Characterization of RBD-specific cross-neutralizing antibodies responses against SARS-CoV-2 variants from COVID-19 convalescents.

Introduction: The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has been posing a severe threat to global public health. Although broadly neutralizing antibodies have been used to prevent or treat corona virus disease 2019 (COVID-19), new emerging variants have been proven resistant to these antibodies. Methods: In this study, we isolated receptor binding domain (RBD)-specific memory B cells using single-cell sorting method from two COVID-19 convalescents and expressed the antibody to test their neutralizing activity against diverse SARS-CoV-2 variants. Then, we resolved antibody-RBD complex structures of potent RBD-specific neutralizing antibodies by X-ray diffraction method. Finally, we analyzed the whole antibody repertoires of the two donors and studied the evolutionary pathway of potent neutralizing antibodies. Results and discussion: We identified three potent RBD-specific neutralizing antibodies (1D7, 3G10 and 3C11) from two COVID-19 convalescents that neutralized authentic SARS-CoV-2 WH-1 and Delta variant, and one of them, 1D7, presented broadly neutralizing activity against WH-1, Beta, Gamma, Delta and Omicron authentic viruses. The resolved antibody-RBD complex structures of two antibodies, 3G10 and 3C11, indicate that both of them interact with the external subdomain of the RBD and that they belong to the RBD-1 and RBD-4 communities, respectively. From the antibody repertoire analysis, we found that the CDR3 frequencies of the light chain, which shared high degrees of amino acid identity with these three antibodies, were higher than those of the heavy chain. This research will contribute to the development of RBD-specific antibody-based drugs and immunogens against multiple variants.

SARS Cov-2 vaccines and vaccination strategies

A rapid change has been undergone in the current pandemic and many countries are being exposed to the third wave of COVID-19. The tireless work for the discovery of vaccine had begun by the time the disease occupied a major part of the globe. This is mainly due to the efficacy of vaccines in preventing diseases and it is one of the cost effective strategies adopted for the prevention of many diseases. Currently a lot of countries have come forth with suitable vaccines to tackle the SARS CoV-2 to some extent. This paper incorporates details about vaccination and the common vaccines in use against COVID-19. Based on the evidences available, keen observations and studies carried out on the previously emerged SARS and MERS, the vaccine against SARS CoV-2 was developed, however the primary focus depend on the spike protein which was considered as a target for the development of suitable immunotherapies and thereby played a potential role in the vaccine development process. Vaccination is the most significant strategy to stop the pandemic and the efficacy of SARS-CoV-2 vaccines provides a genuine gauge of hope for future. © 2020 The author (s). Published by Zagazig University.

A Computational Framework for Determining the Breadth of Antibodies Against Highly Mutable Pathogens

Highly mutable pathogens pose daunting challenges for antibody design. The usual criteria of high potency and specificity are often insufficient to design antibodies that provide long-lasting protection. This is due, in part, to the ability of the pathogen to rapidly acquire mutations that permit them to evade the designed antibodies. To overcome these limitations, design of antibodies with a larger neutralizing breadth can be pursued. Such broadly neutralizing antibodies (bnAbs) should remain targeted to a specific epitope, yet show robustness against pathogen mutability, thereby neutralizing a higher number of antigens. This is particularly important for highly mutable pathogens, like the influenza virus and the human immunodeficiency virus (HIV). The protocol describes a method for computing the "breadth” of a given antibody, an essential aspect of antibody design. © 2023, Springer Science+Business Media, LLC, part of Springer Nature.

AbAgIntPre: A deep learning method for predicting antibody-antigen interactions based on sequence information.

Introduction: Antibody-mediated immunity is an essential part of the immune system in vertebrates. The ability to specifically bind to antigens allows antibodies to be widely used in the therapy of cancers and other critical diseases. A key step in antibody therapeutics is the experimental identification of antibody-antigen interactions, which is generally time-consuming, costly, and laborious. Although some computational methods have been proposed to screen potential antibodies, the dependence on 3D structures still limits the application of these methods. Methods: Here, we developed a deep learning-assisted prediction method (i.e., AbAgIntPre) for fast identification of antibody-antigen interactions that only relies on amino acid sequences. A Siamese-like convolutional neural network architecture was established with the amino acid composition encoding scheme for both antigens and antibodies. Results and Discussion: The generic model of AbAgIntPre achieved satisfactory performance with the Area Under Curve (AUC) of 0.82 on a high-quality generic independent test dataset. Besides, this approach also showed competitive performance on the more specific SARS-CoV dataset. We expect that AbAgIntPre can serve as an important complement to traditional experimental methods for antibody screening and effectively reduce the workload of antibody design. The web server of AbAgIntPre is freely available at http://www.zzdlab.com/AbAgIntPre.

Improved Antibody-Specific Epitope Prediction Using AlphaFold and AbAdapt.

Antibodies recognize their cognate antigens with high affinity and specificity, but the prediction of binding sites on the antigen (epitope) corresponding to a specific antibody remains a challenging problem. To address this problem, we developed AbAdapt, a pipeline that integrates antibody and antigen structural modeling with rigid docking in order to derive antibody-antigen specific features for epitope prediction. In this study, we systematically assessed the impact of integrating the state-of-the-art protein modeling method AlphaFold with the AbAdapt pipeline. By incorporating more accurate antibody models, we observed improvement in docking, paratope prediction, and prediction of antibody-specific epitopes. We further applied AbAdapt-AF in an anti-receptor binding domain (RBD) antibody complex benchmark and found AbAdapt-AF outperformed three alternative docking methods. Also, AbAdapt-AF demonstrated higher epitope prediction accuracy than other tested epitope prediction tools in the anti-RBD antibody complex benchmark. We anticipate that AbAdapt-AF will facilitate prediction of antigen-antibody interactions in a wide range of applications.

Monoclonal Antibodies as Potential Treatment Drugs for Nsp15 and 3CLpro Proteins

Selected monoclonal antibody molecules were conducted using the antibody-antigen docking mode, as well as the antibody-antigen docking approach. The objective of the study was to check the effects of Cetuximab COVID-19 proteins (Nsp15 and 3CLpro) by using antibody-antigen docking mode, as well as the antibody-antigen docking approach. The results of molecular docking revealed that Cetuximab, a cancer-fighting antibody, ranks first among antibodies to both COVID-19 proteins (Nsp15 and 3CLpro). In cetuximab-3CLpro and cetuximab-Nsp15 complexes, the antigen interacts with both antibody chains, H and L. According to the findings, Cetuximab can be added to the COVID-19 treatment protocol, which may have the desired effect of inhibiting viral replication and decreasing mortality by targeting COVID-19 proteins (Nsp15 and 3CLpro). Validation of these computational findings will require additional in vitro and in vivo research, which can be considered as a contribution in the field of biotechnology © 2023, Physical Chemistry Research.All Rights Reserved.

Printed Capacitive Immunoassay for Detecting SARS-CoV-2 Viral Particles

The key to fight against a global pandemic such as COVID-19 is to have low-cost, reliable and fast response diagnostic tools. Electronic biosensors are preferred because of their ease of integration into current centralized health care networks and integration with modern point-of-care testing (POCT) devices. Printed electronic sensors provide a sensitive and reliable diagnostic platform to aid in controlling transmissible diseases. In this work, we demonstrate a fully printed capacitive biosensor. The sensor uses coplanar electrodes, coupled with capture antibodies immobilized on microporous Polyvinylidene-fluoride (PVDF) film to detect the SARS-CoV-2 spike protein in spiked buffer solutions. Antibody immobilization on PVDF surface is confirmed with confocal fluorescent imaging microscopy. Gold nanoparticle (GNP) tagged detection antibodies are also introduced to provide increased sensitivity. The gold nanoparticles provide a reflectance layer which leads to increased capacitance. This increased capacitance can be measured directly and has demonstrated the ability to screen for spiked samples with statistical significance. This fully printed capacitive immunoassay has the potential to be used as a transmissible disease screening and vaccine efficacy assessment tool for resource-limited areas. IEEE

Investigation and Comparison of Specific Antibodies' Affinity Interaction with SARS-CoV-2 Wild-Type, B.1.1.7, and B.1.351 Spike Protein by Total Internal Reflection Ellipsometry.

SARS-CoV-2 vaccines provide strong protection against COVID-19. However, the emergence of SARS-CoV-2 variants has raised concerns about the efficacy of vaccines. In this study, we investigated the interactions of specific polyclonal human antibodies (pAb-SCoV2-S) produced after vaccination with the Vaxzevria vaccine with the spike proteins of three SARS-CoV-2 variants of concern: wild-type, B.1.1.7, and B.1.351. Highly sensitive, label-free, and real-time monitoring of these interactions was accomplished using the total internal reflection ellipsometry method. Thermodynamic parameters such as association and dissociation rate constants, the stable immune complex formation rate constant (kr), the equilibrium association and dissociation (KD) constants and steric factors (Ps) were calculated using a two-step irreversible binding mathematical model. The results obtained show that the KD values for the specific antibody interactions with all three types of spike protein are in the same nanomolar range. The KD values for B.1.1.7 and B.1.351 suggest that the antibody produced after vaccination can successfully protect the population from the alpha (B.1.1.7) and beta (B.1.351) SARS-CoV-2 mutations. The steric factors (Ps) obtained for all three types of spike proteins showed a 100-fold lower requirement for the formation of an immune complex when compared with nucleocapsid protein.

Design and simulation of a millifluidic device for differential detection of SARS-CoV-2 and H1N1 based on triboelectricity.

Differential diagnosis of pathogenic diseases, presently coronavirus disease 2019 (COVID-19) and influenza, is crucial with due attention to their superspreading events, presumably long incubation period, particular complications, and treatments. In this paper, a label-free, self-powered, and ultrafast immunosensor device working based on triboelectric effect is proposed. Equilibrium constants of specific antibody-antigen reactions are accompanied by IEP-relevant electric charges of antigens to recognize SARS-CoV-2 and H1N1. Simulation attributes including fluid flow and geometrical parameters are optimized so that the maximum capture efficiency of 85.63% is achieved. Accordingly, antibody-antigen complexes form electric double layers (EDLs) across the channel interfaces. The resultant built-in electric field affects the following external electric field derived from triboelectricity, leading to the variation of open-circuit voltage as a sensing metric. The device is flexible to operate in conductor-to-dielectric single-electrode and contact-separation modes simultaneously. While the detection limit is reduced utilizing the single-electrode mode compared to the latter one, surface treatment of the triboelectric pair contributes to the sensitivity enhancement. A threshold value equal to -4.113 V is featured to discriminate these two viruses in a vast detectable region; however, further surface engineering can allow the on-site detection of any electrically-charged pathogen applying the emerging triboelectric immunosensor enjoying a lower detection limit.

Advances and insights in the diagnosis of viral infections.

Viral infections are the most common among diseases that globally require around 60 percent of medical care. However, in the heat of the pandemic, there was a lack of medical equipment and inpatient facilities to provide all patients with viral infections. The detection of viral infections is possible in three general ways such as (i) direct virus detection, which is performed immediately 1-3 days after the infection, (ii) determination of antibodies against some virus proteins mainly observed during/after virus incubation period, (iii) detection of virus-induced disease when specific tissue changes in the organism. This review surveys some global pandemics from 1889 to 2020, virus types, which induced these pandemics, and symptoms of some viral diseases. Non-analytical methods such as radiology and microscopy also are overviewed. This review overlooks molecular analysis methods such as nucleic acid amplification, antibody-antigen complex determination, CRISPR-Cas system-based viral genome determination methods. Methods widely used in the certificated diagnostic laboratory for SARS-CoV-2, Influenza A, B, C, HIV, and other viruses during a viral pandemic are outlined. A comprehensive overview of molecular analytical methods has shown that the assay's sensitivity, accuracy, and suitability for virus detection depends on the choice of the number of regions in the viral open reading frame (ORF) genome sequence and the validity of the selected analytical method.

Structures and therapeutic potential of anti-RBD human monoclonal antibodies against SARS-CoV-2.

Background: Administration of potent anti-receptor-binding domain (RBD) monoclonal antibodies has been shown to curtail viral shedding and reduce hospitalization in patients with SARS-CoV-2 infection. However, the structure-function analysis of potent human anti-RBD monoclonal antibodies and its links to the formulation of antibody cocktails remains largely elusive. Methods: Previously, we isolated a panel of neutralizing anti-RBD monoclonal antibodies from convalescent patients and showed their neutralization efficacy in vitro. Here, we elucidate the mechanism of action of antibodies and dissect antibodies at the epitope level, which leads to a formation of a potent antibody cocktail. Results: We found that representative antibodies which target non-overlapping epitopes are effective against wild type virus and recently emerging variants of concern, whilst being encoded by antibody genes with few somatic mutations. Neutralization is associated with the inhibition of binding of viral RBD to ACE2 and possibly of the subsequent fusion process. Structural analysis of representative antibodies, by cryo-electron microscopy and crystallography, reveals that they have some unique aspects that are of potential value while sharing some features in common with previously reported neutralizing monoclonal antibodies. For instance, one has a common VH 3-53 public variable region yet is unusually resilient to mutation at residue 501 of the RBD. We evaluate the in vivo efficacy of an antibody cocktail consisting of two potent non-competing anti-RBD antibodies in a Syrian hamster model. We demonstrate that the cocktail prevents weight loss, reduces lung viral load and attenuates pulmonary inflammation in hamsters in both prophylactic and therapeutic settings. Although neutralization of one of these antibodies is abrogated by the mutations of variant B.1.351, it is also possible to produce a bi-valent cocktail of antibodies both of which are resilient to variants B.1.1.7, B.1.351 and B.1.617.2. Conclusions: These findings support the up-to-date and rational design of an anti-RBD antibody cocktail as a therapeutic candidate against COVID-19.

Neutralizing Antibodies to SARS-CoV-2 Selected from a Human Antibody Library Constructed Decades Ago.

Combinatorial antibody libraries not only effectively reduce antibody discovery to a numbers game, but enable documentation of the history of antibody responses in an individual. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic has prompted a wider application of this technology to meet the public health challenge of pandemic threats in the modern era. Herein, a combinatorial human antibody library constructed 20 years before the coronavirus disease 2019 (COVID-19) pandemic is used to discover three highly potent antibodies that selectively bind SARS-CoV-2 spike protein and neutralize authentic SARS-CoV-2 virus. Compared to neutralizing antibodies from COVID-19 patients with generally low somatic hypermutation (SHM), these three antibodies contain over 13-22 SHMs, many of which are involved in specific interactions in their crystal structures with SARS-CoV-2 spike receptor binding domain. The identification of these somatically mutated antibodies in a pre-pandemic library raises intriguing questions about the origin and evolution of these antibodies with respect to their reactivity with SARS-CoV-2.

A combination of cross-neutralizing antibodies synergizes to prevent SARS-CoV-2 and SARS-CoV pseudovirus infection.

Coronaviruses have caused several human epidemics and pandemics including the ongoing coronavirus disease 2019 (COVID-19). Prophylactic vaccines and therapeutic antibodies have already shown striking effectiveness against COVID-19. Nevertheless, concerns remain about antigenic drift in SARS-CoV-2 as well as threats from other sarbecoviruses. Cross-neutralizing antibodies to SARS-related viruses provide opportunities to address such concerns. Here, we report on crystal structures of a cross-neutralizing antibody, CV38-142, in complex with the receptor-binding domains from SARS-CoV-2 and SARS-CoV. Recognition of the N343 glycosylation site and water-mediated interactions facilitate cross-reactivity of CV38-142 to SARS-related viruses, allowing the antibody to accommodate antigenic variation in these viruses. CV38-142 synergizes with other cross-neutralizing antibodies, notably COVA1-16, to enhance neutralization of SARS-CoV and SARS-CoV-2, including circulating variants of concern B.1.1.7 and B.1.351. Overall, this study provides valuable information for vaccine and therapeutic design to address current and future antigenic drift in SARS-CoV-2 and to protect against zoonotic SARS-related coronaviruses.

Multiplex bead binding assays using off-the-shelf components and common flow cytometers.

The ability to quantify protein-ligand interactions in an accurate and high-throughput manner is important in diverse areas of biology and medicine. Multiplex bead binding assays (MBBAs) are powerful methods that allow for simultaneous analysis of many protein-ligand interactions. Although there are a number of well-established MBBA platforms, there are few platforms suitable for research and development that offer rapid experimentation at low costs and without the need for specialized reagents or instruments dedicated for MBBA. Here, we describe a MBBA method that uses low-cost reagents and standard cytometers. The key innovation is the use of the essentially irreversible biotin-streptavidin interaction. We prepared a biotin-conjugated fluorescent dye and used it to produce streptavidin-coated magnetic beads that are labeled at distinct levels of fluorescence. We show the utility of our method in characterization of phage-displayed antibodies against multiple antigens of SARS-CoV-2, which substantially improves the throughput and dramatically reduces antigen consumption compared with conventional phage ELISA methods. This approach will make MBBAs more broadly accessible.

The ACE2-binding Interface of SARS-CoV-2 Spike Inherently Deflects Immune Recognition.

The COVID-19 pandemic remains a global threat, and host immunity remains the main mechanism of protection against the disease. The spike protein on the surface of SARS-CoV-2 is a major antigen and its engagement with human ACE2 receptor plays an essential role in viral entry into host cells. Consequently, antibodies targeting the ACE2-interacting surface (ACE2IS) located in the receptor-binding domain (RBD) of the spike protein can neutralize the virus. However, the understanding of immune responses to SARS-CoV-2 is still limited, and it is unclear how the virus protects this surface from recognition by antibodies. Here, we designed an RBD mutant that disrupts the ACE2IS and used it to characterize the prevalence of antibodies directed to the ACE2IS from convalescent sera of 94 COVID-19-positive patients. We found that only a small fraction of RBD-binding antibodies targeted the ACE2IS. To assess the immunogenicity of different parts of the spike protein, we performed in vitro antibody selection for the spike and the RBD proteins using both unbiased and biased selection strategies. Intriguingly, unbiased selection yielded antibodies that predominantly targeted regions outside the ACE2IS, whereas ACE2IS-binding antibodies were readily identified from biased selection designed to enrich such antibodies. Furthermore, antibodies from an unbiased selection using the RBD preferentially bound to the surfaces that are inaccessible in the context of whole spike protein. These results suggest that the ACE2IS has evolved less immunogenic than the other regions of the spike protein, which has important implications in the development of vaccines against SARS-CoV-2.