Revealing the structural and molecular interaction landscape of the favipiravir-RTP and SARS-CoV-2 RdRp complex through integrative bioinformatics: Insights for developing potent drugs targeting SARS-CoV-2 and other viruses.

BACKGROUND: The global research community has made considerable progress in therapeutic and vaccine research during the COVID-19 pandemic. Several therapeutics have been repurposed for the treatment of COVID-19. One such compound is, favipiravir, which was approved for the treatment of influenza viruses, including drug-resistant influenza. Despite the limited information on its molecular activity, clinical trials have attempted to determine the effectiveness of favipiravir in patients with mild to moderate COVID-19. Here, we report the structural and molecular interaction landscape of the macromolecular complex of favipiravir-RTP and SARS-CoV-2 RdRp with the RNA chain. METHODS: Integrative bioinformatics was used to reveal the structural and molecular interaction landscapes of two macromolecular complexes retrieved from RCSB PDB. RESULTS: We analyzed the interactive residues, H-bonds, and interaction interfaces to evaluate the structural and molecular interaction landscapes of the two macromolecular complexes. We found seven and six H-bonds in the first and second interaction landscapes, respectively. The maximum bond length is 3.79 Å. In the hydrophobic interactions, five residues (Asp618, Asp760, Thr687, Asp623, and Val557) were associated with the first complex and two residues (Lys73 and Tyr217) were associated with the second complex. The mobilities, collective motion, and B-factor of the two macromolecular complexes were analyzed. Finally, we developed different models, including trees, clusters, and heat maps of antiviral molecules, to evaluate the therapeutic status of favipiravir as an antiviral drug. CONCLUSIONS: The results revealed the structural and molecular interaction landscape of the binding mode of favipiravir with the nsp7-nsp8-nsp12-RNA SARS-CoV-2 RdRp complex. Our findings can help future researchers in understanding the mechanism underlying viral action and guide the design of nucleotide analogs that mimic favipiravir and exhibit greater potency as antiviral drugs against SARS-CoV-2 and other infectious viruses. Thus, our work can help in preparing for future epidemics and pandemics.

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.

Delta variant (B.1.617.2) of SARS-CoV-2: current understanding of infection, transmission, immune escape, and mutational landscape.

The Delta variant is one of the alarming variants of the SARS-CoV-2 virus that have been immensely detrimental and a significant cause of the prolonged pandemic (B.1.617.2). During the SARS-CoV-2 pandemic from December 2020 to October 2021, the Delta variant showed global dominance, and afterwards, the Omicron variant showed global dominance. Delta shows high infectivity rate which accounted for nearly 70% of the cases after December 2020. This review discusses the additional attributes that make the Delta variant so infectious and transmissible. The study also focuses on the significant mutations, namely the L452R and T478K present on the receptor-binding domain of spike (S)-glycoprotein, which confers specific alterations to the Delta variant. Considerably, we have also highlighted other notable factors such as the immune escape, infectivity and re-infectivity, vaccine escape, Ro number, S-glycoprotein stability, cleavage pattern, and its binding affinity with the host cell receptor protein. We have also emphasized clinical manifestations, symptomatology, morbidity, and mortality for the Delta variant compared with other significant SARS-CoV-2 variants. This review will help the researchers to get an elucidative view of the Delta variant to adopt some practical strategies to minimize the escalating spread of the SARS-CoV-2 Delta variant.

Comparative Case Study of Teamwork on Zoom and Gather.Town

Teamwork is a strategy for successful learning. With the Coronavirus outbreak, many universities began to rely on synchronous video conferencing and/or metaverse platforms. This study examines the difference between undergraduate students' perceptions and experiences of teamwork on Zoom and Gather.Town. A mixed-method comparative case study was conducted in which a questionnaire survey was administered to 20 undergraduate students in Korea, followed by in-depth interviews and participant observation;reflective journal writing was also examined. The data were quantitatively and qualitatively analyzed. The results show that the students had a higher perception of teamwork on Gather.Town than on Zoom. Gather.Town was effective because of the sense of presence and mobility of space it afforded, the social presence it facilitated through avatars, empowerment, and openness of emotions, and the differences in the interface and social platform. The findings can aid in the selection of platforms to suit the needs of students and instructors and in the design and implementation of effective teamwork activities on the selected platform.

Therapeutic applications of nanobodies against SARS-CoV-2 and other viral infections: Current update.

In the last two years, the world encountered the SARS-CoV-2 virus, which is still dominating the population due to the absence of a viable treatment. To eradicate the global pandemic, scientists, doctors, and researchers took an exceptionally significant initiative towards the development of effective therapeutics to save many lifes. This review discusses about the single-domain antibodies (sdAbs), also called nanobodies, their structure, and their types against the infections of dreadful SARS-CoV-2 virus. A precise description highlights the nanobodies and their therapeutic application against the other selected viruses. It aims to focus on the extraordinary features of these antibodies compared to the conventional therapeutics like mAbs, convalescent plasma therapy, and vaccines. The stable structure of these nanobodies along with the suitable mechanism of action also confers greater resistance to the evolving variants with numerous mutations. The nanobodies developed against SARS-CoV-2 and its mutant variants have shown the greater neutralization potential than the primitive ones. Engineering of these specialized antibodies by modern biotechnological approaches will surely be more beneficial in treating this COVID-19 pandemic along with certain other viral infections.

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.

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.

B.1.1.7 (Alpha) variant is the most antigenic compared to Wuhan strain, B.1.351, B.1.1.28/triple mutant and B.1.429 variants.

The rapid spread of the SARS-CoV-2 virus and its variants has created a catastrophic impact worldwide. Several variants have emerged, including B.1.351 (Beta), B.1.1.28/triple mutant (P.1), B.1.1.7 (Alpha), and B.1.429 (Epsilon). We performed comparative and comprehensive antigenicity mapping of the total S-glycoprotein using the Wuhan strain and the other variants and identified 9-mer, 15-mer, and 20-mer CTL epitopes through in silico analysis. The study found that 9-mer CTL epitope regions in the B.1.1.7 variant had the highest antigenicity and an average of the three epitope types. Cluster analysis of the 9-mer CTL epitopes depicted one significant cluster at the 70% level with two nodes (KGFNCYFPL and EGFNCYFPL). The phage-displayed peptides showed mimic 9-mer CTL epitopes with three clusters. CD spectra analysis showed the same band pattern of S-glycoprotein of Wuhan strain and all variants other than B.1.429. The developed 3D model of the superantigen (SAg)-like regions found an interaction pattern with the human TCR, indicating that the SAg-like component might interact with the TCR beta chain. The present study identified another partial SAg-like region (ANQFNSAIGKI) from the S-glycoprotein. Future research should examine the molecular mechanism of antigen processing for CD8+ T cells, especially all the variants' antigens of S-glycoprotein.

Altered gut microbiota patterns in COVID-19: Markers for inflammation and disease severity.

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection leads to a severe respiratory illness and alters the gut microbiota, which dynamically interacts with the human immune system. Microbiota alterations include decreased levels of beneficial bacteria and augmentation of opportunistic pathogens. Here, we describe critical factors affecting the microbiota in coronavirus disease 2019 (COVID-19) patients. These include, such as gut microbiota imbalance and gastrointestinal symptoms, the pattern of altered gut microbiota composition in COVID-19 patients, and crosstalk between the microbiome and the gut-lung axis/gut-brain-lung axis. Moreover, we have illustrated the hypoxia state in COVID-19 associated gut microbiota alteration. The role of ACE2 in the digestive system, and control of its expression using the gut microbiota is discussed, highlighting the interactions between the lungs, the gut, and the brain during COVID-19 infection. Similarly, we address the gut microbiota in elderly or co-morbid patients as well as gut microbiota dysbiosis of in severe COVID-19. Several clinical trials to understand the role of probiotics in COVID-19 patients are listed in this review. Augmented inflammation is one of the major driving forces for COVID-19 symptoms and gut microbiome disruption and is associated with disease severity. However, understanding the role of the gut microbiota in immune modulation during SARS-CoV-2 infection may help improve therapeutic strategies for COVID-19 treatment.

Continent-wide evolutionary trends of emerging SARS-CoV-2 variants: dynamic profiles from Alpha to Omicron.

The ongoing SARS-CoV-2 evolution process has generated several variants due to its continuous mutations, making pandemics more critical. The present study illustrates SARS-CoV-2 evolution and its emerging mutations in five directions. First, the significant mutations in the genome and S-glycoprotein were analyzed in different variants. Three linear models were developed with the regression line to depict the mutational load for S-glycoprotein, total genome excluding S-glycoprotein, and whole genome. Second, the continent-wide evolution of SARS-CoV-2 and its variants with their clades and divergence were evaluated. It showed the region-wise evolution of the SARS-CoV-2 variants and their clustering event. The major clades for each variant were identified. One example is clade 21K, a major clade of the Omicron variant. Third, lineage dynamics and comparison between SARS-CoV-2 lineages across different countries are also illustrated, demonstrating dominant variants in various countries over time. Fourth, gene-wise mutation patterns and genetic variability of SARS-CoV-2 variants across various countries are illustrated. High mutation patterns were found in the ORF10, ORF6, S, and low mutation pattern E genes. Finally, emerging AA point mutations (T478K, L452R, N501Y, S477N, E484A, Q498R, and Y505H), their frequencies, and country-wise occurrence were identified, and the highest event of two mutations (T478K and L452R) was observed.

A Detailed Overview of Immune Escape, Antibody Escape, Partial Vaccine Escape of SARS-CoV-2 and Their Emerging Variants With Escape Mutations.

The infective SARS-CoV-2 is more prone to immune escape. Presently, the significant variants of SARS-CoV-2 are emerging in due course of time with substantial mutations, having the immune escape property. Simultaneously, the vaccination drive against this virus is in progress worldwide. However, vaccine evasion has been noted by some of the newly emerging variants. Our review provides an overview of the emerging variants' immune escape and vaccine escape ability. We have illustrated a broad view related to viral evolution, variants, and immune escape ability. Subsequently, different immune escape approaches of SARS-CoV-2 have been discussed. Different innate immune escape strategies adopted by the SARS-CoV-2 has been discussed like, IFN-I production dysregulation, cytokines related immune escape, immune escape associated with dendritic cell function and macrophages, natural killer cells and neutrophils related immune escape, PRRs associated immune evasion, and NLRP3 inflammasome associated immune evasion. Simultaneously we have discussed the significant mutations related to emerging variants and immune escape, such as mutations in the RBD region (N439K, L452R, E484K, N501Y, K444R) and other parts (D614G, P681R) of the S-glycoprotein. Mutations in other locations such as NSP1, NSP3, NSP6, ORF3, and ORF8 have also been discussed. Finally, we have illustrated the emerging variants' partial vaccine (BioNTech/Pfizer mRNA/Oxford-AstraZeneca/BBIBP-CorV/ZF2001/Moderna mRNA/Johnson & Johnson vaccine) escape ability. This review will help gain in-depth knowledge related to immune escape, antibody escape, and partial vaccine escape ability of the virus and assist in controlling the current pandemic and prepare for the next.

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.

Comparative genomics, evolutionary epidemiology, and RBD-hACE2 receptor binding pattern in B.1.1.7 (Alpha) and B.1.617.2 (Delta) related to their pandemic response in UK and India.

BACKGROUND: The massive increase in COVID-19 infection had generated a second wave in India during May-June 2021 with a critical pandemic situation. The Delta variant (B.1.617.2) was a significant factor during the second wave. Conversely, the UK had passed through the crucial phase of the pandemic from November to December 2020 due to B.1.1.7. The study tried to comprehend the pandemic response in the UK and India to the spread of the B.1.1.7 (Alpha, UK) variant and B.1.617.2 (Delta, India) variant. METHODS: This study was performed in three directions to understand the pandemic response of the two emerging variants. First, we served comparative genomics, such as genome sequence submission patterns, mutational landscapes, and structural landscapes of significant mutations (N501Y, D614G, L452R, E484Q, and P681R). Second, we performed evolutionary epidemiology using molecular phylogenetics, scatter plots of the cluster evaluation, country-wise transmission pattern, and frequency pattern. Third, the receptor binding pattern was analyzed using the Wuhan reference strain and the other two variants. RESULTS: The study analyzed the country-wise and region-wise genome sequences and their submission pattern, molecular phylogenetics, scatter plot of the cluster evaluation, country-wise geographical distribution and transmission pattern, frequency pattern, entropy diversity, and mutational landscape of the two variants. The structural pattern was analyzed in the N501Y, D614G L452R, E484Q, and P681R mutations. The study found increased molecular interactivity between hACE2-RBD binding of B.1.1.7 and B.1.617.2 compared to the Wuhan reference strain. Our receptor binding analysis showed a similar indication pattern for hACE2-RBD of these two variants. However, B.1.617.2 offers slightly better stability in the hACE2-RBD binding pattern through MD simulation than B.1.1.7. CONCLUSION: The increased hACE2-RBD binding pattern of B.1.1.7 and B.1.617.2 might help to increase the infectivity compared to the Wuhan reference strain.

A Next-Generation Vaccine Candidate Using Alternative Epitopes to Protect against Wuhan and All Significant Mutant Variants of SARS-CoV-2: An Immunoinformatics Approach.

Newly emerging significant SARS-CoV-2 variants such as B.1.1.7, B.1.351, and B.1.1.28 are the variant of concern (VOC) for the human race. These variants are getting challenging to contain from spreading worldwide. Because of these variants, the second wave has started in various countries and is threatening human civilization. Thus, we require efficient vaccines that can combat all emerging variants of SARS-CoV-2. Therefore, we took the initiative to develop a peptide-based next-generation vaccine using four variants (Wuhan variant, B.1.1.7, B.1.351, and B.1.1.28) that could potentially combat SARS-CoV-2 variants. We applied a series of computational tools, servers, and software to identify the most significant epitopes present on the mutagenic regions of SARS-CoV-2 variants. The immunoinformatics approaches were used to identify common B cell derived T cell epitopes, influencing the host immune system. Consequently, to develop a novel vaccine candidate, the antigenic epitopes were linked with a flexible and stable peptide linker, and the adjuvant was added at the N-terminal end. 3D vaccine candidate structure was refined, and quality was assessed using web servers. The physicochemical properties and safety parameters of the vaccine construct were assessed through bioinformatics and immunoinformatics tools. The molecular docking analysis between TLR4/MD2 and the proposed vaccine candidate demonstrated a satisfactory interaction. The molecular dynamics studies confirmed the stability of the vaccine candidate. Finally, we optimized the proposed vaccine through codon optimization and in silico cloning to study the expression. Our multi-epitopic next-generation peptide vaccine construct can boost immunity against the Wuhan variant and all significant mutant variants of SARS-CoV-2.

Development of SARS-CoV-2 packaged RNA reference material for nucleic acid testing.

Nucleic acid tests to detect the SARS-CoV-2 virus have been performed worldwide since the beginning of the COVID-19 pandemic. For the quality assessment of testing laboratories and the performance evaluation of molecular diagnosis products, reference materials (RMs) are required. In this work, we report the production of a lentiviral SARS-CoV-2 RM containing approximately 12 kilobases of its genome including common diagnostics targets such as RdRp, N, E, and S genes. The RM was measured with multiple assays using two different digital PCR platforms. To measure the homogeneity and stability of the lentiviral SARS-CoV-2 RM, reverse transcription droplet digital PCR (RT-ddPCR) was used with in-house duplex assays. The copy number concentration of each target gene in the extracted RNA solution was then converted to that of the RM solution. Their copy number values are measured to be from 1.5 × 105 to 2.0 × 105 copies/mL. The RM has a between-bottle homogeneity of 4.80-8.23% and is stable at 4 °C for 1 week and at -70 °C for 6 months. The lentiviral SARS-CoV-2 RM closely mimics real samples that undergo identical pre-analytical processes for SARS-CoV-2 molecular testing. By offering accurate reference values for the absolute copy number of viral target genes, the developed RM can be used to improve the reliability of SARS-CoV-2 molecular testing.

Bioengineering of Novel Non-Replicating mRNA (NRM) and Self-Amplifying mRNA (SAM) Vaccine Candidates Against SARS-CoV-2 Using Immunoinformatics Approach.

Presently, the world needs safe and effective vaccines to overcome the COVID-19 pandemic. Our work has focused on formulating two types of mRNA vaccines that differ in capacity to copy themselves inside the cell. These are non-amplifying mRNA (NRM) and self-amplifying mRNA (SAM) vaccines. Both the vaccine candidates encode an engineered viral replicon which can provoke an immune response. Hence we predicted and screened twelve epitopes from the spike glycoprotein of SARS-CoV-2. We used five CTL, four HTL, and three B-cell-activating epitopes to formulate each mRNA vaccine. Molecular docking revealed that these epitopes could combine with HLA molecules that are important for boosting immunogenicity. The B-cell epitopes were adjoined with GPGPG linkers, while CTL and HTL epitopes were linked with KK linkers. The entire protein chain was reverse translated to develop a specific NRM-based vaccine. We incorporate gene encoding replicase in the upstream region of CDS encoding antigen to design the SAM vaccine. Subsequently, signal sequences were added to human mRNA to formulate vaccines. Both vaccine formulations translated to produce the epitopes in host cells, initiate a protective immune cascade, and generate immunogenic memory, which can counter future SARS-CoV-2 viral exposures before the onset of infection.

Understanding Gene Expression and Transcriptome Profiling of COVID-19: An Initiative Towards the Mapping of Protective Immunity Genes Against SARS-CoV-2 Infection.

The COVID-19 pandemic has created an urgent situation throughout the globe. Therefore, it is necessary to identify the differentially expressed genes (DEGs) in COVID-19 patients to understand disease pathogenesis and the genetic factor(s) responsible for inter-individual variability. The DEGs will help understand the disease's potential underlying molecular mechanisms and genetic characteristics, including the regulatory genes associated with immune response elements and protective immunity. This study aimed to determine the DEGs in mild and severe COVID-19 patients versus healthy controls. The Agilent-085982 Arraystar human lncRNA V5 microarray GEO dataset (GSE164805 dataset) was used for this study. We used statistical tools to identify the DEGs. Our 15 human samples dataset was divided into three groups: mild, severe COVID-19 patients and healthy control volunteers. We compared our result with three other published gene expression studies of COVID-19 patients. Along with significant DEGs, we developed an interactome map, a protein-protein interaction (PPI) pattern, a cluster analysis of the PPI network, and pathway enrichment analysis. We also performed the same analyses with the top-ranked genes from the three other COVID-19 gene expression studies. We also identified differentially expressed lncRNA genes and constructed protein-coding DEG-lncRNA co-expression networks. We attempted to identify the regulatory genes related to immune response elements and protective immunity. We prioritized the most significant 29 protein-coding DEGs. Our analyses showed that several DEGs were involved in forming interactome maps, PPI networks, and cluster formation, similar to the results obtained using data from the protein-coding genes from other investigations. Interestingly we found six lncRNAs (TALAM1, DLEU2, and UICLM CASC18, SNHG20, and GNAS) involved in the protein-coding DEG-lncRNA network; which might be served as potential biomarkers for COVID-19 patients. We also identified three regulatory genes from our study and 44 regulatory genes from the other investigations related to immune response elements and protective immunity. We were able to map the regulatory genes associated with immune elements and identify the virogenomic responses involved in protective immunity against SARS-CoV-2 infection during COVID-19 development.

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.