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.

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.

Variant-specific deleterious mutations in the SARS-CoV-2 genome reveal immune responses and potentials for prophylactic vaccine development.

Introduction: Coronavirus disease 2019 (COVID-19), caused by SARS-CoV-2, has had a disastrous effect worldwide during the previous three years due to widespread infections with SARS-CoV-2 and its emerging variations. More than 674 million confirmed cases and over 6.7 million deaths have been attributed to successive waves of SARS-CoV-2 infections as of 29th January 2023. Similar to other RNA viruses, SARS-CoV-2 is more susceptible to genetic evolution and spontaneous mutations over time, resulting in the continual emergence of variants with distinct characteristics. Spontaneous mutations of SARS-CoV-2 variants increase its transmissibility, virulence, and disease severity and diminish the efficacy of therapeutics and vaccines, resulting in vaccine-breakthrough infections and re-infection, leading to high mortality and morbidity rates. Materials and methods: In this study, we evaluated 10,531 whole genome sequences of all reported variants globally through a computational approach to assess the spread and emergence of the mutations in the SARS-CoV-2 genome. The available data sources of NextCladeCLI 2.3.0 (https://clades.nextstrain.org/) and NextStrain (https://nextstrain.org/) were searched for tracking SARS-CoV-2 mutations, analysed using the PROVEAN, Polyphen-2, and Predict SNP mutational analysis tools and validated by Machine Learning models. Result: Compared to the Wuhan-Hu-1 reference strain NC 045512.2, genome-wide annotations showed 16,954 mutations in the SARS-CoV-2 genome. We determined that the Omicron variant had 6,307 mutations (retrieved sequence:1947), including 67.8% unique mutations, more than any other variant evaluated in this study. The spike protein of the Omicron variant harboured 876 mutations, including 443 deleterious mutations. Among these deleterious mutations, 187 were common and 256 were unique non-synonymous mutations. In contrast, after analysing 1,884 sequences of the Delta variant, we discovered 4,468 mutations, of which 66% were unique, and not previously reported in other variants. Mutations affecting spike proteins are mostly found in RBD regions for Omicron, whereas most of the Delta variant mutations drawn to focus on amino acid regions ranging from 911 to 924 in the context of epitope prediction (B cell & T cell) and mutational stability impact analysis protruding that Omicron is more transmissible. Discussion: The pathogenesis of the Omicron variant could be prevented if the deleterious and persistent unique immunosuppressive mutations can be targeted for vaccination or small-molecule inhibitor designing. Thus, our findings will help researchers monitor and track the continuously evolving nature of SARS-CoV-2 strains, the associated genetic variants, and their implications for developing effective control and prophylaxis strategies.

SARS-CoV-2 Vaccines, Vaccine Development Technologies, and Significant Efforts in Vaccine Development during the Pandemic: The Lessons Learned Might Help to Fight against the Next Pandemic.

We are currently approaching three years since the beginning of the coronavirus disease 2019 (COVID-19) pandemic. SARS-CoV-2 has caused extensive disruptions in everyday life, public health, and the global economy. Thus far, the vaccine has worked better than expected against the virus. During the pandemic, we experienced several things, such as the virus and its pathogenesis, clinical manifestations, and treatments; emerging variants; different vaccines; and the vaccine development processes. This review describes how each vaccine has been developed and approved with the help of modern technology. We also discuss critical milestones during the vaccine development process. Several lessons were learned from different countries during the two years of vaccine research, development, clinical trials, and vaccination. The lessons learned during the vaccine development process will help to fight the next pandemic.

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.

Knowledge, Attitude and Worry in the Kurdistan Region of Iraq during the Mpox (Monkeypox) Outbreak in 2022: An Online Cross-Sectional Study.

The rapid spread of monkeypox (mpox) has been declared as a public health emergency of international concern (PHEIC). The present study aimed to assess the knowledge, attitude, and worry levels of the general population in the Kurdistan region of Iraq regarding the ongoing mpox multi-country outbreak. An online cross-sectional survey was conducted between 27-30 July 2022, using a convenience sampling method. The questionnaire was adapted from previous studies addressing the same topic. The independent Student's t-test, one-way ANOVA, and logistic regression were used to assess possible factors associated with knowledge, attitude, and worry toward mpox. A total of 510 respondents were included in the final analysis. The participants showed a moderate level of mpox knowledge, a neutral attitude towards mpox, and a relatively moderate worry level. The logistic regression analysis showed that age, gender, marital status, religion, level of education, and place of residence were associated with mpox knowledge; however, the significant variables in the multivariate regression analysis were gender, religion, level of education, and residential area. Gender and residential area were associated with attitudes toward mpox; however, the significant variables in the multivariate regression analysis were gender and residential areas. The worry toward mpox was influenced by gender, marital status, religion, and place of residence, yet the significant variables in the multivariate regression analysis were gender, religion, educational level, and residential area. In conclusion, the Kurdish population had moderate knowledge, a neutral attitude, and a moderate level of worry about mpox. Considering the continuous rapid rise in mpox cases in several countries, and its possible risk as pandemic amid the ongoing COVID-19 pandemic, proactive control measures, adequate disease prevention strategies, and preparedness plans need to be formulated and immediately implemented to tackle the appearance of fears among people, and to safeguard the mental health of the public.

A Detailed Overview of SARS-CoV-2 Omicron: Its Sub-Variants, Mutations and Pathophysiology, Clinical Characteristics, Immunological Landscape, Immune Escape, and Therapies.

The COVID-19 pandemic has created significant concern for everyone. Recent data from many worldwide reports suggest that most infections are caused by the Omicron variant and its sub-lineages, dominating all the previously emerged variants. The numerous mutations in Omicron's viral genome and its sub-lineages attribute it a larger amount of viral fitness, owing to the alteration of the transmission and pathophysiology of the virus. With a rapid change to the viral structure, Omicron and its sub-variants, namely BA.1, BA.2, BA.3, BA.4, and BA.5, dominate the community with an ability to escape the neutralization efficiency induced by prior vaccination or infections. Similarly, several recombinant sub-variants of Omicron, namely XBB, XBD, and XBF, etc., have emerged, which a better understanding. This review mainly entails the changes to Omicron and its sub-lineages due to it having a higher number of mutations. The binding affinity, cellular entry, disease severity, infection rates, and most importantly, the immune evading potential of them are discussed in this review. A comparative analysis of the Delta variant and the other dominating variants that evolved before Omicron gives the readers an in-depth understanding of the landscape of Omicron's transmission and infection. Furthermore, this review discusses the range of neutralization abilities possessed by several approved antiviral therapeutic molecules and neutralizing antibodies which are functional against Omicron and its sub-variants. The rapid evolution of the sub-variants is causing infections, but the broader aspect of their transmission and neutralization has not been explored. Thus, the scientific community should adopt an elucidative approach to obtain a clear idea about the recently emerged sub-variants, including the recombinant variants, so that effective neutralization with vaccines and drugs can be achieved. This, in turn, will lead to a drop in the number of cases and, finally, an end to the pandemic.

Global emerging Omicron variant of SARS-CoV-2: Impacts, challenges and strategies.

Newly emerging variants of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are continuously posing high global public health concerns and panic resulting in waves of coronavirus disease 2019 (COVID-19) pandemic. Depending on the extent of genomic variations, mutations and adaptation, few of the variants gain the ability to spread quickly across many countries, acquire higher virulency and ability to cause severe disease, morbidity and mortality. These variants have been implicated in lessening the efficacy of the current COVID-19 vaccines and immunotherapies resulting in break-through viral infections in vaccinated individuals and recovered patients. Altogether, these could hinder the protective herd immunity to be achieved through the ongoing progressive COVID-19 vaccination. Currently, the only variant of interest of SARS-CoV-2 is Omicron that was first identified in South Africa. In this review, we present the overview on the emerging SARS-CoV-2 variants with a special focus on the Omicron variant, its lineages and hybrid variants. We discuss the hypotheses of the origin, genetic change and underlying molecular mechanism behind higher transmissibility and immune escape of Omicron variant. Major concerns related to Omicron including the efficacy of the current available immunotherapeutics and vaccines, transmissibility, disease severity, and mortality are discussed. In the last part, challenges and strategies to counter Omicron variant, its lineages and hybrid variants amid the ongoing COVID-19 pandemic are presented.

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.