Coronavirus Antiviral Research Database (CoV-RDB): An Online Database Designed to Facilitate Comparisons between Candidate Anti-Coronavirus Compounds

A novel class of broad-spectrum active-site-directed 3C-like protease inhibitors with nanomolar antiviral activity against highly immune-evasive SARS-CoV-2 Omicron subvariants

Antivirals with broad coronavirus activity are important for treating high-risk individuals exposed to the constantly evolving SARS-CoV-2 variants of concern (VOCs) as well as emerging drug-resistant variants. We developed and characterized a novel class of active-site-directed 3-chymotrypsin-like protease (3CLpro) inhibitors (C2-C5a). Our lead direct-acting antiviral (DAA), C5a, is a non-covalent, non-peptide with a dissociation constant of 170 nM against recombinant SARS-CoV-2 3CLpro. The compounds C2-C5a exhibit broad-spectrum activity against Omicron subvariants (BA.5, BQ.1.1, and XBB.1.5) and seasonal human coronavirus-229E infection in human cells. Notably, C5a has median effective concentrations of 30-50 nM against BQ.1.1 and XBB.1.5 in two different human cell lines. X-ray crystallography has confirmed the unique binding modes of C2-C5a to the 3CLpro, which can limit virus cross-resistance to emerging Paxlovid-resistant variants. We tested the effect of C5a with two of our newly discovered host-directed antivirals (HDAs): N-0385, a TMPRSS2 inhibitor, and bafilomycin D (BafD), a human vacuolar H+-ATPase [V-ATPase] inhibitor. We demonstrated a synergistic action of C5a in combination with N-0385 and BafD against Omicron BA.5 infection in human Calu-3 lung cells. Our findings underscore that a SARS-CoV-2 multi-targeted treatment for circulating Omicron subvariants based on DAAs (C5a) and HDAs (N-0385 or BafD) can lead to therapeutic benefits by enhancing treatment efficacy. Furthermore, the high-resolution structures of SARS-CoV-2 3CLpro in complex with C2-C5a will facilitate future rational optimization of our novel broad-spectrum active-site-directed 3C-like protease inhibitors.

Light chain of a public SARS-CoV-2 class-3 antibody modulates neutralization against Omicron

The pairing of antibody genes IGHV2-5/IGLV2-14 is established as a public immune response that potently cross-neutralizes SARS-CoV-2 variants, including Omicron, by targeting class-3/RBD-5 epitopes in the receptor binding domain (RBD). LY-CoV1404 (bebtelovimab) exemplifies this, displaying exceptional potency against Omicron sub-variants up to BA.5. Here, we report a human antibody, 002-S21B10, encoded by the public clonotype IGHV2-5/IGLV2-14. While 002-S21B10 neutralized key SARS-CoV-2 variants, it did not neutralize Omicron, despite sharing >92% sequence similarity with LY-CoV1404. The structure of 002-S21B10 in complex with spike trimer plus structural and sequence comparisons with LY-CoV1404 and other IGHV2-5/IGLV2-14 antibodies revealed significant variations in light-chain orientation, paratope residues, and epitope-paratope interactions that enable some antibodies to neutralize Omicron but not others. Confirming this, replacing the light chain of 002-S21B10 with the light chain of LY-CoV1404 restored 002-S21B10's binding to Omicron. Understanding such Omicron evasion from public response is vital for guiding therapeutics and vaccine design.

Unraveling the impact of ORF3a Q57H mutation on SARS-CoV-2: insights from molecular dynamics

ORF3a is a conserved accessory protein of SARS-CoV-2, linked to viral infection and pathogenesis, with acquired mutations at various locations. Previous studies have shown that the occurrence of the Q57H mutation is higher in comparison to other positions in ORF3a. This mutation is known to induce conformational changes, yet the extent of structural alteration and its role in the viral adaptation process remain unknown. Here we performed molecular dynamics (MD) simulations of wt-ORF3a, Q57H, and Q57A mutants to analyze structural changes caused by mutations compared to the native protein. The MD analysis revealed that Q57H and Q57A mutants show significant structural changes in the dimer conformation than the wt-ORF3a. This dimer conformer narrows down the ion channel cavity, which reduces Na + or K + permeability leading to decrease the antigenic response that can help the virus to escape the host immune system. Non-bonding interaction analysis shows the Q57H mutant has more interacting residues, resulting in more stability within dimer conformation than the wt-ORF3a and Q57A. Moreover, both mutant dimers (Q57H and Q57A) form a novel salt-bridge interaction at the same position between A:Asp142 and B:Lys61, whereas such an interaction is absent in the wt-ORF3a dimer. We have also noticed that the TM3 domain's flexibility in Q57H is increased because of strong inter-domain interactions of TM1 and TM2 within the dimer conformation. These unusual interactions and flexibility of Q57H mutant can have significant impacts on the SARS-CoV-2 adaptations, virulence, transmission, and immune system evasion. Our findings are consistent with the previous experimental data and provided details information on the structural perturbation in ORF3a caused by mutations, which can help better understand the structural change at the molecular level as well as the reason for the high virulence properties of this variant.Communicated by Ramaswamy H. Sarma.

Modeling of ACE2 and antibodies bound to SARS-CoV-2 provides insights into infectivity and immune evasion

Given the COVID-19 pandemic, there is interest in understanding ligand-receptor features and targeted antibody-binding attributes against emerging SARS-CoV-2 variants. Here, we developed a large-scale structure-based pipeline for analysis of protein-protein interactions regulating SARS-CoV-2 immune evasion. First, we generated computed structural models of the Spike protein of 3 SARS-CoV-2 variants (B.1.1.529, BA.2.12.1, and BA.5) bound either to a native receptor (ACE2) or to a large panel of targeted ligands (n = 282), which included neutralizing or therapeutic monoclonal antibodies. Moreover, by using the Barnes classification, we noted an overall loss of interfacial interactions (with gain of new interactions in certain cases) at the receptor-binding domain (RBD) mediated by substituted residues for neutralizing complexes in classes 1 and 2, whereas less destabilization was observed for classes 3 and 4. Finally, an experimental validation of predicted weakened therapeutic antibody binding was performed in a cell-based assay. Compared with the original Omicron variant (B.1.1.529), derivative variants featured progressive destabilization of antibody-RBD interfaces mediated by a larger set of substituted residues, thereby providing a molecular basis for immune evasion. This approach and findings provide a framework for rapidly and efficiently generating structural models for SARS-CoV-2 variants bound to ligands of mechanistic and therapeutic value.

Alpha to Omicron (Variants of Concern): Mutation Journey, Vaccines, and Therapy

Coronavirus disease 2019 caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) initially emerged in December 2019 and has subsequently expanded globally, leading to the ongoing pandemic. The extensive spread of various SARS-CoV-2 variants possesses a serious public health threat. An extensive literature search along with deep analysis was performed to describe and evaluate the characteristics of SARS-CoV-2 variants of concern in relation to the effectiveness of the current vaccines and therapeutics. The obtained results showed that several significant mutations have evolved during the COVID-19 pandemic. The developed variants and their various structural mutations can compromise the effectiveness of several vaccines, escape the neutralizing antibodies, and limit the efficiency of available therapeutics. Furthermore, deep analysis of the available data enables the prediction of the future impact of virus mutations on the ongoing pandemic along with the selection of appropriate vaccines and therapeutics.

Coronavirus Immunotherapeutic Consortium Database

The coronavirus disease 2019 (COVID-19) pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has seen multiple anti-SARS-CoV-2 antibodies being generated globally. It is difficult, however, to assemble a useful compendium of these biological properties if they are derived from experimental measurements performed at different sites under different experimental conditions. The Coronavirus Immunotherapeutic Consortium (COVIC) circumvents these issues by experimentally testing blinded antibodies side by side for several functional activities. To collect these data in a consistent fashion and make it publicly available, we established the COVIC database (COVIC-DB, https://covicdb.lji.org/). This database enables systematic analysis and interpretation of this large-scale dataset by providing a comprehensive view of various features such as affinity, neutralization, in vivo protection and effector functions for each antibody. Interactive graphs enable direct comparisons of antibodies based on select functional properties. We demonstrate how the COVIC-DB can be utilized to examine relationships among antibody features, thereby guiding the design of therapeutic antibody cocktails. Database URL  https://covicdb.lji.org/.

Structural patterns of SARS-CoV-2 variants of concern (alpha, beta, gamma, delta) spike protein are influenced by variant-specific amino acid mutations: A computational study with implications on viral evolution

SARS-CoV-2 (SARS2) regularly mutates resulting to variants of concern (VOC) which have higher virulence and transmissibility rates while concurrently evading available therapeutic strategies. This highlights the importance of amino acid mutations occurring in the SARS2 spike protein structure since it may affect virus biology. However, this was never fully elucidated. Here, network analysis was performed based on the COVID-19 genomic epidemiology network between December 2019-July 2021. Representative SARS2 VOC spike protein models were generated and quality checked, protein model superimposition was done, and common contact based on contact mapping was established. Throughout this study, we found that: (1) certain individual variant-specific amino acid mutations can affect the spike protein structural pattern; (2) certain individual variant-specific amino acid mutations had no affect on the spike protein structural pattern; and (3) certain combination of variant-specific amino acids are putatively epistatic mutations that can potentially influence the VOC spike protein structural pattern. This manuscript was submitted as part of a theme issue on "Modelling COVID-19 and Preparedness for Future Pandemics".

The SARS-CoV-2 Delta (B.1.617.2) variant with spike N501Y mutation in the shadow of Omicron emergence

Circulation of the Omicron variant with the reemergence of the N501Y mutation along with many others in the spike protein has once again stirred the academic community. Interestingly, tracing the genetic diversity of SARS-CoV-2 shed light on a less frequent N501Y + Delta variant which has been in the global circulation for some time before the Omicron appearance. This paper aims to present the molecular characteristics of the SARS-CoV-2 Spike_N501Y + Delta variant detected in Bosnia and Herzegovina. The study was conducted during November and December 2021. All patients were tested using real-time RT-PCR for detection of SARS-CoV-2. A representative number of SARS-CoV-2 positive samples was pre-screened using VirSNiP SARS-CoV-2 Spike N501Y kit. The characterization of the viruses was carried out with Illumina RNA Prep with enrichment and the Respiratory Virus Oligo Panel kit. Among the analyzed sequences, we found two isolates of the Delta variant that differ from their most related clade- GK AY.4.3 in additional mutations N501Y and L54F. In this study, we described the presence of a rare form of Delta variant with Spike_N501Y mutation in the shadow of the Omicron emergence. Despite the set of mutations in the Spike protein, this form of Delta variant does not indicate the large-scale consequences for the general population. Further functional studies of this form could provide more information about its antigenicity and infectivity.

Investigation of SARS-CoV-2 Variants and Their Effect on SARS-CoV-2 Monoclonal Antibodies, Convalescent and Vaccine Plasma by a Novel Web Tool

(1) Background: SARS-CoV-2 variants possess specific mutations throughout their genome; however, the effect of these mutations on pathogenesis is little known. The study aimed to identify SARS-CoV-2 variants and their susceptibility rate against monoclonal antibodies, convalescent, and vaccine plasma. (2) Methods: Strains isolated from COVID-19 cases in Turkey in April and September 2021 were involved. Illuma Nextera XT was processed for NGS, followed by virtual phenotyping (Coronavirus Antiviral and Resistance Database (CoV-RDB) by Stanford University). (3) Results: Among 211 strains, 79% were SARS-CoV-2 variants. B.1.1.7 (Alpha) was the most dominant, followed by B.1.617.2 (Delta), B.1.351 (Beta), and B.1.525 (Eta). Alpha and Delta were less susceptible to Etesevimab-Sotrovimab and Bamlanivimab-Etesevimab, respectively. Reduced efficacy was observed for convalescent plasma in Beta and Delta; AstraZeneca, Comirnaty plus AstraZeneca in Alpha; Comirnaty, Moderna, Novovax in Beta; Comirnaty in Delta. (4) Conclusion: CoV-RDB analysis is an efficient, rapid, and helpful web tool for SARS-CoV-2 variant detection and susceptibility analysis.

Deep mutational learning predicts ACE2 binding and antibody escape to combinatorial mutations in the SARS-CoV-2 receptor-binding domain

The continual evolution of SARS-CoV-2 and the emergence of variants that show resistance to vaccines and neutralizing antibodies threaten to prolong the COVID-19 pandemic. Selection and emergence of SARS-CoV-2 variants are driven in part by mutations within the viral spike protein and in particular the ACE2 receptor-binding domain (RBD), a primary target site for neutralizing antibodies. Here, we develop deep mutational learning (DML), a machine-learning-guided protein engineering technology, which is used to investigate a massive sequence space of combinatorial mutations, representing billions of RBD variants, by accurately predicting their impact on ACE2 binding and antibody escape. A highly diverse landscape of possible SARS-CoV-2 variants is identified that could emerge from a multitude of evolutionary trajectories. DML may be used for predictive profiling on current and prospective variants, including highly mutated variants such as Omicron, thus guiding the development of therapeutic antibody treatments and vaccines for COVID-19.

On the Origins of Omicron's Unique Spike Gene Insertion

The emergence of a heavily mutated SARS-CoV-2 variant (Omicron; Pango lineage B.1.1.529 and BA sublineages) and its rapid spread to over 75 countries raised a global public health alarm. Characterizing the mutational profile of Omicron is necessary to interpret its clinical phenotypes which are shared with or distinctive from those of other SARS-CoV-2 variants. We compared the mutations of the initially circulating Omicron variant (now known as BA.1) with prior variants of concern (Alpha, Beta, Gamma, and Delta), variants of interest (Lambda, Mu, Eta, Iota, and Kappa), and ~1500 SARS-CoV-2 lineages constituting ~5.8 million SARS-CoV-2 genomes. Omicron's Spike protein harbors 26 amino acid mutations (23 substitutions, 2 deletions, and 1 insertion) that are distinct compared to other variants of concern. While the substitution and deletion mutations appeared in previous SARS-CoV-2 lineages, the insertion mutation (ins214EPE) was not previously observed in any other SARS-CoV-2 lineage. Here, we consider and discuss various mechanisms through which the nucleotide sequence encoding for ins214EPE could have been acquired, including local duplication, polymerase slippage, and template switching. Although we are not able to definitively determine the mechanism, we highlight the plausibility of template switching. Analysis of the homology of the inserted nucleotide sequence and flanking regions suggests that this template-switching event could have involved the genomes of SARS-CoV-2 variants (e.g., the B.1.1 strain), other human coronaviruses that infect the same host cells as SARS-CoV-2 (e.g., HCoV-OC43 or HCoV-229E), or a human transcript expressed in a host cell that was infected by the Omicron precursor.

Evolution of Stronger SARS-CoV-2 Variants as Revealed Through the Lens of Molecular Dynamics Simulations

Using molecular dynamics simulations, the protein–protein interactions of the receptor-binding domain of the wild-type and seven variants of the severe acute respiratory syndrome coronavirus 2 spike protein and the peptidase domain of human angiotensin-converting enzyme 2 were investigated. These variants are alpha, beta, gamma, delta, eta, kappa, and omicron. Using 100 ns simulation data, the residue interaction networks at the protein–protein interface were identified. Also, the impact of mutations on essential protein dynamics, backbone flexibility, and interaction energy of the simulated protein–protein complexes were studied. The protein–protein interface for the wild-type, delta, and omicron variants contained several stronger interactions, while the alpha, beta, gamma, eta, and kappa variants exhibited an opposite scenario as evident from the analysis of the inter-residue interaction distances and pair-wise interaction energies. The study reveals that two distinct residue networks at the central and right contact regions forge stronger binding affinity between the protein partners. The study provides a molecular-level insight into how enhanced transmissibility and infectivity by delta and omicron variants are most likely tied to a handful of interacting residues at the binding interface, which could potentially be utilized for future antibody constructs and structure-based antiviral drug design.

Fast Prediction of Binding Affinities of SARS-CoV-2 Spike Protein and Its Mutants with Antibodies through Intermolecular Interaction Modeling-Based Machine Learning

Since the introduction of the novel SARS-CoV-2 virus (COVID-19) in late 2019, various new variants have appeared with mutations that confer resistance to the vaccines and monoclonal antibodies that were developed in response to the wild-type virus. As we continue through the pandemic, an accurate and efficient methodology is needed to help predict the effects certain mutations will have on both our currently produced therapeutics and those that are in development. Using published cryo-electron microscopy and X-ray crystallography structures of the spike receptor binding domain region with currently known antibodies, in the present study, we created and cross-validated an intermolecular interaction modeling-based multi-layer perceptron machine learning approach that can accurately predict the mutation-caused shifts in the binding affinity between the spike protein (wild-type or mutant) and various antibodies. This validated artificial intelligence (AI) model was used to predict the binding affinity (Kd) of reported SARS-CoV-2 antibodies with various variants of concern, including the most recently identified "Deltamicron" (or "Deltacron") variant. This AI model may be employed in the future to predict the Kd of developed novel antibody therapeutics to overcome the challenging antibody resistance issue and develop structural bases for the effects of both current and new mutants of the spike protein. In addition, the similar AI strategy and approach based on modeling of the intermolecular interactions may be useful in development of machine learning models predicting binding affinities for other protein-protein binding systems, including other antibodies binding with their antigens.

Network for network concept offers new insights into host- SARS-CoV-2 protein interactions and potential novel targets for developing antiviral drugs

SARS-CoV-2, the causal agent of COVID-19, is primarily a pulmonary virus that can directly or indirectly infect several organs. Despite many studies carried out during the current COVID-19 pandemic, some pathological features of SARS-CoV-2 have remained unclear. It has been recently attempted to address the current knowledge gaps on the viral pathogenicity and pathological mechanisms via cellular-level tropism of SARS-CoV-2 using human proteomics, visualization of virus-host protein-protein interactions (PPIs), and enrichment analysis of experimental results. The synergistic use of models and methods that rely on graph theory has enabled the visualization and analysis of the molecular context of virus/host PPIs. We review current knowledge on the SARS-COV-2/host interactome cascade involved in the viral pathogenicity through the graph theory concept and highlight the hub proteins in the intra-viral network that create a subnet with a small number of host central proteins, leading to cell disintegration and infectivity. Then we discuss the putative principle of the "gene-for-gene and "network for network" concepts as platforms for future directions toward designing efficient anti-viral therapies.

Molecular characteristics, immune evasion, and impact of SARS-CoV-2 variants

The persistent COVID-19 pandemic since 2020 has brought an enormous public health burden to the global society and is accompanied by various evolution of the virus genome. The consistently emerging SARS-CoV-2 variants harboring critical mutations impact the molecular characteristics of viral proteins and display heterogeneous behaviors in immune evasion, transmissibility, and the clinical manifestation during infection, which differ each strain and endow them with distinguished features during populational spread. Several SARS-CoV-2 variants, identified as Variants of Concern (VOC) by the World Health Organization, challenged global efforts on COVID-19 control due to the rapid worldwide spread and enhanced immune evasion from current antibodies and vaccines. Moreover, the recent Omicron variant even exacerbated the global anxiety in the continuous pandemic. Its significant evasion from current medical treatment and disease control even highlights the necessity of combinatory investigation of the mutational pattern and influence of the mutations on viral dynamics against populational immunity, which would greatly facilitate drug and vaccine development and benefit the global public health policymaking. Hence in this review, we summarized the molecular characteristics, immune evasion, and impacts of the SARS-CoV-2 variants and focused on the parallel comparison of different variants in mutational profile, transmissibility and tropism alteration, treatment effectiveness, and clinical manifestations, in order to provide a comprehensive landscape for SARS-CoV-2 variant research.

SARS-CoV-2 Virology

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first identified in 2020 and has led to an unprecedented global pandemic. Understanding the virology behind SARS-CoV-2 infection has provided key insights into our efforts to develop antiviral agents and control the COVID-19 pandemic. In this review, the authors focus on the genomic features of SARS-CoV-2, its intrahost and interhost evolution, viral dynamics in respiratory tract, and systemic dissemination.

Identifying COVID-19 Severity-Related SARS-CoV-2 Mutation Using a Machine Learning Method

SARS-CoV-2 shows great evolutionary capacity through a high frequency of genomic variation during transmission. Evolved SARS-CoV-2 often demonstrates resistance to previous vaccines and can cause poor clinical status in patients. Mutations in the SARS-CoV-2 genome involve mutations in structural and nonstructural proteins, and some of these proteins such as spike proteins have been shown to be directly associated with the clinical status of patients with severe COVID-19 pneumonia. In this study, we collected genome-wide mutation information of virulent strains and the severity of COVID-19 pneumonia in patients varying depending on their clinical status. Important protein mutations and untranslated region mutations were extracted using machine learning methods. First, through Boruta and four ranking algorithms (least absolute shrinkage and selection operator, light gradient boosting machine, max-relevance and min-redundancy, and Monte Carlo feature selection), mutations that were highly correlated with the clinical status of the patients were screened out and sorted in four feature lists. Some mutations such as D614G and V1176F were shown to be associated with viral infectivity. Moreover, previously unreported mutations such as A320V of nsp14 and I164ILV of nsp14 were also identified, which suggests their potential roles. We then applied the incremental feature selection method to each feature list to construct efficient classifiers, which can be directly used to distinguish the clinical status of COVID-19 patients. Meanwhile, four sets of quantitative rules were set up, which can help us to more intuitively understand the role of each mutation in differentiating the clinical status of COVID-19 patients. Identified key mutations linked to virologic properties will help better understand the mechanisms of infection and will aid in the development of antiviral treatments.

A pyrosequencing protocol for rapid identification of SARS-CoV-2 variants

Next‐generation sequencing (NGS) is the primary method used to monitor the distribution and emergence of severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) variants around the world; however, it is costly and time‐consuming to perform and is not widely available in low‐resourced geographical regions. Pyrosequencing has the potential to augment surveillance efforts by providing information on specific targeted mutations for rapid identification of circulating and emerging variants. The current study describes the development of a reverse transcription (RT)‐PCR‐pyrosequencing assay targeting >65 spike protein gene (S) mutations of SARS‐CoV‐2, which permits differentiation of commonly reported variants currently circulating in the United States with a high degree of confidence. Variants typed using the assay included B.1.1.7 (Alpha), B.1.1.529 (Omicron), B.1.351 (Beta), B.1.375, B.1.427/429 (Epsilon), B.1.525 (Eta), B.1.526.1 (Iota), B.1.617.1 (Kappa), B.1.617.2 (Delta), B.1.621 (Mu), P1 (Gamma), and B.1.1 variants, all of which were confirmed by the NGS data. An electronic typing tool was developed to aid in the identification of variants based on mutations detected by pyrosequencing. The assay could provide an important typing tool for rapid identification of candidate patients for monoclonal antibody therapies and a method to supplement SARS‐CoV‐2 surveillance efforts by identification of circulating variants and novel emerging lineages.

Advanced Functions Embedded in the Second Version of Database, Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2

The Global Evaluation of SARS-CoV-2/hCoV-19 Sequences 2 (GESS v2 https://shiny.ph.iu.edu/GESS_v2/) is an updated version of GESS, which has offered a handy query platform to analyze single-nucleotide variants (SNVs) on millions of high coverages and high-quality severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) complete genomes provided by the Global Initiative on Sharing Avian Influenza Data (GISAID). Including the tools in the first version, the GESS v2 is embedded with new functions, which allow users to search SNVs, given the viral nucleotide or amino acid sequence. The GESS v2 helps users to identify SNVs or SARS-CoV-2 lineages enriched in countries of user's interest and show the migration path of a selected lineage on a world map during specific time periods chosen by the users. In addition, the GESS v2 can recognize the dynamic variations of newly emerging SNVs in each month to help users monitor SNVs, which will potentially become dominant soon. More importantly, multiple sets of analyzed results about SNVs can be downloaded directly from the GESS v2 by which users can conduct their own independent research. With these significant updates, the GESS v2 will continue to serve as a public open platform for researchers to explore SARS-CoV-2 evolutionary patterns from the perspectives of the prevalence and impact of SNVs.

Evaluating the in vitro efficacy of bovine lactoferrin products against SARS-CoV-2 variants of concern

Bovine lactoferrin (bLF), a naturally occurring glycoprotein found in milk, has bioactive characteristics against many microbes, viruses, and other pathogens. Bovine lactoferrin strongly inhibits SARS-CoV-2 infection in vitro through direct entry inhibition and immunomodulatory mechanisms. This study reports on the anti-SARS-CoV-2 efficacy of commercially available bLF and common dairy ingredients in the human lung cell line H1437 using a custom high-content imaging and analysis pipeline. We also show for the first time that bLF has potent efficacy across different viral strains including the South African B.1.351, UK B.1.1.7, Brazilian P.1, and Indian Delta variants. Interestingly, we show that bLF is most potent against the B.1.1.7 variant [half-maximal inhibitory concentration (IC₅₀) = 3.7 µg/mL], suggesting that this strain relies on entry mechanisms that are strongly inhibited by bLF. We also show that one of the major proteolysis products of bLF, lactoferricin B 17-41, has a modest anti-SARS-CoV-2 activity that could add to the clinical significance of this protein for SARS-CoV-2 treatment as lactoferricin is released by pepsin during digestion. Finally, we show that custom chewable lactoferrin tablets formulated in dextrose or sorbitol have equivalent potency to unformulated samples and provide an option for future human clinical trials. Lactoferrin's broad inhibition of SARS-CoV-2 variants in conjunction with the low cost and ease of production make this an exciting clinical candidate for treatment or prevention of SARS-CoV-2 in the future.

Tolerance of Human Fibroblasts to Benfo-Oxythiamine In Vitro

OBJECTIVES

To explore the potential application of B-OT in the aspiration tract.

MATERIALS AND METHODS

We conceived and optimized an in vitro model simulating the mouth-washing process to assess tolerance to B-OT on primary human gingival fibroblasts. Cells derived from 4 unrelated donors were flushed with medium containing drugs of various concentration for one minute twice daily for 3 days.

RESULTS

No effect was seen on the cells up to 1000 µM B-OT. In addition, we treated the cells with B-OT permanently in medium, corresponding to a systemic treatment. No effect was seen by 10 µM B-OT and only a slight reduction (approximately 10%) was seen by 100 µM B-OT.

CONCLUSIONS

Our results suggest good tolerance of oral cells for B-OT, favoring the further development of this antiviral reagent as a mouth-washing solution and nasal spray.

Use of Antivirals in SARS-CoV-2 Infection. Critical Review of the Role of Remdesivir

The aim of this report is to review the literature and shed light on the uncertainties surrounding the use of antiviral agents in general and remdesivir in COVID-19 patients. This review evaluated a battery of antiviral compounds and their effectiveness in the treatment of COVID-19 since the beginning of the pandemic. Remdesivir is the only antiviral approved by the EMA and FDA for the treatment of SARS-CoV-2 infection. This work extensively reviews remdesivir data generated from clinical trials and observational studies, paying attention to the most recent data, and focusing on outcomes to give readers a more comprehensive understanding of the results. This review also discusses the recommendations issued by official bodies during the pandemic in the light of the current knowledge. The use of remdesivir in the treatment of SARS-CoV-2 infection is justified because a virus is the causative agent that triggers the inflammatory responses and its consequences. More trials are needed to improve the management of this disease.

Omicron: What Makes the Latest SARS-CoV-2 Variant of Concern So Concerning?

Emerging strains of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative agent of the coronavirus disease 2019 (COVID-19) pandemic, that show increased transmission fitness and/or immune evasion are classified as "variants of concern" (VOCs). Recently, a SARS-CoV-2 variant first identified in November 2021 in South Africa has been recognized as a fifth VOC, termed "Omicron." What makes this VOC so alarming is the high number of changes, especially in the viral Spike protein, and accumulating evidence for increased transmission efficiency and escape from neutralizing antibodies. In an amazingly short time, the Omicron VOC has outcompeted the previously dominating Delta VOC. However, it seems that the Omicron VOC is overall less pathogenic than other SARS-CoV-2 VOCs. Here, we provide an overview of the mutations in the Omicron genome and the resulting changes in viral proteins compared to other SARS-CoV-2 strains and discuss their potential functional consequences.

Coronavirus Resistance Database (CoV-RDB): SARS-CoV-2 susceptibility to monoclonal antibodies, convalescent plasma, and plasma from vaccinated persons

As novel SARS-CoV-2 variants with different patterns of spike protein mutations have emerged, the susceptibility of these variants to neutralization by antibodies has been rapidly assessed. However, neutralization data are generated using different approaches and are scattered across different publications making it difficult for these data to be located and synthesized. The Stanford Coronavirus Resistance Database (CoV-RDB; https://covdb.stanford.edu) is designed to house comprehensively curated published data on the neutralizing susceptibility of SARS-CoV-2 variants and spike mutations to monoclonal antibodies (mAbs), convalescent plasma (CP), and vaccinee plasma (VP). As of December 31, 2021, CoV-RDB encompassed 257 publications including 91 (35%) containing 9,070 neutralizing mAb susceptibility results, 131 (51%) containing 16,773 neutralizing CP susceptibility results, and 178 (69%) containing 33,540 neutralizing VP results. The database also records which spike mutations are selected during in vitro passage of SARS-CoV-2 in the presence of mAbs and which emerge in persons receiving mAbs as treatment. The CoV-RDB interface interactively displays neutralizing susceptibility data at different levels of granularity by filtering and/or aggregating query results according to one or more experimental conditions. The CoV-RDB website provides a companion sequence analysis program that outputs information about mutations present in a submitted sequence and that also assists users in determining the appropriate mutation-detection thresholds for identifying non-consensus amino acids. The most recent data underlying the CoV-RDB can be downloaded in its entirety from a GitHub repository in a documented machine-readable format.

Inhaled ciclesonide for outpatient treatment of COVID-19 in adults at risk of adverse outcomes: a randomised controlled trial (COVERAGE)

Objectives

To assess the efficacy of inhaled ciclesonide in reducing the risk of adverse outcomes in COVID-19 outpatients at risk of developing severe illness.

Methods

COVERAGE is an open-label, randomized controlled trial. Outpatients with documented COVID-19, risk factors for aggravation, symptoms for ≤7 days, and absence of criteria for hospitalization are randomly allocated to either a control arm or one of several experimental arms, including inhaled ciclesonide. The primary efficacy endpoint is COVID-19 worsening (hospitalization, oxygen therapy at home, or death) by Day 14. Other endpoints are adverse events, maximal follow-up score on the WHO Ordinal Scale for Clinical Improvement, sustained alleviation of symptoms, cure, and RT-PCR and blood parameter evolution at Day 7. The trial's Safety Monitoring Board reviewed the first interim analysis of the ciclesonide arm and recommended halting it for futility. The results of this analysis are reported here.

Results

The analysis involved 217 participants (control 107, ciclesonide 110), including 111 women and 106 men. Their median age was 63 years (interquartile range 59–68), and 157 of 217 (72.4%) had at least one comorbidity. The median time since first symptom was 4 days (interquartile range 3–5). During the 28-day follow-up, 2 participants died (control 2/107 [1.9%], ciclesonide 0), 4 received oxygen therapy at home and were not hospitalized (control 2/107 [1.9%], ciclesonide 2/110 [1.8%]), and 24 were hospitalized (control 10/107 [9.3%], ciclesonide 14/110 [12.7%]). In intent-to-treat analysis of observed data, 26 participants reached the composite primary endpoint by Day 14, including 12 of 106 (11.3%, 95% CI: 6.0%–18.9%) in the control arm and 14 of 106 (13.2%; 95% CI: 7.4–21.2%) in the ciclesonide arm. Secondary outcomes were similar for both arms.

Discussion

Our findings are consistent with the European Medicines Agency's COVID-19 task force statement that there is currently insufficient evidence that inhaled corticosteroids are beneficial for patients with COVID-19.

Understanding the Role of SARS-CoV-2 ORF3a in Viral Pathogenesis and COVID-19

The ongoing SARS-CoV-2 pandemic has shocked the world due to its persistence, COVID-19-related morbidity and mortality, and the high mutability of the virus. One of the major concerns is the emergence of new viral variants that may increase viral transmission and disease severity. In addition to mutations of spike protein, mutations of viral proteins that affect virulence, such as ORF3a, also must be considered. The purpose of this article is to review the current literature on ORF3a, to summarize the molecular actions of SARS-CoV-2 ORF3a, and its role in viral pathogenesis and COVID-19. ORF3a is a polymorphic, multifunctional viral protein that is specific to SARS-CoV/SARS-CoV-2. It was acquired from β-CoV lineage and likely originated from bats through viral evolution. SARS-CoV-2 ORF3a is a viroporin that interferes with ion channel activities in host plasma and endomembranes. It is likely a virion-associated protein that exerts its effect on the viral life cycle during viral entry through endocytosis, endomembrane-associated viral transcription and replication, and viral release through exocytosis. ORF3a induces cellular innate and pro-inflammatory immune responses that can trigger a cytokine storm, especially under hypoxic conditions, by activating NLRP3 inflammasomes, HMGB1, and HIF-1α to promote the production of pro-inflammatory cytokines and chemokines. ORF3a induces cell death through apoptosis, necrosis, and pyroptosis, which leads to tissue damage that affects the severity of COVID-19. ORF3a continues to evolve along with spike and other viral proteins to adapt in the human cellular environment. How the emerging ORF3a mutations alter the function of SARS-CoV-2 ORF3a and its role in viral pathogenesis and COVID-19 is largely unknown. This review provides an in-depth analysis of ORF3a protein's structure, origin, evolution, and mutant variants, and how these characteristics affect its functional role in viral pathogenesis and COVID-19.

Structural and biochemical rationale for enhanced spike protein fitness in delta and kappa SARS-CoV-2 variants

The Delta and Kappa variants of SARS-CoV-2 co-emerged in India in late 2020, with the Delta variant underlying the resurgence of COVID-19, even in countries with high vaccination rates. In this study, we assess structural and biochemical aspects of viral fitness for these two variants using cryo-electron microscopy (cryo-EM), ACE2-binding and antibody neutralization analyses. Both variants demonstrate escape of antibodies targeting the N-terminal domain, an important immune hotspot for neutralizing epitopes. Compared to wild-type and Kappa lineages, Delta variant spike proteins show modest increase in ACE2 affinity, likely due to enhanced electrostatic complementarity at the RBD-ACE2 interface, which we characterize by cryo-EM. Unexpectedly, Kappa variant spike trimers form a structural head-to-head dimer-of-trimers assembly, which we demonstrate is a result of the E484Q mutation and with unknown biological implications. The combination of increased antibody escape and enhanced ACE2 binding provides an explanation, in part, for the rapid global dominance of the Delta variant.

Saville, Mannar et al. provide a structural basis for enhanced antibody evasion and ACE2 binding by the Delta SARS-CoV-2 spike protein. They further identify a head-to-head dimer-of-trimers cryoEM reconstruction unique to the Kappa variant spike.

Targeting SARS-CoV-2 Proteases for COVID-19 Antiviral Development

The emergence of severe acute respiratory syndrome (SARS-CoV-2) in 2019 marked the third occurrence of a highly pathogenic coronavirus in the human population since 2003. As the death toll surpasses 5 million globally and economic losses continue, designing drugs that could curtail infection and disease progression is critical. In the US, three highly effective Food and Drug Administration (FDA)-authorized vaccines are currently available, and Remdesivir is approved for the treatment of hospitalized patients. However, moderate vaccination rates and the sustained evolution of new viral variants necessitate the ongoing search for new antivirals. Several viral proteins have been prioritized as SARS-CoV-2 antiviral drug targets, among them the papain-like protease (PLpro) and the main protease (Mpro). Inhibition of these proteases would target viral replication, viral maturation, and suppression of host innate immune responses. Knowledge of inhibitors and assays for viruses were quickly adopted for SARS-CoV-2 protease research. Potential candidates have been identified to show inhibitory effects against PLpro and Mpro, both in biochemical assays and viral replication in cells. These results encourage further optimizations to improve prophylactic and therapeutic efficacy. In this review, we examine the latest developments of potential small-molecule inhibitors and peptide inhibitors for PLpro and Mpro, and how structural biology greatly facilitates this process.

Considerable escape of SARS-CoV-2 Omicron to antibody neutralization

The SARS-CoV-2 Omicron variant was first identified in November 2021 in Botswana and South Africa^1-3. It has since spread to many countries and is expected to rapidly become dominant worldwide. The lineage is characterized by the presence of around 32 mutations in spike-located mostly in the N-terminal domain and the receptor-binding domain-that may enhance viral fitness and enable antibody evasion. Here we isolated an infectious Omicron virus in Belgium from a traveller returning from Egypt. We examined its sensitivity to nine monoclonal antibodies that have been clinically approved or are in development⁴, and to antibodies present in 115 serum samples from COVID-19 vaccine recipients or individuals who have recovered from COVID-19. Omicron was completely or partially resistant to neutralization by all monoclonal antibodies tested. Sera from recipients of the Pfizer or AstraZeneca vaccine, sampled five months after complete vaccination, barely inhibited Omicron. Sera from COVID-19-convalescent patients collected 6 or 12 months after symptoms displayed low or no neutralizing activity against Omicron. Administration of a booster Pfizer dose as well as vaccination of previously infected individuals generated an anti-Omicron neutralizing response, with titres 6-fold to 23-fold lower against Omicron compared with those against Delta. Thus, Omicron escapes most therapeutic monoclonal antibodies and, to a large extent, vaccine-elicited antibodies. However, Omicron is neutralized by antibodies generated by a booster vaccine dose.

Variant analysis of SARS-CoV-2 strains with phylogenetic analysis and the Coronavirus Antiviral and Resistance Database

Aims: This study determined SARS-CoV-2 variations by phylogenetic and virtual phenotyping analyses. Materials & methods: Strains isolated from 143 COVID-19 cases in Turkey in April 2021 were assessed. Illumina NexteraXT library preparation kits were processed for next-generation ]sequencing. Phylogenetic (neighbor-joining method) and virtual phenotyping analyses (Coronavirus Antiviral and Resistance Database [CoV-RDB] by Stanford University) were used for variant analysis. Results: B.1.1.7-1/2 (n = 103, 72%), B.1.351 (n = 5, 3%) and B.1.525 (n = 1, 1%) were identified among 109 SARS-CoV-2 variations by phylogenetic analysis and B.1.1.7 (n = 95, 66%), B.1.351 (n = 5, 4%), B.1.617 (n = 4, 3%), B.1.525 (n = 2, 1.4%), B.1.526-1 (n = 1, 0.6%) and missense mutations (n = 15, 10%) were reported by CoV-RDB. The two methods were 85% compatible and B.1.1.7 (alpha) was the most frequent SARS-CoV-2 variation in Turkey in April 2021. Conclusion: The Stanford CoV-RDB analysis method appears useful for SARS-CoV-2 lineage surveillance.

Considerable escape of SARS-CoV-2 Omicron to antibody neutralization

The SARS-CoV-2 Omicron variant was first identified in November 2021 in Botswana and South Africa^1-3. It has since then spread to many countries and is expected to rapidly become dominant worldwide. The lineage is characterized by the presence of about 32 mutations in the spike, located mostly in the N-terminal domain (NTD) and the receptor binding domain (RBD), which may enhance viral fitness and allow antibody evasion. Here, we isolated an infectious Omicron virus in Belgium, from a traveller returning from Egypt. We examined its sensitivity to 9 monoclonal antibodies (mAbs) clinically approved or in development⁴, and to antibodies present in 115 sera from COVID-19 vaccine recipients or convalescent individuals. Omicron was totally or partially resistant to neutralization by all mAbs tested. Sera from Pfizer or AstraZeneca vaccine recipients, sampled 5 months after complete vaccination, barely inhibited Omicron. Sera from COVID-19 convalescent patients collected 6 or 12 months post symptoms displayed low or no neutralizing activity against Omicron. Administration of a booster Pfizer dose as well as vaccination of previously infected individuals generated an anti-Omicron neutralizing response, with titers 6 to 23 fold lower against Omicron than against Delta. Thus, Omicron escapes most therapeutic monoclonal antibodies and to a large extent vaccine-elicited antibodies. Omicron remains however neutralized by antibodies generated by a booster vaccine dose.

SARS-CoV-2 Variants and Their Relevant Mutational Profiles: Update Summer 2021

Since the beginning of the coronavirus disease 2019 (COVID-19) pandemic caused by it, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been undergoing a genetic diversification leading to the emergence of new variants. Nevertheless, a clear definition of the genetic signatures underlying the circulating variants is still missing. Here, we provide a comprehensive insight into mutational profiles characterizing each SARS-CoV-2 variant, focusing on spike mutations known to modulate viral infectivity and/or antigenicity. We focused on variants and on specific relevant mutations reported by GISAID, Nextstrain, Outbreak.info, Pango, and Stanford database websites that were associated with any clinical/diagnostic impact, according to published manuscripts. Furthermore, 1,223,338 full-length high-quality SARS-CoV-2 genome sequences were retrieved from GISAID and used to accurately define the specific mutational patterns in each variant. Finally, mutations were mapped on the three-dimensional structure of the SARS-CoV-2 spike protein to assess their localization in the different spike domains. Overall, this review sheds light and assists in defining the genetic signatures characterizing the currently circulating variants and their clinical relevance. IMPORTANCE Since the emergence of SARS-CoV-2, several recurrent mutations, particularly in the spike protein, arose during human-to-human transmission or spillover events between humans and animals, generating distinct worrisome variants of concern (VOCs) or of interest (VOIs), designated as such due to their clinical and diagnostic impacts. Characterizing these variants and their related mutations is important in tracking SAR-CoV-2 evolution and understanding the efficacy of vaccines and therapeutics based on monoclonal antibodies, convalescent-phase sera, and direct antivirals. Our study provides a comprehensive survey of the mutational profiles characterizing the important SARS-CoV-2 variants, focusing on spike mutations and highlighting other protein mutations.

Structural models of SARS-CoV-2 Omicron variant in complex with ACE2 receptor or antibodies suggest altered binding interfaces

There is enormous ongoing interest in characterizing the binding properties of the SARS-CoV-2 Omicron Variant of Concern (VOC) (B.1.1.529), which continues to spread towards potential dominance worldwide. To aid these studies, based on the wealth of available structural information about several SARS-CoV-2 variants in the Protein Data Bank (PDB) and a modeling pipeline we have previously developed for tracking the ongoing global evolution of SARS-CoV-2 proteins, we provide a set of computed structural models (henceforth models) of the Omicron VOC receptor-binding domain (omRBD) bound to its corresponding receptor Angiotensin-Converting Enzyme (ACE2) and a variety of therapeutic entities, including neutralizing and therapeutic antibodies targeting previously-detected viral strains. We generated bound omRBD models using both experimentally-determined structures in the PDB as well as machine learningbased structure predictions as starting points. Examination of ACE2-bound omRBD models reveals an interdigitated multi-residue interaction network formed by omRBD-specific substituted residues (R493, S496, Y501, R498) and ACE2 residues at the interface, which was not present in the original Wuhan-Hu-1 RBD-ACE2 complex. Emergence of this interaction network suggests optimization of a key region of the binding interface, and positive cooperativity among various sites of residue substitutions in omRBD mediating ACE2 binding. Examination of neutralizing antibody complexes for Barnes Class 1 and Class 2 antibodies modeled with omRBD highlights an overall loss of interfacial interactions (with gain of new interactions in rare cases) mediated by substituted residues. Many of these substitutions have previously been found to independently dampen or even ablate antibody binding, and perhaps mediate antibody-mediated neutralization escape ( e.g ., K417N). We observe little compensation of corresponding interaction loss at interfaces when potential escape substitutions occur in combination. A few selected antibodies ( e.g ., Barnes Class 3 S309), however, feature largely unaltered or modestly affected protein-protein interfaces. While we stress that only qualitative insights can be obtained directly from our models at this time, we anticipate that they can provide starting points for more detailed and quantitative computational characterization, and, if needed, redesign of monoclonal antibodies for targeting the Omicron VOC Spike protein. In the broader context, the computational pipeline we developed provides a framework for rapidly and efficiently generating retrospective and prospective models for other novel variants of SARS-CoV-2 bound to entities of virological and therapeutic interest, in the setting of a global pandemic.

Mass spectrometric identification of immunogenic SARS-CoV-2 epitopes and cognate TCRs

Durable protection against COVID-19 infection may be achieved by generating robust T cell responses to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and emerging SARS-CoV-2 variants; for those infected, effective treatments are urgently needed. For these strategies to be successful, accurate identification of T cell epitopes is critical. In this study, we used major histocompatibility complex immune precipitation, acid elution, and tandem mass spectrometry to define the SARS-CoV-2 immunopeptidome for membrane glycoprotein (MGP) and the nonstructural protein. Furthermore, taking advantage of a highly robust endogenous T cell workflow, we verify the immunogenicity of these MS-defined peptides by in vitro generation of MGP and NSP13 peptide-specific T cells and confirm T cell recognition of MGP or NSP13 endogenously expressing cell lines.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections elicit both humoral and cellular immune responses. For the prevention and treatment of COVID-19, the disease caused by SARS-CoV-2, it has become increasingly apparent that T cell responses are equally if not more important than humoral responses in mediating recovery and immune protection. One major challenge in developing T cell–based therapies for infectious and malignant diseases has been the identification of immunogenic epitopes that can elicit a meaningful T cell response. Traditionally, this has been achieved using sophisticated in silico methods to predict putative epitopes deduced from binding affinities. Our studies find that, in contrast to current convention, “immunodominant” SARS-CoV-2 peptides defined by such in silico methods often fail to elicit T cell responses recognizing naturally presented SARS-CoV-2 epitopes. We postulated that immunogenic epitopes for SARS-CoV-2 are best defined empirically by directly analyzing peptides eluted from the naturally processed peptide–major histocompatibility complex (MHC) and then validating immunogenicity by determining whether such peptides can elicit T cells recognizing SARS-CoV-2 antigen-expressing cells. Using a tandem mass spectrometry approach, we identified epitopes derived from not only structural but also nonstructural genes in regions highly conserved among SARS-CoV-2 strains, including recently recognized variants. Finally, there are no reported T cell receptor–engineered T cell technology that can redirect T cell specificity to recognize and kill SARS-CoV-2 target cells. We report here several SARS-CoV-2 epitopes defined by mass spectrometric analysis of MHC-eluted peptides, provide empiric evidence for their immunogenicity, and demonstrate engineered TCR-redirected killing.

ESC: a comprehensive resource for SARS-CoV-2 immune escape variants

Ever since the breakout of COVID-19 disease, ceaseless genomic research to inspect the epidemiology and evolution of the pathogen has been undertaken globally. Large scale viral genome sequencing and analysis have uncovered the functional impact of numerous genetic variants in disease pathogenesis and transmission. Emerging evidence of mutations in spike protein domains escaping antibody neutralization is reported. We have built a database with precise collation of manually curated variants in SARS-CoV-2 from literature with potential escape mechanisms from a range of neutralizing antibodies. This comprehensive repository encompasses a total of 5258 variants accounting for 2068 unique variants tested against 230 antibodies, patient convalescent plasma and vaccine breakthrough events. This resource enables the user to gain access to an extensive annotation of SARS-CoV-2 escape variants which would contribute to exploring and understanding the underlying mechanisms of immune response against the pathogen. The resource is available at http://clingen.igib.res.in/esc/.

Global Prevalence of Adaptive and Prolonged Infections' Mutations in the Receptor-Binding Domain of the SARS-CoV-2 Spike Protein

Several vaccines with varying efficacies have been developed and are currently administered globally to minimize the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Despite having an RNA-dependent RNA polymerase with a proofreading activity, new variants of SARS-CoV-2 are on the rise periodically. Some of the mutations in these variants, especially mutations on the spike protein, aid the virus in transmission, infectivity and host immune evasion. Further, these mutations also reduce the effectiveness of some of the current vaccines and monoclonal antibodies (mAbs). In the present study, using the available 984,769 SARS-CoV-2 nucleotide sequences on the NCBI database from the end of 2019 till 28 July 2021, we have estimated the global prevalence of so-called 'adaptive mutations' and 'mutations identified in the prolonged infections', in the receptor-binding domain (RBD) of the spike (S) protein. Irrespective of the geographical region, in the case of the adaptive mutations, N501Y (48.38%) was found to be the dominant mutation followed by L452R (17.52%), T478K (14.31%), E484K (4.69%), S477N (3.29%), K417T (1.64%), N439K (0.7%) and S494P (0.7%). Other mutations were found to be less prevalent (less than 0.7%). Since the last two months, there has been a massive increase of L452R and T478K mutations (delta variant) in certain areas. In the case of prolonged infections' mutations (long-term SARS-CoV-2 infections), V483A (0.009%) was found to be dominant followed by Q493R (0.009%), while other mutations were found in less than 0.007% of the studied sequences. The data obtained in this study will aid in the development of better infection control policies, thereby curbing the spread of this virus.

Next-Generation Bioinformatics Approaches and Resources for Coronavirus Vaccine Discovery and Development-A Perspective Review

COVID-19 is a contagious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). To fight this pandemic, which has caused a massive death toll around the globe, researchers are putting efforts into developing an effective vaccine against the pathogen. As genome sequencing projects for several coronavirus strains have been completed, a detailed investigation of the functions of the proteins and their 3D structures has gained increasing attention. These high throughput data are a valuable resource for accelerating the emerging field of immuno-informatics, which is primarily aimed toward the identification of potential antigenic epitopes in viral proteins that can be targeted for the development of a vaccine construct eliciting a high immune response. Bioinformatics platforms and various computational tools and databases are also essential for the identification of promising vaccine targets making the best use of genomic resources, for further experimental validation. The present review focuses on the various stages of the vaccine development process and the vaccines available for COVID-19. Additionally, recent advances in genomic platforms and publicly available bioinformatics resources in coronavirus vaccine discovery together with related immunoinformatics databases and advances in technology are discussed.

Reduced sensitivity of SARS-CoV-2 variant Delta to antibody neutralization

The SARS-CoV-2 B.1.617 lineage was identified in October 2020 in India^1-5. Since then, it has become dominant in some regions of India and in the UK, and has spread to many other countries⁶. The lineage includes three main subtypes (B1.617.1, B.1.617.2 and B.1.617.3), which contain diverse mutations in the N-terminal domain (NTD) and the receptor-binding domain (RBD) of the SARS-CoV-2 spike protein that may increase the immune evasion potential of these variants. B.1.617.2-also termed the Delta variant-is believed to spread faster than other variants. Here we isolated an infectious strain of the Delta variant from an individual with COVID-19 who had returned to France from India. We examined the sensitivity of this strain to monoclonal antibodies and to antibodies present in sera from individuals who had recovered from COVID-19 (hereafter referred to as convalescent individuals) or who had received a COVID-19 vaccine, and then compared this strain with other strains of SARS-CoV-2. The Delta variant was resistant to neutralization by some anti-NTD and anti-RBD monoclonal antibodies, including bamlanivimab, and these antibodies showed impaired binding to the spike protein. Sera collected from convalescent individuals up to 12 months after the onset of symptoms were fourfold less potent against the Delta variant relative to the Alpha variant (B.1.1.7). Sera from individuals who had received one dose of the Pfizer or the AstraZeneca vaccine had a barely discernible inhibitory effect on the Delta variant. Administration of two doses of the vaccine generated a neutralizing response in 95% of individuals, with titres three- to fivefold lower against the Delta variant than against the Alpha variant. Thus, the spread of the Delta variant is associated with an escape from antibodies that target non-RBD and RBD epitopes of the spike protein.

Meta-analysis of randomized trials of ivermectin to treat SARS-CoV-2 infection

Ivermectin is an antiparasitic drug being investigated for repurposing against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Ivermectin showed in vitro activity against SARS-COV-2, but only at high concentrations. This meta-analysis investigated ivermectin in 23 randomized clinical trials (3349 patients) identified through systematic searches of PUBMED, EMBASE, MedRxiv, and trial registries. The primary meta-analysis was carried out by excluding studies at a high risk of bias. Ivermectin did not show a statistically significant effect on survival (risk ratio [RR], 0.90; 95% CI, 0.57 to 1.42; P = .66) or hospitalizations (RR, 0.63; 95% CI, 0.36 to 1.11; P = .11). Ivermectin displayed a borderline significant effect on duration of hospitalization in comparison with standard of care (mean difference, –1.14 days; 95% CI, –2.27 to –0.00; P = .05). There was no significant effect of ivermectin on time to clinical recovery (mean difference, –0.57 days; 95% CI, –1.31 to 0.17; P = .13) or binary clinical recovery (RR, 1.19; 95% CI, 0.94 to 1.50; P = .15). Currently, the World Health Organization recommends the use of ivermectin only inside clinical trials. A network of large clinical trials is in progress to validate the results seen to date.

Machine learning techniques applied to the drug design and discovery of new antivirals: a brief look over the past decade

Introduction: Drug design and discovery of new antivirals will always be extremely important in medicinal chemistry, taking into account known and new viral diseases that are yet to come. Although machine learning (ML) have shown to improve predictions on the biological potential of chemicals and accelerate the discovery of drugs over the past decade, new methods and their combinations have improved their performance and established promising perspectives regarding ML in the search for new antivirals.Areas covered: The authors consider some interesting areas that deal with different ML techniques applied to antivirals. Recent innovative studies on ML and antivirals were selected and analyzed in detail. Also, the authors provide a brief look at the past to the present to detect advances and bottlenecks in the area.Expert opinion: From classical ML techniques, it was possible to boost the searches for antivirals. However, from the emergence of new algorithms and the improvement in old approaches, promising results will be achieved every day, as we have observed in the case of SARS-CoV-2. Recent experience has shown that it is possible to use ML to discover new antiviral candidates from virtual screening and drug repurposing.

SARS-CoV-2 RNA-dependent RNA polymerase as a therapeutic target for COVID-19

Introduction: The current SARS-CoV-2 pandemic urgently demands for both prevention and treatment strategies. RNA-dependent RNA-polymerase (RdRp), which has no counterpart in human cells, is an excellent target for drug development. Given the time-consuming process of drug development, repurposing drugs approved for other indications or at least successfully tested in terms of safety and tolerability, is an attractive strategy to rapidly provide an effective medication for severe COVID-19 cases.Areas covered: The currently available data and upcominSg studies on RdRp which can be repurposed to halt SARS-CoV-2 replication, are reviewed.Expert opinion: Drug repurposing and design of novel compounds are proceeding in parallel to provide a quick response and new specific drugs, respectively. Notably, the proofreading SARS-CoV-2 exonuclease activity could limit the potential for drugs designed as immediate chain terminators and favor the development of compounds acting through delayed termination. While vaccination is awaited to curb the SARS-CoV-2 epidemic, even partially effective drugs from repurposing strategies can be of help to treat severe cases of disease. Considering the high conservation of RdRp among coronaviruses, an improved knowledge of its activity in vitro can provide useful information for drug development or drug repurposing to combat SARS-CoV-2 as well as future pandemics.

A SARS-CoV-2 antiviral therapy score card

The COVID-19 pandemic has unleashed an unprecedented effort to identify efficacious treatments for persons infected with SARS-CoV-2. As of September 2020, more than 750 completed, ongoing, or planned clinical trials of drugs intended to inhibit SARS-CoV-2 replication have been registered on the ClinicalTrials.gov or WHO International Clinical Trials Platform websites. Most of the treatments studied in these trials are repurposed licensed or investigational drugs targeting viral proteins or cellular pathways required for virus replication. The use of repurposed compounds is understandable because with the exception of monoclonal antibodies, it will be several months before novel SARS-CoV-2-specific drugs will be available for human testing. This editorial describes those compounds that I believe should be prioritized for clinical testing: i) viral RNA polymerase inhibitors including GS-441524, its prodrug remdesivir, and EIDD-2801; ii) entry inhibitors including monoclonal antibodies, ACE2 molecular decoys, and peptide fusion inhibitors; iii) parenteral and inhalational preparations of interferon β and λ; and iv) inhibitors of host transmembrane protease serine 2 (TMPRSS2), endosomal trafficking, and pyrimidine synthesis. As SARS-CoV-2 is pandemic and as its most severe consequences result from a dysregulated immunological response to infection, the ideal therapies should be inexpensive and should be able to be administered to non-hospitalized persons at the time of their initial diagnosis.