Prospects of ultraviolet resonance Raman spectroscopy in supramolecular chemistry on proteins

Ultraviolet resonance Raman scattering (UVRR) has been frequently used for studying peptide and protein structure and dynamics, while applications in supramolecular chemistry are quite rare. Since UVRR offers the additional advantages of chromophore selectivity and high sensitivity compared with conventional non-resonant Raman scattering, it is ideally suited for label-free probing of relatively small artificial/supramolecular ligands exhibiting electronic resonances in the UV. In this perspective article, we first summarize results of UVRR spectroscopy in supramolecular chemistry in the context of peptide/protein recognition. We focus on selected artificial ligands which were rationally designed as selective carboxylate binders (guanidiniocarbonyl pyrrole, GCP, and guanidiniocarbonyl indole, GCI) and selective lysine binder (molecular tweezer, CLR01), respectively, via a combination of non-covalent interactions involving electrostatics, hydrogen bonding, and hydrophobic effects/van der Waals forces. Current limitations of applying UVRR as a universally applicable method for label-free and site-specific probing of molecular recognition between supramolecular ligands and proteins are highlighted. We then propose solutions to overcome these limitations for transforming UVRR spectroscopy into a generic tool in supramolecular chemistry on proteins, with an emphasis on mono- and multivalent GCP- and GCI-based ligands. Finally, we outline specific cases of supramolecular ligands such as molecular tweezers where alternative approaches such as laser-based mid-IR spectroscopy are required since UVRR can intrinsically not provide the required molecular information.

Ultraviolet resonance Raman spectroscopy with a continuously tunable picosecond laser: Application to the supramolecular ligand guanidiniocarbonyl pyrrole (GCP)

We present a UVRR spectroscopy setup which is equipped with a picosecond pulsed laser excitation source continuously tunable in the 210-2600 nm wavelength range. This laser source is based on a three-stage optical parametric amplifier (OPA) pumped by a bandwidth-compressed second harmonic output of an amplified Yb:KGW laser. It provides <15 cm^-1 linewidth pulses below 270 nm, which is sufficient for resolving Raman lines of samples in condensed phase studies. For demonstrating the capability of this tunable setup for UVRR spectroscopy we present its application to the artificial ligand guanidiniocarbonyl pyrrole (GCP), a carboxylate binder used in peptide and protein recognition. A UVRR excitation study in the range 244-310 nm was performed for identifying the optimum laser excitation wavelength for UVRR spectroscopy of this ligand (λ_max = 298 nm) at submillimolar concentrations (400 µM) in aqueous solution. The optimum UVRR spectrum is observed for laser excitation with λ_exc = 266 nm. Only in the relatively narrow range of λ_exc = 266-275 nm UVRR spectra with a sufficiently high signal-to-noise ratio and without severe interference from autofluorescence (AF) were detectable. At longer excitation wavelengths the UVRR signal is masked by AF. At shorter excitation wavelengths the UVRR spectrum is sufficiently separated from the AF, but the resonance enhancement is not sufficient. The presented tunable UVRR setup provides the flexibility to also identify optimum conditions for other supramolecular ligands for peptide/protein recognition.

UV resonance Raman spectroscopy of the supramolecular ligand guanidiniocarbonyl indole (GCI) with 244 nm laser excitation

Ultraviolet resonance Raman (UVRR) spectroscopy is a powerful vibrational spectroscopic technique for the label-free monitoring of molecular recognition of peptides or proteins with supramolecular ligands such as guanidiniocarbonyl pyrroles (GCPs). The use of UV laser excitation enables Raman binding studies of this class of supramolecular ligands at submillimolar concentrations in aqueous solution and provides a selective signal enhancement of the carboxylate binding site (CBS). A current limitation for the extension of this promising UVRR approach from peptides to proteins as binding partners for GCPs is the UV-excited autofluorescence from aromatic amino acids observed for laser excitation wavelengths >260 nm. These excitation wavelengths are in the electronic resonance with the GCP for achieving both a signal enhancement and the selectivity for monitoring the CBS, but the resulting UVRR spectrum overlaps with the UV-excited autofluorescence from the aromatic binding partners. This necessitates the use of a laser excitation <260 nm for spectrally separating the UVRR spectrum of the supramolecular ligand from the UV-excited autofluorescence of the peptide or protein. Here, we demonstrate the use of UVRR spectroscopy with 244 nm laser excitation for the characterization of GCP as well as guanidiniocarbonyl indole (GCI), a next generation supramolecular ligand for the recognition of carboxylates. For demonstrating the feasibility of the UVRR binding studies without an interference from the disturbing UV-excited autofluorescence, benzoic acid (BA) was chosen as an aromatic binding partner for GCI. We also present the UVRR results from the binding of GCI to the ubiquitous RGD sequence (arginylglycylaspartic acid) as a biologically relevant peptide. In the case of RGD, the more pronounced differences between the UVRR spectra of the free and complexed GCI (1:1 mixture) clearly indicate a stronger binding of GCI to RGD compared with BA. A tentative assignment of the experimentally observed changes upon molecular recognition is based on the results from density functional theory (DFT) calculations.

A rapid rice blast detection and identification method based on crop disease spores' diffraction fingerprint texture

BACKGROUND

Rice blast fungus is a worldwide disease, and it is one of the most serious rice diseases in the north and south rice fields in China. The initial symptoms of rice blast are not obvious, and the speed of transmission is fast. Manual identification is time-consuming and laborious. At present, it is a great challenge to realize rapid and accurate early identification of rice blast.

RESULTS

In this paper, an identification method based on crop disease spores' diffraction fingerprint texture for rice blast was studied; this method utilizes the light field and texture features of diffraction images. To verify the reliability of the model that we proposed, we selected two methods of manual identification and machine recognition to compare and detect rice blast spores. The experimental results show that the identification of light diffraction characteristics is not only higher than the traditional manual recognition by microscope (increased by more than 0.3%), but also faster after neural network training (increased by more than 90%). The diffraction recognition method used in this study, based on crop disease spores' diffraction fingerprint texture, can be completed in a few seconds, and its test accuracy is 97.18%.

CONCLUSION

The proposed method, a rapid rice blast detection and identification method based on crop disease spores' diffraction fingerprint texture, has certain advantages compared with the existing manual identification by microscope. This method can be applied to the recognition of rice blast in agricultural research. © 2020 Society of Chemical Industry.