Label-Free Analysis of Binding and Inhibition of SARS-Cov-19 Spike Proteins to ACE2 Receptor with ACE2-Derived Peptides by Surface Plasmon Resonance

Trends in surface plasmon resonance biosensing: materials, methods, and machine learning

Surface plasmon resonance (SPR) proves to be one of the most effective methods of label-free detection and has been integral for the study of biomolecular interactions and the development of biosensors. This trend delves into the latest SPR research and progress built upon the Kretschmann configuration, a pivotal platform, and highlights three key developments that have enhanced the capabilities of the technique. We will first cover a range of explorations of novel plasmonic materials that have shaped SPR performance. Innovative signal transduction and collection, which leverages traditional materials and emerging alternatives, will then be discussed. Finally, the evolving landscape of data analysis, including the integration of machine learning algorithms to navigate complex SPR datasets, will be reviewed. We will also discuss the implementation of these improvements that have enabled new biosensing functions. These advancements not only pave the way for enhanced biosensing in general but also open new avenues for the technique to play a more significant role in research concerning human health.

Curved Membrane Mimics for Quantitative Probing of Protein-Membrane Interactions by Surface Plasmon Resonance

A majority of biomimetic membranes used for current biophysical studies rely on planar structures such as supported lipid bilayer (SLB) and self-assembled monolayers (SAMs). While they have facilitated key information collection, the lack of curvature makes these models less effective for the investigation of curvature-dependent protein binding. Here, we report the development and characterization of curved membrane mimics on a solid substrate with tunable curvature and ease in incorporation of cellular membrane components for the study of protein-membrane interactions. The curved membranes were generated with an underlayer lipid membrane composed of DGS-Ni-NTA and POPC lipids on the substrate, followed by the attachment of histidine-tagged cholera toxin (his-CT) as a capture layer. Lipid vesicles containing different compositions of gangliosides, including GA1, GM1, GT1b, and GQ1b, were anchored to the capture layer, providing fixation of the curved membranes with intact structures. Characterization of the curved membrane was accomplished with surface plasmon resonance (SPR), fluorescence recovery after photobleaching (FRAP), and nano-tracking analysis (NTA). Further optimization of the interface was achieved through principal component analysis (PCA) to understand the effect of ganglioside type, percentage, and vesicle dimensions on their interactions with proteins. In addition, Monte Carlo simulations were employed to predict the distribution of the gangliosides and interaction patterns with single point and multipoint binding models. This work provides a reliable approach to generate robust, component-tuning, and curved membranes for investigating protein interactions more pertinently than what a traditional planar membrane offers.