A Strategy to Detect Emerging Non-Delta SARS-CoV-2 Variants with a Monoclonal Antibody Specific for the N501 Spike Residue

Application of the Nicoya OpenSPR to Studies of Biomolecular Binding: A Review of the Literature from 2016 to 2022

The Nicoya OpenSPR is a benchtop surface plasmon resonance (SPR) instrument. As with other optical biosensor instruments, it is suitable for the label-free interaction analysis of a diverse set of biomolecules, including proteins, peptides, antibodies, nucleic acids, lipids, viruses, and hormones/cytokines. Supported assays include affinity/kinetics characterization, concentration analysis, yes/no assessment of binding, competition studies, and epitope mapping. OpenSPR exploits localized SPR detection in a benchtop platform and can be connected with an autosampler (XT) to perform automated analysis over an extended time period. In this review article, we provide a comprehensive survey of the 200 peer-reviewed papers published between 2016 and 2022 that use the OpenSPR platform. We highlight the range of biomolecular analytes and interactions that have been investigated using the platform, provide an overview on the most common applications for the instrument, and point out some representative research that highlights the flexibility and utility of the instrument.

QM/MM study of N501 involved intermolecular interaction between SARS-CoV-2 receptor binding domain and antibody of human origin

Intermolecular interaction between key residue N501 of the epitope on SARS-CoV-2 RBD and screening antibody B38 was studied using the QM/MM and QM approach. The QM/MM optimized geometry shows that angle X-H---Y is 165° for O-H---O between mAb light chain S30 and RBD N501. High level MP2 calculations indicated the interaction between RBD N501 and S30 of B38 Fab light chain provide a relatively strong attractive force of - 3.32 kcal/mol, whereas the hydrogen bond between RBD Q498 and S30 was quantified as 0.10 kcal/mol. The decrease in ESP partial charge on hydrogen atom of hydroxyl group on S30 drops from 0.38 a.u. to 0.31 a.u., exhibiting the sharing of 0.07 a.u. from the lone pair electron oxygen of N501 due to hydrogen bond formation. The NBO occupancy of hydrogen atom also decreases from 25.79 % to 22.93 % in the hydroxyl H-O NBO bond of S30. However, the minor change of NBO hybridization of hydroxyl oxygen of S30 from sp3.00 to sp3.05 implies the rigidity of hydrogen bond tetrahedral geometry in the relative dynamic protein complex. The O-H---O angle is 165° which is close but not exactly linear. The structural requirement for sp3 hybridization of oxygen for hydroxyl group on S30 and dimension of protein likely prevent O-H---O from adopting linear geometry. The hydrogen bond strengths were also calculated using a variety of DFT methods, and the result of - 3.33 kcal/mol from the M06L method is the closest to that of the MP2 calculation. Results of this work may aid in the COVID-19 vaccine and drug screening.

Recombinant Protein Micelles to Block Transduction by SARS-CoV-2 Pseudovirus

The continuing emergence of variants of the SARS-CoV-2 virus requires the development of modular molecular therapies. Here, we engineered a recombinant amphiphilic protein, oleosin, to spontaneously self-assemble into multivalent micellar nanostructures which can block the Spike S1 protein of SARS-CoV-2 pseudoviruses (PVs). Short recombinant proteins like oleosin can be formulated more easily than antibodies and can be functionalized with precision through genetic engineering. We cloned S1-binding mini-protein genes called LCBx, previously designed by David Baker's laboratory (UW Seattle), to the N-terminus of oleosin, expressing Oleo-LCBx proteins in E. coli. These proteins largely formed 10-100 nm micelles as verified by dynamic light scattering. Two proteins, Oleo-LCB1 and Oleo-LCB3, were seen to completely and irreversibly block transduction by both wild-type and delta variant PVs into 293T-hsACE2 cells at 10 μM. Presented in multivalent micelles, these proteins reduced transduction by PVs down to a functional protein concentration of 5 nM. Additionally, Oleo-LCB1 micelles outperformed corresponding synthetic LCB1 mini-proteins in reducing transduction by PVs. Tunable aqueous solubility of recombinant oleosin allowed incorporation of peptides/mini-proteins at high concentrations within micelles, thus enhancing drug loading. To validate the potential multifunctionality of the micelles, we showed that certain combinations of Oleo-LCB1 and Oleo-LCB3 performed much better than the individual proteins at the same concentration. These micelles, which we showed to be non-toxic to human cells, are thus a promising step toward the design of modular, multifunctional therapeutics that could bind to and inactivate multiple receptors and proteins necessary for the infection of the SARS-CoV-2 virus.

An Update on Detection Technologies for SARS-CoV-2 Variants of Concern

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is responsible for the global epidemic of Coronavirus Disease 2019 (COVID-19), with a significant impact on the global economy and human safety. Reverse transcription-quantitative polymerase chain reaction (RT-PCR) is the gold standard for detecting SARS-CoV-2, but because the virus's genome is prone to mutations, the effectiveness of vaccines and the sensitivity of detection methods are declining. Variants of concern (VOCs) include Alpha, Beta, Gamma, Delta, and Omicron, which are able to evade recognition by host immune mechanisms leading to increased transmissibility, morbidity, and mortality of COVID-19. A range of research has been reported on detection techniques for VOCs, which is beneficial to prevent the rapid spread of the epidemic, improve the effectiveness of public health and social measures, and reduce the harm to human health and safety. However, a meaningful translation of this that reduces the burden of disease, and delivers a clear and cohesive message to guide daily clinical practice, remains preliminary. Herein, we summarize the capabilities of various nucleic acid and protein-based detection methods developed for VOCs in identifying and differentiating current VOCs and compare the advantages and disadvantages of each method, providing a basis for the rapid detection of VOCs strains and their future variants and the adoption of corresponding preventive and control measures.

COVI3D: Automatic COVID-19 CT Image-Based Classification and Visualization Platform Utilizing Virtual and Augmented Reality Technologies

Recently many studies have shown the effectiveness of using augmented reality (AR) and virtual reality (VR) in biomedical image analysis. However, they are not automating the COVID level classification process. Additionally, even with the high potential of CT scan imagery to contribute to research and clinical use of COVID-19 (including two common tasks in lung image analysis: segmentation and classification of infection regions), publicly available data-sets are still a missing part in the system care for Algerian patients. This article proposes designing an automatic VR and AR platform for the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) pandemic data analysis, classification, and visualization to address the above-mentioned challenges including (1) utilizing a novel automatic CT image segmentation and localization system to deliver critical information about the shapes and volumes of infected lungs, (2) elaborating volume measurements and lung voxel-based classification procedure, and (3) developing an AR and VR user-friendly three-dimensional interface. It also centered on developing patient questionings and medical staff qualitative feedback, which led to advances in scalability and higher levels of engagement/evaluations. The extensive computer simulations on CT image classification show a better efficiency against the state-of-the-art methods using a COVID-19 dataset of 500 Algerian patients. The developed system has been used by medical professionals for better and faster diagnosis of the disease and providing an effective treatment plan more accurately by using real-time data and patient information.