A comprehensive analysis of the mutational landscape of the newly emerging Omicron (B.1.1.529) variant and comparison of mutations with VOCs and VOIs.

The Omicron variant is spreading rapidly throughout several countries. Thus, we comprehensively analyzed Omicron's mutational landscape and compared mutations with VOC/VOI. We analyzed SNVs throughout the genome, and AA variants (NSP and SP) in VOC/VOI, including Omicron. We generated heat maps to illustrate the AA variants with high mutation prevalence (> 75% frequency) of Omicron, which demonstrated eight mutations with > 90% prevalence in ORF1a and 29 mutations with > 75% prevalence in S-glycoprotein. A scatter plot for Omicron and VOC/VOI's cluster evaluation was computed. We performed a risk analysis of the antibody-binding risk among four mutations (L452, F490, P681, D614) and observed three mutations (L452R, F490S, D614G) destabilized antibody interactions. Our comparative study evaluated the properties of 28 emerging mutations of the S-glycoprotein of Omicron, and the ΔΔG values. Our results showed K417N with minimum and Q954H with maximum ΔΔG value. Furthermore, six important RBD mutations (G339D, S371L, N440K, G446S, T478K, Q498R) were chosen for comprehensive analysis for stabilizing/destabilizing properties and molecular flexibility. The G339D, S371L, N440K, and T478K were noted as stable mutations with 0.019 kcal/mol, 0.127 kcal/mol, 0.064 kcal/mol, and 1.009 kcal/mol. While, G446S and Q498R mutations showed destabilizing results. Simultaneously, among six RBD mutations, G339D, G446S, and Q498R mutations increased the molecular flexibility of S-glycoprotein. This study depicts the comparative mutational pattern of Omicron and other VOC/VOI, which will help researchers to design and deploy novel vaccines and therapeutic antibodies to fight against VOC/VOI, including Omicron.

Integrative Bioinformatics Approaches Indicate a Particular Pattern of Some SARS-CoV-2 and Non-SARS-CoV-2 Proteins.

Pattern recognition plays a critical role in integrative bioinformatics to determine the structural patterns of proteins of viruses such as SARS-CoV-2. This study identifies the pattern of SARS-CoV-2 proteins to depict the structure-function relationships of the protein alphabets of SARS-CoV-2 and COVID-19. The assembly enumeration algorithm, Anisotropic Network Model, Gaussian Network Model, Markovian Stochastic Model, and image comparison protein-like alphabets were used. The distance score was the lowest with 22 for "I" and highest with 40 for "9". For post-processing and decision, two protein alphabets "C" (PDB ID: 6XC3) and "S" (PDB ID: 7OYG) were evaluated to understand the structural, functional, and evolutionary relationships, and we found uniqueness in the functionality of proteins. Here, models were constructed using "SARS-CoV-2 proteins" (12 numbers) and "non-SARS-CoV-2 proteins" (14 numbers) to create two words, "SARS-CoV-2" and "COVID-19". Similarly, we developed two slogans: "Vaccinate the world against COVID-19" and "Say no to SARS-CoV-2", which were made with the proteins structure. It might generate vaccine-related interest to broad reader categories. Finally, the evolutionary process appears to enhance the protein structure smoothly to provide suitable functionality shaped by natural selection.

Structural Landscape of nsp Coding Genomic Regions of SARS-CoV-2-ssRNA Genome: A Structural Genomics Approach Toward Identification of Druggable Genome, Ligand-Binding Pockets, and Structure-Based Druggability.

SARS-CoV-2 has a single-stranded RNA genome (+ssRNA), and synthesizes structural and non-structural proteins (nsps). All 16 nsp are synthesized from the ORF1a, and ORF1b regions associated with different life cycle preprocesses, including replication. The regions of ORF1a synthesizes nsp1 to 11, and ORF1b synthesizes nsp12 to 16. In this paper, we have predicted the secondary structure conformations, entropy & mountain plots, RNA secondary structure in a linear fashion, and 3D structure of nsp coding genes of the SARS-CoV-2 genome. We have also analyzed the A, T, G, C, A+T, and G+C contents, GC-profiling of these genes, showing the range of the GC content from 34.23 to 48.52%. We have observed that the GC-profile value of the nsp coding genomic regions was less (about 0.375) compared to the whole genome (about 0.38). Additionally, druggable pockets were identified from the secondary structure-guided 3D structural conformations. For secondary structure generation of all the nsp coding genes (nsp 1-16), we used a recent algorithm-based tool (deep learning-based) along with the conventional algorithms (centroid and MFE-based) to develop secondary structural conformations, and we found stem-loop, multi-branch loop, pseudoknot, and the bulge structural components, etc. The 3D model shows bound and unbound forms, branched structures, duplex structures, three-way junctions, four-way junctions, etc. Finally, we identified binding pockets of nsp coding genes which will help as a fundamental resource for future researchers to develop RNA-targeted therapeutics using the druggable genome.

CONTROL DEL COVID-19: UN MODELO EXITOSO DE UNA PEQUEÑA ISLA

A comienzos de diciembre 2019 los medios trajeron noticias de una neumonía infecciosa letal que mataba gente en Wuhan y, de inmediato, los funcionarios sanitarios de Taiwan enviaron una alerta roja a la comunidad de salud. Al regreso activaron el centro de comando epidémico el 20 de enero, notificando a todos los hospitales hacer pruebas rápidas y reportar infecciones sospechosas al CDC. Además, Taiwan ha integrado su base de datos de seguros de salud con la de inmigración/aduanas que escanea todos los billetes de viajeros con variables tales como origen de vuelos, rutas seguidas por dos semanas, historia de viajes, riesgos de infección, etc.

A Paradigm Shift in the Combination Changes of SARS-CoV-2 Variants and Increased Spread of Delta Variant (B.1.617.2) across the World.

Since September 2020, the SARS-CoV-2 variants have gained their dominance worldwide, especially in Kenya, Italy, France, the UK, Turkey, Indonesia, India, Finland, Ireland, Singapore, Denmark, Germany, and Portugal. In this study, we developed a model on the frequency of delta variants across 28 countries (R2= 0.1497), displaying the inheritance of mutations during the generation of the delta variants with 123,526 haplotypes. The country-wise haplotype network showed the distribution of haplotypes in USA (10,174), Denmark (5,637), India (4,089), Germany (2,350), Netherlands (1,899), Sweden (1,791), Italy (1,720), France (1,293), Ireland (1,257), Belgium (1,207), Singapore (1,193), Portugal (1,184) and Spain (1,133). Our analysis shows the highest haplotype in Europe with 84% and the lowest in Australia with 0.00001%. A model of scatter plot was generated with a regression line which provided the estimated rate of mutation, including 24.048 substitutions yearly. Our study concluded that the high global prevalence of the delta variants is due to a high frequency of infectivity, supporting the paradigm shift of the viral variants.

Hybrid immunity against COVID-19 in different countries with a special emphasis on the Indian scenario during the Omicron period.

Hybrid immunity has been accepted as the most robust immunity to fight against SARS-CoV-2. The hybrid immunity against the virus is produced in individuals who have contracted the disease and received the COVID-19 vaccine. This happens due to the cumulative effect of natural and acquired (vaccine) immunity, which provides higher antibody responses compared to natural and vaccine-produced immunity alone. Scientists have noted that it provides about 25 to 100 times higher antibody responses than natural and vaccine-produced immunity alone. Here, we have tried to illustrate the molecular basis of hybrid immunity against various SARS-CoV-2 variants. We have described hybrid immunity under different headings, which are as follows: an overview of hybrid immunity; a comparison between herd immunity and hybrid immunity against SARS-CoV-2; hybrid immunity in different countries; hybrid immunity and different SARS-CoV-2 variants; the molecular basis of hybrid immunity; and hybrid immunity in Indian scenario. India's large population has recovered from SARS-CoV-2, and data shows that over 1000 million of the population received at least one dose of the vaccine. Besides, many infected individuals who have recovered also received at least one dose of the vaccine leading to hybrid immunity with a less severe third wave compared to the first and second waves. Based on the available data, we hypothesize that people's hybrid immunity could be a major cause of the less severe third wave.

D614G mutation and SARS-CoV-2: impact on S-protein structure, function, infectivity, and immunity.

The progression of the COVID-19 pandemic has generated numerous emerging variants of SARS-CoV-2 on a global scale. These variants have gained evolutionary advantages, comprising high virulence and serious infectivity due to multiple spike glycoprotein mutations. As a reason, variants are demonstrating significant abilities to escape the immune responses of the host. The D614G mutation in the S-glycoprotein of SARS-CoV-2 variants has shown the most efficient interaction with the ACE2 receptor of the cells. This explicit mutation at amino acid position 614 (aspartic acid-to-glycine substitution) is the prime cause of infection and re-infection. It changes the conformation of RBD and cleavage patterns S-glycoprotein with higher stability, replication fitness, and fusion efficiencies. Therefore, this review aims to provide several crucial pieces of information associated with the D614 mutational occurrence of SARS-CoV-2 variants and their infectivity patterns. This review will also effectively emphasize the mechanism of action of D614G mutant variants, immune escape, and partial vaccine escape of this virus. Furthermore, the viral characteristic changes leading to the current global pandemic condition have been highlighted. Here, we have tried to illustrate a novel direction for future researchers to develop effective therapeutic approaches and counterweight strategies to minimize the spread of COVID-19.Key points• D614G mutation arises within the S-glycoprotein of significant SARS-CoV-2 variants.• The D614G mutation affects infection, re-infection, cleavage patterns of S-glycoprotein, and replication fitness of SARS-CoV-2 variants.• The D614G mutation influences the immunity and partial vaccine escape.

Omicron variant (B.1.1.529) of SARS-CoV-2: understanding mutations in the genome, S-glycoprotein, and antibody-binding regions.

The Omicron variant has been detected in nearly 150 countries. We analyzed the mutational landscape of Omicron throughout the genome, focusing the S-glycoprotein. We also evaluated mutations in the antibody-binding regions and observed some important mutations overlapping those of previous variants including N501Y, D614G, H655Y, N679K, and P681H. Various new receptor-binding domain mutations were detected, including Q493K, G496S, Q498R, S477N, G466S, N440K, and Y505H. New mutations were found in the NTD (Δ143-145, A67V, T95I, L212I, and Δ211) including one new mutation in fusion peptide (D796Y). There are several mutations in the antibody-binding region including K417N, E484A, Q493K, Q498R, N501Y, and Y505H and several near the antibody-binding region (S477N, T478K, G496S, G446S, and N440K). The impact of mutations in regions important for the affinity between spike proteins and neutralizing antibodies was evaluated. Furthermore, we examined the effect of significant antibody-binding mutations (K417N, T478K, E484A, and N501Y) on antibody affinity, stability to ACE2 interaction, and possibility of amino acid substitution. All the four mutations destabilize the antibody-binding affinity. This study reveals future directions for developing neutralizing antibodies against the Omicron variant.

The Drug Repurposing for COVID-19 Clinical Trials Provide Very Effective Therapeutic Combinations: Lessons Learned From Major Clinical Studies.

SARS-CoV-2 has spread across the globe in no time. In the beginning, people suffered due to the absence of efficacious drugs required to treat severely ill patients. Nevertheless, still, there are no established therapeutic molecules against the SARS-CoV-2. Therefore, repurposing of the drugs started against SARS-CoV-2, due to which several drugs were approved for the treatment of COVID-19 patients. This paper reviewed the treatment regime for COVID-19 through drug repurposing from December 8, 2019 (the day when WHO recognized COVID-19 as a pandemic) until today. We have reviewed all the clinical trials from RECOVERY trials, ACTT-1 and ACTT-2 study group, and other major clinical trial platforms published in highly reputed journals such as NEJM, Lancet, etc. In addition to single-molecule therapy, several combination therapies were also evaluated to understand the treatment of COVID-19 from these significant clinical trials. To date, several lessons have been learned on the therapeutic outcomes for COVID-19. The paper also outlines the experiences gained during the repurposing of therapeutic molecules (hydroxychloroquine, ritonavir/ lopinavir, favipiravir, remdesivir, ivermectin, dexamethasone, camostatmesylate, and heparin), immunotherapeutic molecules (tocilizumab, mavrilimumab, baricitinib, and interferons), combination therapy, and convalescent plasma therapy to treat COVID-19 patients. We summarized that anti-viral therapeutic (remdesivir) and immunotherapeutic (tocilizumab, dexamethasone, and baricitinib) therapy showed some beneficial outcomes. Until March 2021, 4952 clinical trials have been registered in ClinicalTrials.gov toward the drug and vaccine development for COVID-19. More than 100 countries have participated in contributing to these clinical trials. Other than the registered clinical trials (medium to large-size), several small-size clinical trials have also been conducted from time to time to evaluate the treatment of COVID-19. Four molecules showed beneficial therapeutic to treat COVID-19 patients. The short-term repurposing of the existing drug may provide a successful outcome for COVID-19 patients. Therefore, more clinical trials can be initiated using potential anti-viral molecules by evaluating in different phases of clinical trials.

D614G mutation eventuates in all VOI and VOC in SARS-CoV-2: Is it part of the positive selection pioneered by Darwin?

Recently, several emerging variants of SARS-CoV-2 have originated from the Wuhan strain and spread throughout the globe within one and a half years. One mutation, D614G, is very prominent in all VOI and VOC in SARS-CoV-2. This mutation might help to increase the viral fitness in all emerging variants where the mutation is present. With the help of this mutation (D614G), the SARS-CoV-2 variants have gained viral fitness to enhance viral replication and increase transmission. This paper attempts to answer the question of whether the mutation (D614G) occurs due to positive selection or not.

SARS-CoV-2 and other human coronaviruses: Mapping of protease recognition sites, antigenic variation of spike protein and their grouping through molecular phylogenetics.

In recent years, a total of seven human pathogenic coronaviruses (HCoVs) strains were identified, i.e., SARS-CoV, SARS-CoV-2, MERS-CoV, HCoV-OC43, HCoV-229E, HCoV-NL63, and HCoV-HKU1. Here, we performed an analysis of the protease recognition sites and antigenic variation of the S-protein of these HCoVs. We showed tissue-specific expression pattern, functions, and a number of recognition sites of proteases in S-proteins from seven strains of HCoVs. In the case of SARS-CoV-2, we found two new protease recognition sites, each of calpain-2, pepsin-A, and caspase-8, and one new protease recognition site each of caspase-6, caspase-3, and furin. Our antigenic mapping study of the S-protein of these HCoVs showed that the SARS-CoV-2 virus strain has the most potent antigenic epitopes (highest antigenicity score with maximum numbers of epitope regions). Additionally, the other six strains of HCoVs show common antigenic epitopes (both B-cell and T-cell), with low antigenicity scores compared to SARS-CoV-2. We suggest that the molecular evolution of structural proteins of human CoV can be classified, such as (i) HCoV-NL63 and HCoV-229E, (ii) SARS-CoV-2, and SARS-CoV and (iii) HCoV-OC43 and HCoV-HKU1. In conclusion, we can presume that our study might help to prepare the interventions for the possible HCoVs outbreaks in the future.

Evolution, Mode of Transmission, and Mutational Landscape of Newly Emerging SARS-CoV-2 Variants.

The recent emergence of multiple variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has become a significant concern for public health worldwide. New variants have been classified either as variants of concern (VOCs) or variants of interest (VOIs) by the CDC (USA) and WHO. The VOCs include lineages such as B.1.1.7 (20I/501Y.V1 variant), P.1 (20J/501Y.V3 variant), B.1.351 (20H/501Y.V2 variant), and B.1.617.2. In contrast, the VOI category includes B.1.525, B.1.526, P.2, and B.1.427/B.1.429. The WHO provided the alert for last two variants (P.2 and B.1.427/B.1.429) and labeled them for further monitoring. As per the WHO, these variants can be reclassified due to their status at a particular time. At the same time, the CDC (USA) has marked these two variants as VOIs up through today. This article analyzes the evolutionary patterns of all these emerging variants, as well as their geographical distributions and transmission patterns, including the circulating frequency, entropy diversity, and mutational event diversity throughout the genomes of all SARS-CoV-2 lineages. The transmission pattern was observed highest in the B.1.1.7 lineage. Our frequency evaluation found that this lineage achieved 100% frequency in early October 2020. We also critically evaluated the above emerging variants mutational landscape and significant spike protein mutations (E484K, K417T/N, N501Y, and D614G) impacting public health. Finally, the effectiveness of vaccines against newly SARS-CoV-2 variants was also analyzed. IMPORTANCE Irrespective of the aggressive vaccination drive, the newly emerging multiple SARS-CoV-2 variants are causing havoc in several countries. As per the CDC (USA) and WHO, the VOCs include the B.1.1.7, P.1, B.1.351, and B.1.617.2 lineages, while the VOIs include the B.1.525, B.1.526, P.2, and B.1.427/B.1.429 lineages. This study analyzed the evolutionary patterns, geographical distributions and transmission patterns, circulating frequency, entropy diversity, and mutational event diversity throughout the genome of significant SARS-CoV-2 lineages. A higher transmission pattern was observed for the B.1.1.7 variant. The study also evaluated the mutational landscape and important spike protein mutations (E484K, K417T/N, N501Y, and D614G) of all of the above variants. Finally, a survey was performed on the efficacy of vaccines against these variants from the previously published literature. The results presented in this article will help design future countrywide pandemic planning strategies for the emerging variants, next-generation vaccine development using alternative wild-type antigens and significant viral antigens, and immediate planning for ongoing vaccination programs worldwide.

SARS-CoV-2 Brazil variants in Latin America: More serious research urgently needed on public health and vaccine protection.

COVID-19 has not only created a pandemic but also affected both economically and socially in all countries. It has further created a socio-economic chaos throughout Latin America. Currently, some new SARS-CoV-2 variants are circulating in Latin America and one among the significant variant belongs to the P.1 lineage (B.1.1.28.1) that has 17 mutations. The essential modifications located in the spike glycoprotein RBD include E484K, K417T and N501Y. Along with the P.1 lineage, P.2 lineage (B.1.1.28.2) has also appeared recently. Details on all the variants are unknown, along with the Brazil variants at this time. Therefore, we call for intensive research to collect more data to understand the variants' virulence and the effects on vaccine efficacy.