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Dual DNA binding mode of a turn-on red fluorescent probe thiazole coumarin.

Sudakshina GangulyDebasis GhoshNagarjun NarayanaswamyT GovindarajuGautam Basu
Published in: PloS one (2020)
Turn-on fluorescent probes show enhanced emission upon DNA binding, advocating their importance in imaging cellular DNA. We have probed the DNA binding mode of thiazole-coumarin (TC) conjugate, a recently reported hemicyanine-based turn-on red fluorescent probe, using a number of biophysical techniques and a series of short oligonucleotides. TC exhibited increased fluorescence anisotropy and decreased absorbance (~50%) at low [DNA]/[TC] ratio. Although the observed hypochromicity and the saturating value of [DNA base pair]:[TC] ratio is consistent with a previous study that suggested intercalation to be the DNA binding mode of TC, a distinctly different and previously unreported binding mode was observed at higher ratios of [DNA]:[TC]. With further addition of DNA, only oligonucleotides containing AnTn or (AT)n stretches showed further change-decreased hypochromicity, red shifted absorption peaks and concomitant fluorescence enhancement, saturating at about 1:1 [DNA]: [TC]. 1H-NMR chemical shift perturbation patterns and H1'-H6/H8 NOE cross-peaks of the 1:1 complex indicated minor groove binding by TC. ITC showed the 1:1 DNA binding event to be endothermic (ΔH° ~ 2 kcal/mol) and entropy driven (ΔS° ~ 32 cal/mol/K). Taken together, the experimental data suggest a dual DNA binding mode by TC. At low [DNA]/[TC] ratio, the dominant mode is intercalation. This switches to minor groove binding at higher [DNA]/[TC], only for sequences containing AnTn or (AT)n stretches. Turn-on fluorescence results only in the previously unreported minor groove bound state. Our results allow a better understanding of DNA-ligand interaction for the newly reported turn-on probe TC.
Keyphrases
  • dna binding
  • fluorescent probe
  • living cells
  • single molecule
  • circulating tumor
  • transcription factor
  • cell free
  • nucleic acid
  • high resolution
  • sensitive detection
  • machine learning
  • mass spectrometry
  • big data