Immune Escape Associated with RBD Omicron Mutations and SARS-CoV-2 Evolution Dynamics

Revealing patterns of SARS-CoV-2 variant emergence and evolution using RBD amplicon sequencing of wastewater

OBJECTIVES

Rapid evolution of SARS-CoV-2 has resulted in the emergence of numerous variants, posing significant challenges to public health surveillance. Clinical genome sequencing, while valuable, has limitations in capturing the full epidemiological dynamics of circulating variants in the general population. This study aimed to monitor the SARS-CoV-2 variant community dynamics and evolution using receptor-binding domain (RBD) amplicon sequencing of wastewater samples.

METHODS

We sequenced wastewater from El Paso, Texas, over 17 months, compared the sequencing data with clinical genome data, and performed biodiversity analysis to reveal SARS-CoV-2 variant dynamics and evolution.

RESULTS

We identified 91 variants and observed waves of dominant variants transitioning from BA.2 to BA.2.12.1, BA.4&5, BQ.1, and XBB.1.5. Comparison with clinical genome sequencing data revealed earlier detection of variants and identification of unreported outbreaks. Our results also showed strong consistency with clinical data for dominant variants at the local, state, and national levels. Alpha diversity analyses revealed significant seasonal variations, with the highest diversity observed in winter. By segmenting the outbreak into lag, growth, stationary, and decline phases, we found higher variant diversity during the lag phase, likely due to lower inter-variant competition preceding outbreak growth.

CONCLUSIONS

Our findings underscore the importance of low transmission periods in facilitating rapid mutation and variant evolution. Our approach, integrating RBD amplicon sequencing with wastewater surveillance, demonstrates effectiveness in tracking viral evolution and understanding variant emergence, thus enhancing public health preparedness.

Leveraging neural networks to correct FoldX free energy estimates

Proteins play a pivotal role in many biological processes, and changes in their amino acid sequences can lead to dysfunction and disease. These changes can affect protein folding or interaction with other biomolecules, such as preventing antibodies from inhibiting a viral infection or causing proteins to misfold. The ability to predict the effects of mutations in proteins is crucial. Although experimental techniques can accurately quantify the effect of mutations on protein folding free energies and protein-protein binding free energies, they are often time-consuming and costly. By contrast, computational techniques offer fast and cost-effective alternatives for estimating free energies, but they typically suffer from lower accuracy. Enhancing the accuracy of computational predictions is therefore of high importance, with the potential to greatly impact fields ranging from drug design to understanding disease mechanisms. One such widely used computational method, FoldX, is capable of rapidly predicting the relative folding stability ( Δ Δ G fold ) for a protein as well as the relative binding affinity ( Δ Δ G bind ) between proteins using a single protein structure as input. However, it can suffer from low accuracy, especially for antibody-antigen systems. In this work, we trained a neural network on FoldX output to enhance its prediction accuracy. We first performed FoldX calculations on the largest datasets available for mutations that affect binding (SKEMPIv2) and folding (ProTherm4) with experimentally measured Δ Δ G . Features were then extracted from the FoldX output files including its prediction for Δ Δ G . We then developed and optimized a neural network framework to predict the difference between FoldX's estimated Δ Δ G and the experimental data, creating a model capable of producing a correction factor. Our approach showed significant improvements in Pearson correlation performance. For single mutations affecting folding, the correlation improved from a baseline of 0.3 to 0.66. In terms of binding, performance increased from 0.37 to 0.61 for single mutations and from 0.52 to 0.81 for double mutations. For epistasis, the correlation for binding affinity (both singles and doubles) improved from 0.19 to 0.59. Our results also indicated that models trained on double mutations enhanced accuracy when predicting higher-order mutations (such as triple or quadruple mutations), whereas models trained on singles did not. This suggests that interaction energy and epistasis effects present in the FoldX output are not fully utilized by FoldX itself. Once trained, these models add minimal computational time but provide a substantial increase in performance, especially for higher-order mutations and epistasis. This makes them a valuable addition to any free energy prediction pipeline using FoldX. Furthermore, we believe this technique can be further optimized and tested for predicting antibody escape, aiding in the efficient development of watch lists.

Lipid nanoparticle encapsulation of a Delta spike-CD40L DNA vaccine improves effectiveness against Omicron challenge in Syrian hamsters

The effectiveness of mRNA vaccines largely depends on their lipid nanoparticle (LNP) component. Herein, we investigate the effectiveness of DLin-KC2-DMA (KC2) and SM-102-based LNPs for the intramuscular delivery of a plasmid encoding B.1.617.2 (Delta) spike fused with CD40 ligand. LNP encapsulation of this CD40L-adjuvanted DNA vaccine with either LNP formulation drastically enhanced antibody responses, enabling neutralization of heterologous Omicron variants. The DNA-LNP formulations provided excellent protection from homologous challenge, reducing viral replication, and preventing histopathological changes in the pulmonary tissues. Moreover, the DNA-LNP vaccines maintained a high level of protection against heterologous Omicron BA.5 challenge despite a reduced neutralizing response. In addition, we observed that DNA-LNP vaccination led to the pulmonary downregulation of interferon signaling, interleukin-12 signaling, and macrophage response pathways following SARS-CoV-2 challenge, shedding some light on the mechanisms underlying the prevention of pulmonary injury. These results highlight the potential combination of molecular adjuvants with LNP-based vaccine delivery to induce greater and broader immune responses capable of preventing inflammatory damage and protecting against emerging variants. These findings could be informative for the future design of both DNA and mRNA vaccines.

A longitudinal study on SARS-CoV-2 seroconversion, reinfection and neutralisation spanning several variant waves and vaccination campaigns, Heinsberg, Germany, April 2020 to November 2022

BackgroundSince its emergence in December 2019, over 700 million people worldwide have been infected with SARS-CoV-2 up to May 2024. While early rollout of mRNA vaccines against COVID-19 has saved many lives, there was increasing immune escape of new virus variants. Longitudinal monitoring of population-wide SARS-CoV-2 antibody responses from regular sample collection irrespective of symptoms provides representative data on infection and seroconversion/seroreversion rates.AimTo examine adaptive and cellular immune responses of a German SARS-CoV-2 outbreak cohort through several waves of infection with different virus variants.MethodsUtilising a 31-month longitudinal seroepidemiological study (n = 1,446; mean age: 50 years, range: 2-103) initiated during the first SARS-CoV-2 superspreading event (February 2020) in Heinsberg, Germany, we analysed acute infection, seroconversion and virus neutralisation at five follow-up visits between October 2020 and November 2022; cellular and cross-protective immunity against SARS-CoV-2 Omicron variants were also examined.ResultsSARS-CoV-2 spike (S)-specific IgAs decreased shortly after infection, while IgGs remained stable. Both increased significantly after vaccination. We predict an 18-month half-life of S IgGs upon infection. Nucleocapsid (N)-specific responses declined over 12 months post-infection but increased (p < 0.0001) during Omicron. Frequencies of SARS-CoV-2-specific TNF-alpha+/IFN-gamma+ CD4+  T-cells declined over 12 months after infection (p < 0.01). SARS-CoV-2 S antibodies and neutralisation titres were highest in triple-vaccinated participants infected between April 2021 and November 2022 compared with infections between April 2020 and January 2021. Cross neutralisation against Omicron BQ.1.18 and XBB.1.5 was very low in all groups.ConclusionInfection and/or vaccination did not provide the population with cross-protection against Omicron variants.

tANCHOR-cell-based assay for monitoring of SARS-CoV-2 neutralizing antibodies rapidly adaptive to various receptor-binding domains

Conventional neutralizing enzyme-linked immunosorbent assay (ELISA) systems for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mimic the protein-protein interaction between angiotensin-converting enzyme 2 (ACE2) and the receptor-binding domain (RBD). However, an easy and rapidly adaptative ELISA-based system for testing neutralizing antibodies against upcoming SARS-CoV-2 variants is urgently needed. In this study, we closed this gap by developing a tANCHOR-cell-based RBD neutralization assay that avoids time-consuming protein expression and purification followed by coating on ELISA plates. This cell-based assay can be rapidly adopted to monitor neutralizing antibodies (NAbs) against upcoming SARS-CoV-2 variants. We show that the results obtained with the tANCHOR-cell-based assay system strongly correlate with commercially available surrogate assays for testing NAbs. Moreover, this technique can directly measure binding between cell-surface-exposed RBDs and soluble ACE2. With this technique, the degree of antibody escape elicited by emerging SARS-CoV-2 variants in current vaccination regimens can be determined rapidly and reliably.

Analysis of SARS-CoV-2 genome evolutionary patterns

The spread of SARS-CoV-2 virus accompanied by public availability of abundant sequence data provides a window for the determination of viral evolutionary patterns. In this study, SARS-CoV-2 genome sequences were collected from seven countries in the period January 2020-December 2022. The sequences were classified into three phases, namely, pre-vaccination, post-vaccination, and recent period. Comparison was performed between these phases based on parameters like mutation rates, selection pressure (dN/dS ratio), and transition to transversion ratios (Ti/Tv). Similar comparisons were performed among SARS-CoV-2 variants. Statistical significance was tested using Graphpad unpaired t-test. The analysis showed an increase in the percent genomic mutation rates post-vaccination and in recent periods across all countries from the pre-vaccination sequences. Mutation rates were highest in NSP3, S, N, and NSP12b before and increased further after vaccination. NSP4 showed the largest change in mutation rates after vaccination. The dN/dS ratios showed purifying selection that shifted toward neutral selection after vaccination. N, ORF8, ORF3a, and ORF10 were under highest positive selection before vaccination. Shift toward neutral selection was driven by E, NSP3, and ORF7a in the after vaccination set. In recent sequences, the largest dN/dS change was observed in E, NSP1, and NSP13. The Ti/Tv ratios decreased with time. C→U and G→U were the most frequent transitions and transversions. However, U→G was the most frequent transversion in recent period. The Omicron variant had the highest genomic mutation rates, while Delta showed the highest dN/dS ratio. Protein-wise dN/dS ratio was also seen to vary across the different variants.IMPORTANCETo the best of our knowledge, there exists no other large-scale study of the genomic and protein-wise mutation patterns during the time course of evolution in different countries. Analyzing the SARS-CoV-2 evolutionary patterns in view of the varying spatial, temporal, and biological signals is important for diagnostics, therapeutics, and pharmacovigilance of SARS-CoV-2.

tANCHOR cell-based ELISA approach as a surrogate for antigen-coated plates to monitor specific IgG directed to the SARS-CoV-2 receptor-binding domain

Enzyme-linked immunosorbent assay (ELISA) systems use plates coated with peptides or expressed and purified proteins to monitor immunoglobulins derived from patient serum. However, there is currently no easy, flexible, and fast adaptive ELISA-based system for testing antibodies directed against new severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants. In this study, we utilized the tANCHOR protein display system that provides a cell surface decorated with the receptor-binding domain (RBD) to monitor specific antibodies derived from SARS-CoV-2 convalescent and vaccinated individuals directed against it. To test sera from vaccinees or convalescent individuals, only the RBD coding sequence needs to be cloned in the tANCHOR vector system and transfected into HeLa cells. Time-consuming protein expression, isolation, and purification followed by coating assay plates are not necessary. With this technique, the immune evasion of new SARS-CoV-2 variants from current vaccination regimes can be examined quickly and reliably.

Effectiveness of bivalent mRNA vaccines against medically attended symptomatic SARS-CoV-2 infection and COVID-19-related hospital admission among SARS-CoV-2-naive and previously infected individuals: a retrospective cohort study

BACKGROUND

Emergence of the SARS-CoV-2 omicron (B.1.1.529) variant with high immune evasion has led to the development and roll-out of bivalent mRNA vaccines targeting original and omicron strains. However, real-world observational data on effectiveness of bivalent vaccines are scarce. We aimed to assess the relative effectiveness of a fourth vaccine dose with the BA.1-adapted or BA.4/BA.5-adapted bivalent vaccines against medically attended symptomatic SARS-CoV-2 infection and COVID-19-related hospital admission among SARS-CoV-2-naive and previously infected individuals in Singapore.

METHODS

We conducted a retrospective cohort study among Singapore residents aged 18 years and older who had received three monovalent mRNA vaccine doses and were eligible for a fourth dose. Data were collected from official databases on COVID-19 cases and vaccinations maintained by the Singapore Ministry of Health. We analysed the incidence of medically attended symptomatic SARS-CoV-2 infection and COVID-19-related hospital admission between Oct 14, 2022, and Jan 31, 2023, by previous infection status and type of fourth vaccine dose received. Inverse probability-weighted Cox regressions were used to estimate hazard ratios (HRs).

FINDINGS

2 749 819 individuals were included in the analysis. For the SARS-CoV-2-naive group, a fourth monovalent vaccine dose did not confer additional protection over three monovalent doses against symptomatic infection (HR 1·09 [95% CI 1·07-1·11]), whereas the bivalent vaccine did provide additional protection (0·18 [0·17-0·19]). Among individuals with previous infection, the HR was 0·87 (95% CI 0·84-0·91) and 0·14 (0·13-0·15) with receipt of the fourth monovalent and bivalent doses, respectively. Against COVID-19-related hospital admission, the bivalent vaccine (HR 0·12 [95% CI 0·08-0·18] in SARS-CoV-2-naive participants and 0·04 [0·01-0·15] in previously infected participants) conferred greater benefit compared with the fourth monovalent dose (0·84 [0·77-0·91] in SARS-CoV-2-naive participants and 0·85 [0·69-1·04] in previously infected participants).

INTERPRETATION

A fourth dose with the bivalent vaccine was substantially more effective against medically attended symptomatic SARS-CoV-2 infection and COVID-19-related hospital admission than four monovalent doses among both SARS-CoV-2-naive and previously infected individuals. Boosters with the bivalent vaccine might be preferred in this omicron-predominant pandemic, regardless of previous infection history.

FUNDING

None.

Structural understanding of SARS-CoV-2 virus entry to host cells

Coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a major global health concern associated with millions of fatalities worldwide. Mutant variants of the virus have further exacerbated COVID-19 mortality and infection rates, emphasizing the urgent need for effective preventive strategies. Understanding the viral infection mechanism is crucial for developing therapeutics and vaccines. The entry of SARS-CoV-2 into host cells is a key step in the infection pathway and has been targeted for drug development. Despite numerous reviews of COVID-19 and the virus, there is a lack of comprehensive reviews focusing on the structural aspects of viral entry. In this review, we analyze structural changes in Spike proteins during the entry process, dividing the entry process into prebinding, receptor binding, proteolytic cleavage, and membrane fusion steps. By understanding the atomic-scale details of viral entry, we can better target the entry step for intervention strategies. We also examine the impacts of mutations in Spike proteins, including the Omicron variant, on viral entry. Structural information provides insights into the effects of mutations and can guide the development of therapeutics and vaccines. Finally, we discuss available structure-based approaches for the development of therapeutics and vaccines. Overall, this review provides a detailed analysis of the structural aspects of SARS-CoV-2 viral entry, highlighting its significance in the development of therapeutics and vaccines against COVID-19. Therefore, our review emphasizes the importance of structural information in combating SARS-CoV-2 infection.

Antibody evasion associated with the RBD significant mutations in several emerging SARS-CoV-2 variants and its subvariants

Since the origin of the wild strain of SARS-CoV-2, several variants have emerged, which were designated as VOC, VOI, and VUM from time to time. The Omicron variant is noted as the recent VOC. After the origin of the Omicron variant on November 2021, several subvariants of Omicron have originated subsequently, like BA.1/2, BA.2.75/2.75.2, BA.4/5, BF.7, BQ.1/1.1, XBB.1/1.5, etc. which are circulated throughout the globe. Scientists reported that antibody escape is a common phenomenon observed in all the previous VOCs, VOIs, including Omicron and its subvariants. The mutations in the NTD (N-terminal domain) and RBD (Receptor-binding domain) of the spike of these variants and subvariants are responsible for antibody escape. At the same time, it has been noted that spike RBD mutations have been increasing in the last few months. This review illustrates significant RBD mutations namely R346T, K417N/T, L452R, N460K E484A/K/Q, and N501Y found in the previous emerging SARS-CoV-2 variants, including Omicron and its subvariants in high frequency and their role in antibody evasion and immune evasion. The review also describes the different classes of nAb responsible for antibody escape in SARS-CoV-2 variants and the molecular perspective of the mutation in nAb escape. It will help the future researchers to develop efficient vaccines which can finally prevent the pandemic.

Evolution of transient RNA structure-RNA polymerase interactions in respiratory RNA virus genomes

RNA viruses are important human pathogens that cause seasonal epidemics and occasional pandemics. Examples are influenza A viruses (IAV) and coronaviruses (CoV). When emerging IAV and CoV spill over to humans, they adapt to evade immune responses and optimize their replication and spread in human cells. In IAV, adaptation occurs in all viral proteins, including the viral ribonucleoprotein (RNP) complex. RNPs consist of a copy of the viral RNA polymerase, a double-helical coil of nucleoprotein, and one of the eight segments of the IAV RNA genome. The RNA segments and their transcripts are partially structured to coordinate the packaging of the viral genome and modulate viral mRNA translation. In addition, RNA structures can affect the efficiency of viral RNA synthesis and the activation of host innate immune response. Here, we investigated if RNA structures that modulate IAV replication processivity, so-called template loops (t-loops), vary during the adaptation of pandemic and emerging IAV to humans. Using cell culture-based replication assays and in silico sequence analyses, we find that the sensitivity of the IAV H3N2 RNA polymerase to t-loops increased between isolates from 1968 and 2017, whereas the total free energy of t-loops in the IAV H3N2 genome was reduced. This reduction is particularly prominent in the PB1 gene. In H1N1 IAV, we find two separate reductions in t-loop free energy, one following the 1918 pandemic and one following the 2009 pandemic. No destabilization of t-loops is observed in the influenza B virus genome, whereas analysis of SARS-CoV-2 isolates reveals destabilization of viral RNA structures. Overall, we propose that a loss of free energy in the RNA genome of emerging respiratory RNA viruses may contribute to the adaption of these viruses to the human population.

Evolution of transient RNA structure-RNA polymerase interactions in respiratory RNA virus genomes

RNA viruses are important human pathogens that cause seasonal epidemics and occasional pandemics. Examples are influenza A viruses (IAV) and coronaviruses (CoV). When emerging IAV and CoV spill over to humans, they adapt to evade immune responses and optimize their replication and spread in human cells. In IAV, adaptation occurs in all viral proteins, including the viral ribonucleoprotein (RNP) complex. RNPs consists of a copy of the viral RNA polymerase, a double-helical coil of nucleoprotein, and one of the eight segments of the IAV RNA genome. The RNA segments and their transcripts are partially structured to coordinate the packaging of the viral genome and modulate viral mRNA translation. In addition, RNA structures can affect the efficiency of viral RNA synthesis and the activation of host innate immune response. Here, we investigated if RNA structures that modulate IAV replication processivity, so called template loops (t-loops), vary during the adaptation of pandemic and emerging IAV to humans. Using cell culture-based replication assays and in silico sequence analyses, we find that the sensitivity of the IAV H3N2 RNA polymerase to t-loops increased between isolates from 1968 and 2017, whereas the total free energy of t-loops in the IAV H3N2 genome was reduced. This reduction is particularly prominent in the PB1 gene. In H1N1 IAV, we find two separate reductions in t-loop free energy, one following the 1918 pandemic and one following the 2009 pandemic. No destabilization of t-loops is observed in the IBV genome, whereas analysis of SARS-CoV-2 isolates reveals destabilization of viral RNA structures. Overall, we propose that a loss of free energy in the RNA genome of emerging respiratory RNA viruses may contribute to the adaption of these viruses to the human population.

A novel mutation-proof, next-generation vaccine to fight against upcoming SARS-CoV-2 variants and subvariants, designed through AI enabled approaches and tools, along with the machine learning based immune simulation: A vaccine breakthrough

Emerging SARS-CoV-2 variants and subvariants are great concerns for their significant mutations, which are also responsible for vaccine escape. Therefore, the study was undertaken to develop a mutation-proof, next-generation vaccine to protect against all upcoming SARS-CoV-2 variants. We used advanced computational and bioinformatics approaches to develop a multi-epitopic vaccine, especially the AI model for mutation selection and machine learning (ML) strategies for immune simulation. AI-enabled and the top-ranked antigenic selection approaches were used to select nine mutations from 835 RBD mutations. We selected twelve common antigenic B cell and T cell epitopes (CTL and HTL) containing the nine RBD mutations and joined them with the adjuvants, PADRE sequence, and suitable linkers. The constructs' binding affinity was confirmed through docking with TLR4/MD2 complex and showed significant binding free energy (-96.67 kcal mol^-1) with positive binding affinity. Similarly, the calculated eigenvalue (2.428517e-05) from the NMA of the complex reveals proper molecular motion and superior residues' flexibility. Immune simulation shows that the candidate can induce a robust immune response. The designed mutation-proof, multi-epitopic vaccine could be a remarkable candidate for upcoming SARS-CoV-2 variants and subvariants. The study method might guide researchers in developing AI-ML and immunoinformatics-based vaccines for infectious disease.

The impact of mutation sets in receptor-binding domain of SARS-CoV-2 variants on the stability of RBD–ACE2 complex

Aim: Bioinformatic analysis of mutation sets in receptor-binding domain (RBD) of currently and previously circulating SARS-CoV-2 variants of concern (VOCs) and interest (VOIs) to assess their ability to bind the ACE2 receptor. Methods: In silico sequence and structure-oriented approaches were used to evaluate the impact of single and multiple mutations. Results: Mutations detected in VOCs and VOIs led to the reduction of binding free energy of the RBD–ACE2 complex, forming additional chemical bonds with ACE2, and to an increase of RBD–ACE2 complex stability. Conclusion: Mutation sets characteristic of SARS-CoV-2 variants have complex effects on the ACE2 receptor-binding affinity associated with amino acid interactions at mutation sites, as well as on the acquisition of other viral adaptive advantages.

Nirmatrelvir Resistance in SARS-CoV-2 Omicron_BA.1 and WA1 Replicons and Escape Strategies

The antiviral component of Paxlovid, nirmatrelvir (NIR), forms a covalent bond with Cys145 of SARS-CoV-2 nsp5. To explore NIR resistance we designed mutations to impair binding of NIR over substrate. Using 12 Omicron (BA.1) and WA.1 SARS-CoV-2 replicons, cell-based complementation and enzymatic assays, we showed that in both strains, E166V imparted high NIR resistance (∼55-fold), with major decrease in WA1 replicon fitness (∼20-fold), but not BA.1 (∼2-fold). WA1 replicon fitness was restored by L50F. These differences may contribute to a potentially lower barrier to resistance in Omicron than WA1. E166V is rare in untreated patients, albeit more prevalent in paxlovid-treated EPIC-HR clinical trial patients. Importantly, NIR-resistant replicons with E166V or E166V/L50F remained susceptible to a) the flexible GC376, and b) PF-00835231, which forms additional interactions. Molecular dynamics simulations show steric clashes between the rigid and bulky NIR t-butyl and β-branched V166 distancing the NIR warhead from its Cys145 target. In contrast, GC376, through "wiggling and jiggling" accommodates V166 and still covalently binds Cys145. PF-00835231 uses its strategically positioned methoxy-indole to form a β-sheet and overcome E166V. Drug design based on strategic flexibility and main chain-targeting may help develop second-generation nsp5-targeting antivirals efficient against NIR-resistant viruses.

On Immunological Studies at Sirius University of Science and Technology

This short report summarizes the results of recent immunological studies performed at new Sirius University of Science and Technology. The report focuses on studying the features of the immune response to vaccination and revaccination against SARS-CoV-2, as well as on a search of potential agents to prevent infection with this virus.

The rapid emergence of multiple sublineages of Omicron (B.1.1.529) variant: Dynamic profiling via molecular phylogenetics and mutational landscape studies

PURPOSE

The recent Omicron (B.1.1.529) variant poses a significant threat to global health. This variant has spread worldwide, and several sublineages have rapidly emerged. Study tried to analyze the microevolution of this variant.

METHODS

We studied the molecular phylogenetics, divergence, geographical distributions, frequencies, risk mutations for antibody affinity, and mutational landscape for Omicron sublineages using in silico analysis and statistical models. The risk mutation of spike for nAb affinity was analyzed and illustrated by statistical plots. Finally, the mutational properties of the spike mutations and their stability were predicted and demonstrated.

RESULTS

First, we studied the microevolutionary Omicron sublineages using molecular phylogenetics. Simultaneously, we revealed divergence events of the Omicron sublineages and observed the lowest minimum divergence of 51 in clade 21K and the highest maximum divergence of 90 in clade 21L. We have demonstrated cluster analyses, geographical distributions, frequencies of Omicron and its sublineages. Finally, we evaluated the mutational landscape of the Omicron sublineages. In this mutational study, we performed a genome-wide analysis of general mutations, mutations in the non-spike genome, and spike mutations of Omicron sublineages. The risk mutation of S-glycoprotein for nAb affinity has been analyzed for Omicron sublineages. Here, we found that some sublineages have all four significant highly destabilizing mutations. Such sublineages are BA.1 (G446S, E484A, T95I, and D614G), BA.2 (H655Y, Q493R, G493S, and D614G), BA.4 (N501Y, Y505H, N969K, and D614G), and BA.2.75 (Q454H, T547K, N764K, D614G and G446S). Finally, from the mutation stability prediction through ΔΔG, we observed that BA.1 and BA.4 had two destabilizing and two stabilizing mutations. Similarly, BA.2, BA.5, and BA.2.12.1 have one destabilizing and three stabilizing mutations. However, all four mutations in BA.2.75 are stabilizing mutations.

CONCLUSIONS

Our molecular phylogenetic studies provided a deeper understanding of the microevolution of sublineages and the creation of Omicron. Similarly, this study might help scientists develop pan-coronavirus vaccines that consider their mutational properties.

(+)-Usnic Acid and Its Derivatives as Inhibitors of a Wide Spectrum of SARS-CoV-2 Viruses

In order to test the antiviral activity, a series of usnic acid derivatives were synthesized, including new, previously undescribed compounds. The activity of the derivatives against three strains of SARS-CoV-2 virus was studied. To understand the mechanism of antiviral action, the inhibitory activity of the main protease of SARS-CoV-2 virus was studied using the developed model as well as the antiviral activity against the pseudoviral system with glycoprotein S of SARS-CoV-2 virus on its surface. It was shown that usnic acid exhibits activity against three strains of SARS-CoV-2 virus: Wuhan, Delta, and Omicron. Compounds 10 and 13 also showed high activity against the three strains. The performed biological studies and molecular modeling allowed us to assume that the derivatives of usnic acid bind in the N-terminal domain of the surface glycoprotein S at the binding site of the hemoglobin decay metabolite.