Forecasting COVID-19 Cases Using n-SARS-CoV-2 Variants

This work proposes a novel Deep Learning-based model to forecast the total number of confirmed COVID-19 cases in four of the worst-hit states of India. Along with statewide restrictions and public holidays, a novel parameter is introduced for training the proposed model, which considers the Alpha, Beta, Delta, and Omicron variants and the degree of their prevalence in each of the four states. Recurrent Neural Network-based Long-Short Term Memory is applied to the custom dataset, with the lowest Mean Absolute Percentage Error being 0.77% for the state of Maharashtra. SHapley Additive exPlanations values are used to examine the significance of the various parameters. The proposed model can be applied to other countries and can include newer variants of the novel coronavirus discovered in the future. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Plant lectins as versatile tools to fight coronavirus outbreaks.

The S protein forming the homotrimeric spikes of pathogenic beta-coronaviruses, such as MERS-CoV, SARS-CoV and SARS-CoV-2, is a highly glycosylated protein containing mainly N-glycans of the complex and high-mannose type, as well as O-glycans. Similarly, the host cell receptors DPP4 for MERS-CoV and ACE2 for SARS-CoV and SARS-CoV-2, also represent N- and O-glycosylated proteins. All these glycoproteins share common glycosylation patterns, suggesting that plant lectins with different carbohydrate-binding specificities could be used as carbohydrate-binding agents for the spikes and their receptors, to combat COVID19 pandemics. The binding of plant lectins to the spikes and their receptors could mask the non-glycosylated receptor binding domain of the virus and the corresponding region of the receptor, thus preventing a proper interaction of the spike proteins with their receptors. In this review, we analyze (1) the ability of plant lectins to interact with the N- and O-glycans present on the spike proteins and their receptors, (2) the in vitro and in vivo anti-COVID19 activity already reported for plant lectins and, (3) the possible ways for delivery of lectins to block the spikes and/or their receptors.

Decoding molecular factors shaping human angiotensin converting enzyme 2 receptor usage by spike glycoprotein in lineage B beta-coronaviruses.

Acquiring the human ACE2 receptor usage trait enables the coronaviruses to spill over to humans. However, the origin of the ACE2 usage trait in coronaviruses is poorly understood. Using a multi-disciplinary approach combining evolutionary bioinformatics and molecular dynamics simulation, we decode the principal driving force behind human ACE2 receptor recognition in coronaviruses. Genomic content, evolutionary divergence, and codon usage bias analysis reveal that SARS-CoV2 is evolutionarily divergent from other human ACE2-user CoVs, indicating that SARS-CoV2 originates from a different lineage. Sequence analysis shows that all the human ACE2-user CoVs contain two insertions in the receptor-binding motif (RBM) that directly interact with ACE2. However, the insertion sequences in SARS-CoV2 are divergent from other ACE2-user CoVs, implicating their different recombination origins. The potential of mean force calculations reveals that the high binding affinity of SARS-CoV2 RBD to human ACE2 is primarily attributed to its ability to form a higher number of hydrogen bonds than the other ACE2-user CoVs. The adaptive branch-site random effects likelihood method identifies positive selection bias across the ACE2 user CoVs lineages. Recombination and selection forces shape the spike evolution in human ACE2-using beta-CoVs to optimize the interfacial hydrogen bonds between RBD and ACE2. However, these evolutionary forces work within the constraints of nucleotide composition, ensuring optimum codon adaptation of the spike (S) gene within the host cell.

Functional Antibodies Against SARS-CoV-2 Receptor Binding Domain Variants with Mutations N501Y or E484K in Human Milk from COVID-19-Vaccinated, -Recovered, and -Unvaccinated Women.

Background: New variants are evolving in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), and receptor binding domain (RBD) mutations have been associated with a higher capacity to evade neutralizing antibodies (NAbs). We aimed at determining the impact of COVID-19 vaccine and infection on human milk antibody titers and activity against the RBD mutations from SARS-CoV-2 variants of concern. Materials and Methods: Milk samples were collected from 19 COVID-19 vaccinated women, 10 women who had a positive COVID-19 PCR test, and 13 unvaccinated women. The titers and NAbs of secretory IgA (SIgA)/IgA, secretory IgM (IgM)/IgM, and IgG against SARS-CoV-2 RBD with mutations N501Y or E484K were measured by using ELISA and a surrogate virus neutralization assay. Results: The titers of human milk IgG against N501Y were higher in the COVID-19 vaccine group than in the no-vaccine group but comparable with the COVID-19 PCR group. Other antibody titers did not differ between the three groups. The titers of SIgA/IgA were higher than those of SIgM/IgM and IgG in all three groups. The titers of SIgM/IgM and the inhibition of NAbs were higher against the mutation E484K than N501Y. Milk NAb did not differ between the three groups, but the inhibition of NAb against binding of the two mutant RBD proteins to their receptor was higher in the COVID-19 vaccine and PCR groups than in milk from prepandemic women. Conclusions: COVID-19 vaccination and exposure of mothers to SARS-CoV-2 influenced the titers and NAbs in breast milk against the variants of concern.

Sequence and structural analysis of COVID-19 E and M proteins with MERS virus E and M proteins-A comparative study.

The outbreak of SARS in 2003, MERS in 2012, and now COVID-19 in 2019 has demonstrated that Coronaviruses are capable of causing primary lethal infections in humans, and the pandemic is now a global concern. The COVID-19 belongs to the beta coronavirus family encoding 29 proteins, of which four are structural, the Spike, Membrane, Envelope, and Nucleocapsid proteins. Here we have analyzed and compared the Membrane (M) and Envelope (E) proteins of COVID-19 and MERS with SARS and Bat viruses. The sequence analysis of conserved regions of both E and M proteins revealed that many regions of COVID-19 are similar to Bat and SARS viruses while the MERS virus showed variations. The essential binding motifs found in SARS appeared in COVID-19. Besides, the M protein of COVID-19 showed a distinct serine phosphorylation site in the C-terminal domain, which looked like a catalytic triad seen in serine proteases. A Dileucine motif occurred many times in the sequence of the M protein of all the four viruses compared. Concerning the structural part, the COVID-19 E protein showed more similarity to Bat while MERS shared similarity with the SARS virus. The M protein of both COVID-19 and MERS displayed variations in the structure. The interaction between M and E proteins was also studied to know the additional binding regions. Our study highlights the critical motifs and structural regions to be considered for further research to design better inhibitors for the infection caused by these viruses.