Molecular orientation and specificity in the identification of biomolecules via surface enhanced Raman spectroscopy

From Bulk to Single Molecules: Surface-Enhanced Raman Scattering of Cytochrome C Using Plasmonic DNA Origami Nanoantennas

Cytochrome C, an evolutionarily conserved protein, plays pivotal roles in cellular respiration and apoptosis. Understanding its molecular intricacies is essential for both academic inquiry and potential biomedical applications. This study introduces an advanced single-molecule surface-enhanced Raman scattering (SM-SERS) system based on DNA origami nanoantennas (DONAs), optimized to provide unparalleled insights into protein structure and interactions. Our system effectively detects shifts in the Amide III band, thereby elucidating protein dynamics and conformational changes. Additionally, the system permits concurrent observations of oxidation processes and Amide bands, offering an integrated view of protein structural and chemical modifications. Notably, our approach diverges from traditional SM-SERS techniques by de-emphasizing resonance conditions for SERS excitation, aiming to mitigate challenges like peak oversaturation. Our findings underscore the capability of our DONAs to illuminate single-molecule behaviors, even within aggregate systems, providing clarity on molecular interactions and behaviors.

Bio-synthesis, purification and structural analysis of Cyclosporine-A produced by Tolypocladium inflatum with valorization of agro-industrial wastes

Cyclosporine A (CyA) holds significant importance as a strategic immunosuppressive drug for organ transplant patients. In this study, we aimed to produce pure and cost-effective Cyclosporine A (CyA) by fermenting a culture medium containing dairy sludge, using Tolypocladium inflatum PTCC 5253. Following the fermentation stage, ethyl acetate extraction and fast protein liquid chromatography were employed for sample purification. The initial evaluation of the effectiveness of CyA obtained from these processes was performed through bioassay, wherein the antimicrobial clear zone diameter was found to be larger compared to the sample obtained from the fermentation culture. The concentration of CyA was determined using high-performance liquid chromatography, yielding values of 334 mg/L, 456 mg/L, and 578 mg/L for the fermented, extracted, and purified samples, respectively. Further analysis utilizing liquid chromatography tandem mass spectrometry (LC/MS/MS) confirmed a purity of 91.9% and proper agreement with the standard sample based on the ion intensity of Z/m 1205. To validate the structure of CyA, nuclear magnetic resonance spectroscopy, Fourier-transform infrared (FT-IR), and Raman spectroscopy were employed. X-ray diffraction and differential scanning calorimetry analyses demonstrated that the purified CyA exhibited a crystal structure similar to the standard sample, characterized by two broad peaks at 2θ = 9° and 20°, and comparable glass transition temperatures (57-68 °C for the purified sample; 53-64 °C for the standard sample). Dynamic light scattering analysis confirmed a uniform particle size distribution in both the purified and standard samples. The zeta potentials of the purified and standard samples were determined to be - 25.8 ± 0.16 and - 23.63 ± 0.12 mV, respectively. Our results demonstrate that dairy sludge can serve as a suitable culture medium for the production of (CyA).

AI-Driven Spectral Decomposition: Predicting the Most Probable Protein Compositions from Surface Enhanced Raman Spectroscopy Spectra of Amino Acids

Surface-enhanced Raman spectroscopy (SERS) is a powerful tool for elucidating the molecular makeup of materials. It possesses the unique characteristics of single-molecule sensitivity and extremely high specificity. However, the true potential of SERS, particularly in capturing the biochemical content of particles, remains underexplored. In this study, we harnessed transformer neural networks to interpret SERS spectra, aiming to discern the amino acid profiles within proteins. By training the network on the SERS profiles of 20 amino acids of human proteins, we explore the feasibility of predicting the predominant proteins within the µL-scale detection volume of SERS. Our results highlight a consistent alignment between the model's predictions and the protein's known amino acid compositions, deepening our understanding of the inherent information contained within SERS spectra. For instance, the model achieved low root mean square error (RMSE) scores and minimal deviation in the prediction of amino acid compositions for proteins such as Bovine Serum Albumin (BSA), ACE2 protein, and CD63 antigen. This novel methodology offers a robust avenue not only for protein analytics but also sets a precedent for the broader realm of spectral analyses across diverse material categories. It represents a solid step forward to establishing SERS-based proteomics.

Using Surface-Enhanced Raman Spectroscopy to Unravel the Wingtip-Dependent Orientation of N-Heterocyclic Carbenes on Gold Nanoparticles

N-Heterocyclic carbenes (NHCs) are an attractive alternative to thiol ligands when forming self-assembled monolayers on noble-metal surfaces; however, relative to the well-studied thiol monolayers, comparatively little is known about the binding, orientation, and packing of NHC monolayers. Herein, we combine surface-enhanced Raman spectroscopy (SERS) and first-principles theory to investigate how the alkyl "wingtip" groups, i.e., those attached to the nitrogens of N-heterocyclic carbenes, affect the NHC orientation on gold nanoparticles. Consistent with previous literature, smaller wingtip groups lead to stable flat configurations; surprisingly, bulkier wingtips also have stable flat configurations likely due to the presence of an adatom. Comparison of experimental SERS results with the theoretically calculated spectra for flat and vertical configurations shows that we are simultaneously detecting both NHC configurations. In addition to providing information on the adsorbate geometry, this study highlights the extreme SERS enhancement of vibrational modes perpendicular to the surface.