Please use this identifier to cite or link to this item: http://nopr.niscpr.res.in/handle/123456789/66471
metadata.dc.identifier.doi: https://doi.org/10.56042/ijbb.v62i10.17233
Title: Computational analysis of N2-Aryl-1,2,3-triazoles as potential multi-target inhibitors
Authors: Sireesha, Sunkara Muni
Prasad, Beda Durga
Keywords: Adenomatous polyposis coli;Cytochrome P450;Docking;Drug designing;Histone deacetylase 8;N2-Aryl- 1,2,3-triazoles;Virtual screening
Issue Date: Oct-2025
Publisher: NIScPR-CSIR, India
Abstract: Triazole derivatives, synthesized using green chemistry, are promising therapeutics due to their strong pharmacokinetics, pharmacodynamics, and ADMET properties. Their proven activities against various conditions have increased industrial demand. Notably, N2-Aryl-1,2,3-triazoles contain heterocyclic nitrogen structures, making them a valuable platform for new drug development. We evaluated 173 N2-Aryl-1,2,3-triazoles obtained from the PubChem database, assessed their ADMET properties,and optimized their structures using the Universal Force Field (UFF). In silico assessments of pharmacological properties were performed. Four key target proteins were identified: HDAC8 (antidiabetic), APC (anticancer), and CYP51 (antitubercular/antibacterial and antifungal), with docking studies conducted on each target.Top hits included CID-135064814 (-8.8 kcal/mol, antidiabetic/anticancer), CID-59814079 (-9.6 kcal/mol, anticancer), CID-139251519 (-10.6 kcal/mol, antibacterial/antitubercular), and CID-102473643 (-13.8 kcal/mol, antifungal), demonstrating the highest binding affinities. Other notable best docked molecules were CID-135064814, CID-102473643, and CID-135066341. CID-135065731, CID-59814079, CID-21331374, CID-88817443, CID-59814075, CID-54036863, and CID-70598857.We conducted human proteome target analysis for the best-docked molecules. A 100 ns molecular dynamics simulation for the overall best-docked compound was done. We successfully screened the molecules that showed the best results and that had multitarget capability.
Page(s): 1129-1141
ISSN: 0975-0959 (Online);0301-1208 (Print)
Appears in Collections:IJBB Vol.62(10) [October 2025]

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