5-Aminoisophthalate-based kojic acid-appended bis-1,2,3-triazole: a fluorescent chemosensor for Cu 2+ sensing and in silico study.
Sachin KumarBajrang LalGurleen Singhnull MuskanRam Kumar TittalJandeep SinghVikas Dasharath GhuleRenu SharmaPublished in: RSC advances (2024)
A new, easy-to-prepare, and highly selective fluorescent chemosensor, i.e. , 5-aminoisophthalate-based kojic acid-appended bis-1,2,3-triazole, was synthesized from an alkyne of 5-aminoisophthalic acid and azido-kojic acid using Cu(i)-catalyzed click chemistry and then successfully characterized. The alkyne structure of 5-aminoisophthalic acid, 1, was supported by the single-crystal X-ray crystallographic data. The fluorescent probe 3 was found to be highly selective for Cu 2+ ions supported by the Job's plot with a stoichiometric ligand : metal ratio of 2 : 1, exhibiting almost a two-fold enhancement in the emission intensity upon the addition of Cu 2+ ions (0-25 μM) with a detection limit of 8.82 μM. A comparison with LODs from previously developed chemosensors for Cu 2+ ions was also conducted. Reversibility analysis indicated that probe 3 could be used as both a reusable sensor and as a scavenger of copper ions. DFT calculations with the basis sets B3LYP/6-311G(d,p) and LanL2DZ were employed for geometrical optimizations of structures of the alkyne 1, azide 2, probe 3, and complex 3.Cu 2+ . Hirshfeld surface analysis revealed significant intermolecular interactions in compound 1. Additionally, molecular docking for the antimicrobial activity showed the better antibacterial efficacy of probe 3.
Keyphrases
- aqueous solution
- quantum dots
- living cells
- molecular docking
- fluorescent probe
- molecular dynamics simulations
- metal organic framework
- high resolution
- density functional theory
- single molecule
- mass spectrometry
- label free
- machine learning
- big data
- room temperature
- artificial intelligence
- deep learning
- wound healing
- real time pcr