Development of natural and artificial receptors with high affinity and exquisite specificity for various purposes remains an important goal and challenge.
Recognition of oligosaccharides is associated with very limited specificity due to their strong solvation in water and the high degree of subtle structural variations between them. Here, oligosaccharide recognition sites are created on material surfaces with unmatched, binary on–off binding behavior, sharply discriminating a target oligosaccharide over closely related carbohydrate structures. The basis for the superselective binding behavior relies on the highly efficient generation of a pure, high order complex of the oligosaccharide target with synthetic carbohydrate receptor sites, in which the spatial arrangement of the multiple receptors in the complex is preserved upon material surface incorporation. The synthetic binding scaffolds can easily be tailored to recognize different oligosaccharides and glycoconjugates, opening up a realm of possibilities for their use in a wide field of applications, ranging from life sciences to diagnostics.
Diagnostic advancements require
continuous developments of reliable analytical sensors, which can
simultaneously fulfill many criteria, including high sensitivity and
specificity for a broad range of target analytes. Incorporating the
highly sensitive attributes of surface-enhanced Raman spectroscopy
(SERS) combined with highly specific analyte recognition capabilities
via molecular surface functionalization could address major challenges
in molecular diagnostics and analytical spectroscopy fields. Herein,
we have established a controllable molecular surface functionalization
process for a series of textured gold surfaces. To create the molecularly
surface-functionalized SERS platforms, self-assembled benzyl-terminated
and benzoboroxole-terminated monolayers were used to compare which
thicknesses and root-mean-square (RMS) roughness of planar gold produced
the most sensitive and specific surfaces. Optimal functionalization
was identified at 80 ± 8 nm thickness and 7.2 ± 1.0 nm RMS.
These exhibited a considerably higher SERS signal (70-fold) and improved
sensitivity for polysaccharides when analyzed using principal component
analysis (PCA) and self-organizing maps (SOM). These findings lay
the procedure for establishing the optimal substrate specifications
as an essential prerequisite for future studies aiming at developing
the feasibility of molecular imprinting for SERS diagnostic applications
and the subsequent delivery of advanced, highly selective, and sensitive
sensing devices and analytical platforms.
Correction for ‘The challenges of glycan recognition with natural and artificial receptors’ by Stefano Tommasone et al., Chem. Soc. Rev., 2019, 48, 5488–5505.
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