–target interactions and guiding lead optimization.
Discussion::
SAR analysis indicates that pharmacophore hybridization, electronic and lipophilic substituents, aromatic or fused heterocycles, and hydrogen-bond-forming groups strongly influence biological potency. However, differences in assay conditions and limited correlation between docking scores and experimental activity highlight the need for standardized evaluation.
Conclusion::
1,2,3-Triazole hybrids represent a versatile platform for drug discovery. Future research should prioritize SAR optimization, target validation, in vivo and pharmacokinetic studies, toxicity assessment, and the integration of artificial intelligence with structure-based design to accelerate the development of therapeutics.