Iodine(III)-promoted regioselective and efficient synthesis of β-triazolyl BODIPYs for the selective recognition of nickel ions and bovine serum albumin.
Bintu KumarAnindita BhattaPrakriti SarafKrishnan RanganMadhushree SarkarSivaprasad MitraDalip KumarPublished in: Dalton transactions (Cambridge, England : 2003) (2022)
Various β-triazolyl tethered BODIPYs were efficiently prepared in a sequential one-pot protocol involving the initial reaction of BODIPY with iodobenzene diacetate (IBD) and sodium azide to in situ generate BODIPY azides followed by a copper-catalyzed azide-alkyne cycloaddition reaction. Under the optimized reaction conditions, various β-triazolyl BODIPYs 5a-i were successfully prepared in good yields and adequately characterized by using UV, NMR, mass spectral data and XRD analyses. The UV-Visible spectra of the prepared β-triazolyl BODIPYs 5a-i showed intense absorption bands (514-545 nm) with a 13-44 nm red shift when compared with those of the parent BODIPY. The selective recognition of compound 5d towards Ni 2+ ions (detection limit 0.26 nM) led to significant quenching in the fluorescence intensity over other selected bivalent metal ions. The complex formed between 5d and Ni 2+ in a stoichiometry of 2 : 1 was found to have a binding constant of 7.5 × 10 5 M -1 . The fluorescence of compound 5i gets enhanced gradually upon interaction with bovine serum albumin due to its selective and high binding affinity (1.25 × 10 5 M -1 ) with protein and a concomitant decrease in the total non-radiative decay rate.
Keyphrases
- aqueous solution
- living cells
- fluorescent probe
- quantum dots
- photodynamic therapy
- energy transfer
- single molecule
- magnetic resonance
- randomized controlled trial
- light emitting
- metal organic framework
- high resolution
- water soluble
- high intensity
- big data
- optical coherence tomography
- magnetic resonance imaging
- mass spectrometry
- gold nanoparticles
- dual energy
- protein protein
- small molecule
- transcription factor
- transition metal
- ulcerative colitis
- deep learning
- artificial intelligence
- real time pcr