Fluorescence Based Platform to Discriminate Protein Using Carbon Quantum
Dots
CHEMISTRYSELECT, 4 (19):
5619-5627 (2019)DOI: 10.1002/slct.201901014
Abstract
There is an urgent demand to develop a cheap, fast and robust
methodology to sense proteins, since these biomolecules are often used
as biomarker responsible for diagnosing of some diseases, such as
cancer. In this regard, we report a theoretical and experimental study,
as well as a cheap and effective `chemical-nose' strategy based on
carbon quantum dots (CQDs) and metallic cations (M) to discriminate
proteins at concentration as low as 50 nM. Thus, the CQDs were firstly
synthesized through citric acid thermolysis and their characteristics
were fully investigated by UV-Vis absorption, fluorescence, infrared
(FTIR), XPS and Raman spectroscopies and atomic force microscopy (AFM).
These results pointed out for quasi-spherical CQDs with diameters in the
range of 1.2-7 nm, presence of stacked graphitic layers and oxygenated
functional groups, as well as disordered carbon. Based on the structural
and morphological features, computational simulations were carried out
to obtain a better understanding of the atomic structure. Our results
evidenced a carbon-based nanoparticle formed by stacked graphene
nanoflakes containing defects due to the presence of functional groups
within the graphene layers. Afterwards, a `tongue'-based approach was developed by using three distinct CQDs - M (M=Fe3+, Cu2+ or Ni2+)
ensembles, which allowed us to acquire different and reproducible
fluorescence patterns for four proteins (bovine serum albumin,
hemoglobin, myoglobin and cytochrome C) at 50 nM. Subsequently, the
pattern recognition was performed using linear discriminant analysis and
36 samples were correctly identified affording 100% of accuracy.