Surface-enhanced Raman scattering as a tool to probe cytochrome P450-catalysed substrate oxidation

Surface-enhanced Raman scattering-based detection of plasmin activity by specific peptide substrate

In this study, a new surface-enhanced Raman scattering (SERS)-based method has been developed for the detection of plasmin activity. Firstly, different peptide sequences, which are specific to plasmin, were examined. Then, SERS substrates were prepared by chosen peptide substrate. Enzyme activity was determined by pursuing the reduction of DTNB band at 1331 cm^-1 with Raman spectroscopy. The reduction in SERS intensity was related to the plasmin activity, and changes in SERS intensity vs. plasmin concentration graph was obtained. Limit of detection (LOD) and limit of quantification (LOQ) values were calculated as 2.14 U/mL and 6.42 U/mL, respectively. Intra- and inter-day repeatability results were determined as 1.45% and 1.47% relative standard deviation (RSD). Also, recovery of the method was determined for the plasmin spiked milk samples. The results demonstrated that the proposed method could be successfully used to detect the plasmin activity in milk samples.

Surface-enhanced resonance Raman scattering of hemoproteins and those in complicated biological systems

The SERRS spectra of heme are influenced by structural changes, orientation, and selective adsorption on the Ag surface.

Cytochromes P450: exploiting diversity and enabling application as biocatalysts

The remarkable chemical reactivity and substrate range displayed by cytochromes P450 (P450s) renders them attractive as potential catalysts for a host of challenging chemical reactions in industry. The opportunities afforded by these biocatalysts are increased by the availability of greater diversity provided by the genomic resource and the variant libraries of well-known P450s produced by rational and random engineering techniques. The exploitation of this enormous diversity will require novel tools in screening, to identify enzyme reactions of interest, and also in the enabling of these valuable activities through protein engineering and bioprocess optimisation.

Selective detection of HbA1c using surface enhanced resonance Raman spectroscopy

In the current work, we report on selective detection of HbA1c, a marker for glycemic control in diabetic patients, using surface enhanced resonance raman spectroscopy (SERRS). We found a characteristic band around 770-830 cm(-1) in the SERRS spectrum of HbA1c which was not present in the SERRS spectrum of HbA. To examine the contribution of glucosyl moiety to the characteristic SERRS band of HbA1c, we investigated SERRS spectra for nonenzymatically glycosylated HbA. We found that the SERRS spectral features are essentially identical for both HbA1c and nonenzymatically glycosylated HbA. Furthermore, addition of HbA into colloidal solution of silver nanoparticles (Ag NPs) resulted in the formation of large aggregates of Ag NPs and subsequent sedimentation. On the other hand, aggregation of Ag NPs was considerably low in the case of HbA1c. The differential effect of HbA and HbA1c on colloidal solution of Ag NPs, probably due to their difference in hydrophilicity, enabled us to separate them in a mixture. The separation was characterized by electrophoresis and SERRS analysis. Thus, colloidal solution of Ag NPs and SERRS would be a promising tool for the selective detection of HbA1c.