Development of a natural product-based selective fluorescent sensor for Cu2+ and DNA/protein: insights from docking, DFT, cellular imaging and anticancer activity

Abstract

The natural product seselin (SS), was synthesized and characterized spectroscopically for the selective detection of Cu2+ and biomolecules such as ct-DNA and BSA. The probe exhibits strong bluish emission in a MeOH–H2O (7 : 3, v/v) HEPES buffer solution (pH 7.4) at 453 nm. Upon exposure to Cu2+, the SS solution shows a selective fluorescence ‘turn-off’ with a binding constant of 2.13 × 105 M−1 and a detection limit of 3.48 × 10−8 M. The HOMO–LUMO energy gap of the probe SS decreases from ΔE = 7.97 eV to ΔE = 7.77 eV upon binding with Cu2+, indicating enhanced stability due to ligand–metal complex formation. Significantly, the ligand SS exhibits fluorescence enhancement in the presence of ct-DNA and BSA, resulting in a visible fluorescence change from colorless to blue, with binding constants of 4.8 × 104 M−1 and 4.7 × 104 M−1, respectively. The binding interactions of SS with biomacromolecules have been explored through molecular docking studies, revealing that the probe can serve as a promising anti-cancer and anti-viral agent. Furthermore, the probe SS demonstrates potent anticancer activity in treatments involving MCF-7 and HLC cells. Additionally, the probe SS is capable of detecting intracellular Cu2+ in live MCF-7 cell lines.

Graphical abstract: Development of a natural product-based selective fluorescent sensor for Cu2+ and DNA/protein: insights from docking, DFT, cellular imaging and anticancer activity

Supplementary files

Article information

Article type
Paper
Submitted
07 May 2025
Accepted
03 Jul 2025
First published
03 Jul 2025
This article is Open Access
Creative Commons BY license

Anal. Methods, 2025, Advance Article

Development of a natural product-based selective fluorescent sensor for Cu2+ and DNA/protein: insights from docking, DFT, cellular imaging and anticancer activity

S. Pakrashy, M. Das, S. Manna, S. M. Choudhury, H. Shinziya, B. Das, M. Dolai and A. K. Das, Anal. Methods, 2025, Advance Article , DOI: 10.1039/D5AY00778J

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