A comprehensive genomic study, mutation screening, phylogenetic and statistical analysis of SARS-CoV-2 and its variant omicron among different countries

Enhancing public health outcomes with AI-powered clinical surveillance: Precise detection of COVID-19 variants using qPCR and nanopore sequencing

BACKGROUND

We aimed to evaluate the efficacy of integrating the Varia5 multiplex assay (qPCR) and whole genome sequencing (WGS) for monitoring SARS-CoV-2, focusing on their overall performance in identifying various virus variants.

METHODS

This study included 140 naso-pharyngeal swab samples from individuals with suspected COVID-19. We utilized our self-developed Varia5 multiplex assay, which targets five viral genes linked to COVID-19 mutations, in conjunction with comprehensive genomic analysis performed through whole genome sequencing (WGS) using the Oxford Nanopore system. Machine learning was integrated to optimize the qPCR conditions and enhance the detection efficiency.

RESULTS

The Varia5 assay identified the prevalent BA.2.75 variant in 92 samples compared to that in 81 samples detected via WGS. The BA.5.2 variant, indicative of higher viral loads, was identified in 15 samples via Varia5 and in 14 samples via WGS.Furthermore, rare variants, such as BA.2.10, were identified. The mean Ct value was 18.36, with significant viral load differences noted between specific variants.

CONCLUSION

Our findings demonstrate that while WGS offers enhanced sensitivity and specificity for variant detection, qPCR remains crucial for large-scale testing because of its cost and time efficiency. The integrated approach, which combines both techniques, represents a more comprehensive monitoring algorithm that can improve public health strategies against pandemics such as COVID-19.

Advancements in Viral Genomics: Gated Recurrent Unit Modeling of SARS-CoV-2, SARS, MERS, and Ebola viruses

BACKGROUND

Emerging infections have posed persistent threats to humanity throughout history. Rapid and unprecedented anthropogenic, behavioral, and social transformations witnessed in the past century have expedited the emergence of novel pathogens, intensifying their impact on the global human population.

METHODS

This study aimed to comprehensively analyze and compare the genomic sequences of four distinct viruses: SARS-CoV-2, SARS, MERS, and Ebola. Advanced genomic sequencing techniques and a Gated Recurrent Unit-based deep learning model were used to examine the intricate genetic makeup of these viruses. The proposed study sheds light on their evolutionary dynamics, transmission patterns, and pathogenicity and contributes to the development of effective diagnostic and therapeutic interventions.

RESULTS

This model exhibited exceptional performance as evidenced by accuracy values of 99.01%, 98.91%, 98.35%, and 98.04% for SARS-CoV-2, SARS, MERS, and Ebola respectively. Precision values ranged from 98.1% to 98.72%, recall values consistently surpassed 92%, and F1 scores ranged from 95.47% to 96.37%.

CONCLUSIONS

These results underscore the robustness of this model and its potential utility in genomic analysis, paving the way for enhanced understanding, preparedness, and response to emerging viral threats. In the future, this research will focus on creating better diagnostic instruments for the early identification of viral illnesses, developing vaccinations, and tailoring treatments based on the genetic composition and evolutionary patterns of different viruses. This model can be modified to examine a more extensive variety of diseases and recently discovered viruses to predict future outbreaks and their effects on global health.

Molecular characterization, phylogenetic and variation analyses of SARS-CoV-2 strains in India

In the wake of the havoc caused by the COVID-19 pandemic, it is imperative to use the available genomic sequence data to gain insight into the mutational and genomic diversity of SARS-CoV-2. Here we have performed comparative phylogenetic, mutational and genetic diversity analysis on 1962 SARS-CoV-2 genome sequences from seven worst hit Indian states during the third Covid-19 wave, to determine the SARS-CoV-2 strains and mutations in circulation during the third wave and the transmission pattern and disease epidemiology across the states and gain valuable insight into the viral evolution. 6083 Single nucleotide polymorphisms (SNPs) were discovered in the analysis with 93 SNPs common to all states. The genetic relatedness among the statewise multilocus genotypes was visualized by plotting a minimum spanning tree based on Bruvo's distance framework. The phylogenetic tree based on Nei's genetic distance showed distinct clades. The AMOVA results indicated that large proportion of the total genetic variation is distributed within the samples, rather than between the samples within each population and between the populations. Our findings provide insight into the SARS-CoV-2 variants and mutations which dominated the third COVID-19 wave in India and thus provide a basis to monitor and further assess these variants and their sub lineages and mutations for their clinical impact and reaction to existing and newly designed drugs and vaccines. The genetic diversity analysis helps in comprehending the viral transmission scenarios across the Indian states so as to enable the State government and researchers in developing state specific prevention measures for future.

Supplementary Information

The online version contains supplementary material available at 10.1007/s13337-024-00878-7.

Analysis of the Spread and Evolution of COVID-19 Mutations in Ecuador Using Open Data

Currently, the analyses of and prediction using COVID-19-related data extracted from patient information repositories compiled by hospitals and health organizations are of paramount importance. These efforts significantly contribute to vaccine development and the formulation of contingency techniques, providing essential tools to prevent resurgence and to effectively manage the spread of the disease. In this context, the present research focuses on analyzing the biological information of the SARS-CoV-2 viral gene sequences and the clinical data of COVID-19-affected patients using publicly accessible data from Ecuador. This involves considering variables such as age, gender, and geographical location to understand the evolution of mutations and their distributions across Ecuadorian provinces. The Cross-Industry Standard Process for Data Mining (CRISP-DM) methodology is applied for data analysis. Various data preprocessing and statistical analysis techniques are employed, including Pearson correlation, the chi-square test, and analysis of variance (ANOVA). Statistical diagrams and charts are used to facilitate a better visualization of the results. The results illuminate the genetic diversity of the virus and its correlation with clinical variables, offering a comprehensive understanding of the dynamics of COVID-19 spread in Ecuador. Critical variables influencing population vulnerability are highlighted, and the findings underscore the significance of mutation monitoring and indicate a need for global expansion of the research area.

Analysis the molecular similarity of least common amino acid sites in ACE2 receptor to predict the potential susceptible species for SARS-CoV-2

SARS-CoV-2 infections in animals have been reported globally. However, the understanding of the complete spectrum of animals susceptible to SARS-CoV-2 remains limited. The virus's dynamic nature and its potential to infect a wide range of animals are crucial considerations for a One Health approach that integrates both human and animal health. This study introduces a bioinformatic approach to predict potential susceptibility to SARS-CoV-2 in both domestic and wild animals. By examining genomic sequencing, we establish phylogenetic relationships between the virus and its potential hosts. We focus on the interaction between the SARS-CoV-2 genome sequence and specific regions of the host species' ACE2 receptor. We analyzed and compared ACE2 receptor sequences from 29 species known to be infected, selecting 10 least common amino acid sites (LCAS) from key binding domains based on similarity patterns. Our analysis included 49 species across primates, carnivores, rodents, and artiodactyls, revealing complete consistency in the LCAS and identifying them as potentially susceptible. We employed the LCAS similarity pattern to predict the likelihood of SARS-CoV-2 infection in unexamined species. This method serves as a valuable screening tool for assessing infection risks in domestic and wild animals, aiding in the prevention of disease outbreaks.

The deleterious variants of N-acetylgalactosamine-6-sulfatase (GalN6S) enzyme trigger Morquio a syndrome by disrupting protein foldings

Lysosomal enzymes degrade cellular macromolecules, while their inactivation causes human hereditary metabolic disorders. Mucopolysaccharidosis IVA (MPS IVA; Moquio A syndrome) is one of the lysosomal storage disorders caused by a defective Galactosamine-6-sulfatase (GalN6S) enzyme. In several populations, disease incidence is elevated due to missense mutations brought on by non-synonymous allelic variation in the GalN6S enzyme. Here, we studied the effect of non-synonymous single nucleotide polymorphism (nsSNPs) on the structural dynamics of the GalN6S enzyme and its binding with N-acetylgalactosamine (GalNAc) using all-atom molecular dynamics simulation and an essential dynamics approach. Consequently, in this study, we have identified three functionally disruptive mutations in domain-I and domain-II, that is, S80L, R90W, and S162F, which presumably contribute to post-translational modifications. The study delineated that both domains work cooperatively, and alteration in domain II (S80L, R90W) leads to conformational changes in the catalytic site in domain-I, while mutation S162F mainly provokes higher residual flexibility of domain II. These results show that these mutations impair the hydrophobic core, implying that Morquio A syndrome is caused by misfolding of the GalN6S enzyme. The results also show the instability of the GalN6S-GalNAc complex upon substitution. Overall, the structural dynamics resulting from point mutations give the molecular rationale for Moquio A syndrome and, more importantly, the Mucopolysaccharidoses (MPS) family of diseases, re-establishing MPS IVA as a protein-folding disease.Communicated by Ramaswamy H. Sarma.

Identification of potential natural products derived from fungus growing termite, inhibiting Pseudomonas aeruginosa quorum sensing protein LasR using molecular docking and molecular dynamics simulation approach

Pseudomonas aeruginosa, the most common opportunistic pathogen, is becoming antibiotic-resistant worldwide. The fate of P. aeruginosa, a multidrug-resistant strain, can be determined by multidrug efflux pumps, enzyme synthesis, outer membrane protein depletion, and target alterations. Microbial niches have long used quorum sensing (QS) to synchronize virulence gene expression. Computational methods can aid in the development of novel P. aeruginosa drug-resistant treatments. The tripartite symbiosis in termites that grow fungus may help special microbes find new antimicrobial drugs. To find anti-quorum sensing natural products that could be used as alternative therapies, a library of 376 fungal-growing termite-associated natural products (NPs) was screened for their physicochemical properties, pharmacokinetics, and drug-likeness. Using GOLD, the top 74 NPs were docked to the QS transcriptional regulator LasR protein. The five lead NPs with the highest gold score and drug-like properties were chosen for a 200-ns molecular dynamics simulation to test the competitive activity of different compounds against negative catechin. Fridamycin and Daidzein had stable conformations, with mean RMSDs of 2.48 and 3.67 Å, respectively, which were similar to Catechin's 3.22 Å. Fridamycin and Daidzein had absolute binding energies of -71.186 and -52.013 kcal/mol, respectively, which were higher than the control's -42.75 kcal/mol. All the compounds within the active site of the LasR protein were kept intact by Trp54, Arg55, Asp67, and Ser123. These findings indicate that termite gut and fungus-associated NPs, specifically Fridamycin and Daidzein, are potent QS antagonists that can be used to treat P. aeruginosa's multidrug resistance.Communicated by Ramaswamy H. Sarma.

Molecular epidemiology of SARS-CoV-2 in Northern South Africa: wastewater surveillance from January 2021 to May 2022

Introduction

Wastewater-based genomic surveillance of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) provides a comprehensive approach to characterize evolutionary patterns and distribution of viral types in a population. This study documents the molecular epidemiology of SARS-CoV-2, in Northern South Africa, from January 2021 to May 2022.

Methodology

A total of 487 wastewater samples were collected from the influent of eight wastewater treatment facilities and tested for SARS-CoV-2 RNA using quantitative reverse transcriptase polymerase chain reaction (qRT-PCR). SARS-CoV-2 positive samples with genome copies/mL ≥1,500 were subjected to allele-specific genotyping (ASG) targeting the Spike protein; 75 SARS-CoV-2 positive samples were subjected to whole genome sequencing (WGS) on the ATOPlex platform. Variants of concern (VoC) and lineages were assigned using the Nextclade and PangoLIN Software. Concordance for VoC between ASG and WGS analyses was determined. Sequence relationship was determined by phylogenetic analysis.

Results

Seventy-five percent (365/487) of the influent samples were positive for SARS-CoV-2 RNA. Delta and Omicron VoC were more predominant at a prevalence of 45 and 32%, respectively, and they were detected as early as January and February 2021, while Beta VoC was least detected at a prevalence of 5%. A total of 11/60 (18%) sequences were assigned lineages and clades only, but not a specific VoC name. Phylogenetic analysis was used to investigate the relationship of these sequences to other study sequences, and further characterize them. Concordance in variant assignment between ASG and WGS was seen in 51.2% of the study sequences. There was more intra-variant diversity among Beta VoC sequences; mutation E484K was absent. Three previously undescribed mutations (A361S, V327I, D427Y) were seen in Delta VoC.

Discussion and Conclusion

The detection of Delta and Omicron VoCs in study sites earlier in the outbreak than has been reported in other regions of South Africa highlights the importance of population-based approaches over individual sample-based approaches in genomic surveillance. Inclusion of non-Spike protein targets could improve the specificity of ASG, since all VoCs share similar Spike protein mutations. Finally, continuous molecular epidemiology with the application of sensitive technologies such as next generation sequencing (NGS) is necessary for the documentation of mutations whose implications when further investigated could enhance diagnostics, and vaccine development efforts.

Phase III, randomized, double-blind, placebo-controlled clinical study: a study on the safety and clinical efficacy of AZVUDINE in moderate COVID-19 patients

Background

In 2019, a highly pathogenic coronavirus named severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) surfaced and resulted in the outbreak of coronavirus disease 2019 (COVID-19). With the aim of finding effective drugs to fight against the disease, several trials have been conducted since COVID-19 can only be considered a treatable disease, from a clinical point of view, after the availability of specific and effective antivirals. AZVUDINE (FNC), initially developed for treating HIV, is a potential treatment for COVID-19 as it has the capability to lower the patient's viral load and promote recovery.

Methods

Volunteers infected with SARS-CoV-2 confirmed by reverse transcription polymerase chain reaction (RT-PCR), with good kidney and liver function, who were not using other antivirals or monoclonal antibodies were eligible. Samples from patients were assessed for viral load every 48 h during treatment using reverse transcription quantitative polymerase chain reaction (RT-qPCR) and droplet digital polymerase chain reaction (ddPCR).

Results

The study's primary outcome measure was the percentage of participants showing an improvement in clinical scores, while the secondary outcome measure was the percentage of participants with a clinical outcome of cure. These measures were used to assess the safety and efficacy of FNC for treating COVID-19. In the analysis of sociodemographic variables, no significant differences were detected between patients in the FNC and the placebo group for race, age group, or sex. The results showed a potential benefit to participants who received FNC during the study, as observed in the shorter hospital stay, shorter negative conversion time of SARS-CoV-2, and a significant reduction in viral load. Furthermore, the reduction in fever and chills were significant at D1, D2, and D3. In this study, a total of 112 adverse events cases were noted, with 105 cases being categorized as non-serious and only 7 cases as serious adverse events.

Conclusion

The pandemic is not being effectively controlled and is causing multiple waves of infection that require extensive medical resources. However, FNC has demonstrated potential to reduce the treatment duration of moderate COVID-19 cases, thereby saving significant medical resources. This makes FNC a promising candidate for COVID-19 treatment.Clinical trial registration: [clinicaltrials.gov], identifier [NCT04668235].

Identification of novel peptide inhibitors for the KRas-G12C variant to prevent oncogenic signaling

Kirsten rat sarcoma viral oncogene homolog (KRas) activating mutations are common in solid tumors, accounting for 90%, 45%, and 35% of pancreatic, colorectal, and lung cancers (LC), respectively. Each year, nearly 150k new cases (both men and women) of KRas-mutated malignancies are reported in the United States. NSCLC (non-small cell lung cancer) accounts for 80% of all LC cases. KRas mutations are found in 15% to 25% of NSCLC patients. The main cause of NSCLC is the KRas-G12C mutation. The drugs Sotorasib and Adagrasib were recently developed to treat advanced NSCLC caused by the KRas-G12C mutation. Most patients do not respond to KRas-G12C inhibitors due to cellular, molecular, and genetic resistance. Because of their safety, efficacy, and selectivity, peptide inhibitors have the potential to treat newly developing KRas mutations. Based on the KRas mutations, peptide inhibitors that are highly selective and specific to individual lung cancers can be rationally designed. The current study uses an alanine and residue scanning approach to design peptide inhibitors for KRas-G12C based on the known peptide. Our findings show that substitution of F3K, G11T, L8C, T14C, K13D, G11S, and G11P considerably enhances the binding affinity of the novel peptides, whereas F3K, G11T, L8C, and T14C peptides have higher stability and favorable binding to the altered peptides. Overall, our study paves the road for the development of potential therapeutic peptidomimetics that target the KRas-G12C complex and may inhibit the KRas and SOS complex from interacting.Communicated by Ramaswamy H. Sarma.

Highly-specific aptamer targeting SARS-CoV-2 S1 protein screened on an automatic integrated microfluidic system for COVID-19 diagnosis

Variants of the severe acute respiratory syndrome coronavirus (SARS-CoV-2) have evolved such that it may be challenging for diagnosis and clinical treatment of the pandemic coronavirus disease-19 (COVID-19). Compared with developed SARS-CoV-2 diagnostic tools recently, aptamers may exhibit some advantages, including high specificity/affinity, longer shelf life (vs. antibodies), and could be easily prepared. Herein an integrated microfluidic system was developed to automatically carry out one novel screening process based on the systematic evolution of ligands by exponential enrichment (SELEX) for screening aptamers specific with SARS-CoV-2. The new screening process started with five rounds of positive selection (with the S1 protein of SARS-CoV-2). In addition, including non-target viruses (influenza A and B), human respiratory tract-related cancer cells (adenocarcinoma human alveolar basal epithelial cells and dysplastic oral keratinocytes), and upper respiratory tract-related infectious bacteria (including methicillin-resistant Staphylococcus aureus, Pseudomonas aeruginosa, Acinetobacter baumannii, and Klebsiella pneumoniae), and human saliva were involved to increase the specificity of the screened aptamer during the negative selection. Totally, all 10 rounds could be completed within 20 h. The dissociation constant of the selected aptamer was determined to be 63.0 nM with S1 protein. Limits of detection for Wuhan and Omicron clinical strains were found to be satisfactory for clinical applications (i.e. 4.80 × 10¹ and 1.95 × 10² copies/mL, respectively). Moreover, the developed aptamer was verified to be capable of capturing inactivated SARS-CoV-2 viruses, eight SARS-CoV-2 pseudo-viruses, and clinical isolates of SARS-CoV-2 viruses. For high-variable emerging viruses, this developed integrated microfluidic system can be used to rapidly select highly-specific aptamers based on the novel SELEX methods to deal with infectious diseases in the future.

Public Anxiety, Attitudes, and Practices towards COVID-19 Infection in the Eastern Province of Saudi Arabia: A Cross-Sectional Study

Coronavirus disease 2019, or COVID-19, still has a terrifying potential due to its continuous genetic variation. Although vaccines have been created, adherence to preventive measures remains a privileged choice to tackle the pandemic. This study aims to investigate the anxiety, attitudes, and practices (KAPs) towards COVID-19 infection in the Eastern Province of Saudi Arabia. In this cross-sectional study, data were collected from 400 participants via an online self-structured questionnaire. Anxiety, attitude, and practice scores were calculated by summing the points of the statements under the corresponding domain multiplied by 100 over 12, 21, or 15, respectively. Chi-square and one-way analysis of variance were used to investigate the relationships between vaccination, anxiety, attitude, practice scores, and demographic characteristics. More than half of the participants were female (58.5%; mean age of 29.5 years; the majority in the age groups of <20 years and 21-30 years). Only 21.5% of the participants were suffering from or previously had chronic diseases. Notably, 22.3% of the male participants were vaccinated (p = 0.000). The old age groups (41-50 years and >50 years) were more vaccinated (16.3% and 24.1%, respectively, p = 0.000), as well as the unemployed (36.4%; p = 0.000). The mean scores of anxiety, attitude, and practice were 66.8, 72.3, and 85.2, respectively. Females had an anxiety score of 68.5% (p = 0.008) and a higher attitude score of 68.5% (p = 0.008). Infected male participants had a lower practice score of 80% (p = 0.038), while females recorded higher practice scores (85.7 ± 11.6). The results highlight the importance of reliable communication from health representatives and legislators in educating the public and promoting their knowledge about non-therapeutic interventions. Efficient intervention approaches are required to fill the gap during the implementation of non-therapeutic measures. Also, it is recommended that awareness programs, during COVID-19 or any other similar pandemics, should be tailored to target Eastern Province inhabitants, especially males.

In Silico Characterization and Analysis of Clinically Significant Variants of Lipase-H (LIPH Gene) Protein Associated with Hypotrichosis

Hypotrichosis is an uncommon type of alopecia (hair loss) characterized by coarse scalp hair caused by the reduced or fully terminated activity of the Lipase-H (LIPH) enzyme. LIPH gene mutations contribute to the development of irregular or non-functional proteins. Because several cellular processes, including cell maturation and proliferation, are inhibited when this enzyme is inactive, the hair follicles become structurally unreliable, undeveloped, and immature. This results in brittle hair, as well as altered hair shaft development and structure. Because of these nsSNPs, the protein's structure and/or function may be altered. Given the difficulty in discovering functional SNPs in genes associated with disease, it is possible to assess potential functional SNPs before conducting broader population investigations. As a result, in our in silico analysis, we separated potentially hazardous nsSNPs of the LIPH gene from benign representatives using a variety of sequencing and architecture-based bioinformatics approaches. Using seven prediction algorithms, 9 out of a total of 215 nsSNPs were shown to be the most likely to cause harm. In order to distinguish between potentially harmful and benign nsSNPs of the LIPH gene, in our in silico investigation, we employed a range of sequence- and architecture-based bioinformatics techniques. Three nsSNPs (W108R, C246S, and H248N) were chosen as potentially harmful. The present findings will likely be helpful in future large population-based studies, as well as in drug discovery, particularly in the creation of personalized medicine, since this study provides an initial thorough investigation of the functional nsSNPs of LIPH.

Elucidation of novel compounds and epitope-based peptide vaccine design against C30 endopeptidase regions of SARS-CoV-2 using immunoinformatics approaches

There has been progressive improvement in immunoinformatics approaches for epitope-based peptide design. Computational-based immune-informatics approaches were applied to identify the epitopes of SARS-CoV-2 to develop vaccines. The accessibility of the SARS-CoV-2 protein surface was analyzed, and hexa-peptide sequences (KTPKYK) were observed having a maximum score of 8.254, located between amino acids 97 and 102, whereas the FSVLAC at amino acids 112 to 117 showed the lowest score of 0.114. The surface flexibility of the target protein ranged from 0.864 to 1.099 having amino acid ranges of 159 to 165 and 118 to 124, respectively, harboring the FCYMHHM and YNGSPSG hepta-peptide sequences. The surface flexibility was predicted, and a 0.864 score was observed from amino acids 159 to 165 with the hepta-peptide (FCYMHHM) sequence. Moreover, the highest score of 1.099 was observed between amino acids 118 and 124 against YNGSPSG. B-cell epitopes and cytotoxic T-lymphocyte (CTL) epitopes were also identified against SARS-CoV-2. In molecular docking analyses, -0.54 to -26.21 kcal/mol global energy was observed against the selected CTL epitopes, exhibiting binding solid energies of -3.33 to -26.36 kcal/mol. Based on optimization, eight epitopes (SEDMLNPNY, GSVGFNIDY, LLEDEFTPF, DYDCVSFCY, GTDLEGNFY, QTFSVLACY, TVNVLAWLY, and TANPKTPKY) showed reliable findings. The study calculated the associated HLA alleles with MHC-I and MHC-II and found that MHC-I epitopes had higher population coverage (0.9019% and 0.5639%) than MHC-II epitopes, which ranged from 58.49% to 34.71% in Italy and China, respectively. The CTL epitopes were docked with antigenic sites and analyzed with MHC-I HLA protein. In addition, virtual screening was conducted using the ZINC database library, which contained 3,447 compounds. The 10 top-ranked scrutinized molecules (ZINC222731806, ZINC077293241, ZINC014880001, ZINC003830427, ZINC030731133, ZINC003932831, ZINC003816514, ZINC004245650, ZINC000057255, and ZINC011592639) exhibited the least binding energy (-8.8 to -7.5 kcal/mol). The molecular dynamics (MD) and immune simulation data suggest that these epitopes could be used to design an effective SARS-CoV-2 vaccine in the form of a peptide-based vaccine. Our identified CTL epitopes have the potential to inhibit SARS-CoV-2 replication.

Inhibition of SARS-CoV2 viral infection with natural antiviral plants constituents: An in-silico approach

Background and Objective

In 2019, a novel coronavirus disease (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) was declared pandemic. Advancement in computational technology has provided rapid and cost-effective techniques to test the efficacy of newer therapeutic agents. This study evaluated some of the potent phytochemicals obtained from AYUSH (Ayurveda, Yoga, Naturopathy, Unani, Siddha, Sowa-Rigpa, and Homeopathy)-listed medicinal plants against SARS-CoV-2 proteins using computational techniques.

Materials and methods

The potential SARS-CoV-2 protein targets were utilized to study the ligand-protein binding characteristics. The bioactive agents were obtained from ashwagandha, liquorice, amla, neem, tinospora, pepper, and stevia. Ivermectin was utilized as a reference agent to compare its efficacy with phytochemicals.

Results

The computational analysis suggested that all the bioactive components from the selected plants possessed negative docking scores (ranging from -6.24 to -10.53). The phytoconstituents were well absorbed, distributed in the body except for the CNS, metabolized by liver enzymes, well cleared from the body, and well tolerated. The data suggest that AYUSH-recommended plants demonstrated therapeutic efficacy against SARS CoV-2 virus infection with significantly reduced toxicity.

Conclusion

The phytoconstituents were found to hinder the early stages of infection, such as absorption and penetration, while ivermectin prevented the passage of genetic material from the cytoplasm to the nucleus. Additional research involving living tissues and clinical trials are suggested to corroborate the computational findings.

Bioinformatic analysis of the S protein of human respiratory coronavirus

The present study aimed to apply bioinformatic methods to analyze the structure of the S protein of human respiratory coronaviruses, including severe respiratory disease syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome coronavirus (MERS-CoV), human coronavirus HKU1 (HCoV-HKU1), and severe respiratory disease syndrome coronavirus type 2 (SARS-CoV-2). We predicted and analyzed the physicochemical properties, hydrophilicity and hydrophobicity, transmembrane regions, signal peptides, phosphorylation and glycosylation sites, epitopes, functional domains, and motifs of the S proteins of human respiratory coronaviruses. All four S proteins contain a transmembrane region, which enables them to bind to host cell surface receptors. All four S proteins contain a signal peptide, phosphorylation sites, glycosylation sites, and epitopes. The predicted phosphorylation sites might mediate S protein activation, the glycosylation sites might affect the cellular orientation of the virus, and the predicted epitopes might have implications for the design of antiviral inhibitors. The S proteins of all four viruses have two structural domains, S1 (C-terminal and N-terminal domains) and S2 (homology region 1 and 2). Our bioinformatic analysis of the structural and functional domains of human respiratory coronavirus S proteins provides a basis for future research to develop broad-spectrum antiviral drugs, vaccines, and antibodies.

The monkeypox diagnosis, treatments and prevention: A review

The world is currently dealing with a second viral outbreak, monkeypox, which has the potential to become an epidemic after the COVID-19 pandemic. People who reside in or close to forest might be exposed indirectly or at a low level, resulting in subclinical disease. However, the disease has lately emerged in shipped African wild mice in the United States. Smallpox can cause similar signs and symptoms to monkeypox, such as malaise, fever, flu-like signs, headache, distinctive rash, and back pain. Because Smallpox has been eliminated, similar symptoms in a monkeypox endemic zone should be treated cautiously. Monkeypox is transmitted to humans primarily via interaction with diseased animals. Infection through inoculation via interaction with skin or scratches and mucosal lesions on the animals is conceivable significantly once the skin barrier is disrupted by scratches, bites, or other disturbances or trauma. Even though it is clinically unclear from other pox-like infections, laboratory diagnosis is essential. There is no approved treatment for human monkeypox virus infection, however, smallpox vaccination can defend counter to the disease. Human sensitivity to monkeypox virus infection has grown after mass vaccination was discontinued in the 1980s. Infection may be prevented by reducing interaction with sick patients or animals and reducing respiratory exposure among people who are infected.

Immunoinformatics design of B and T-cell epitope-based SARS-CoV-2 peptide vaccination

SARS-COV-2 is a virulent respiratory virus, first identified in China (Wuhan) at the end of 2019. Scientists and researchers are trying to find any possible solution to this deadly viral disease. Different drug source agents have been identified, including western medicine, natural products, and traditional Chinese medicine. They have the potential to counteract COVID-19. This virus immediately affects the liver and causes a decrease in oxygen levels. In this study, multiple vacciome approaches were employed for designing a multi-epitope subunit vaccine for battling against SARS-COV-2. Vaccine designing, immunogenicity, allergenic, and physico-chemical assessment were performed by using the vacciome approach. The vaccine design is likely to be antigenic and produce potent interactions with ACE2 and NSP3 receptors. The developed vaccine has also been given to in-silico cloning models and immune response predictions. A total number of 12 CTL and 12 HTL antigenic epitopes were predicted from three selected covid-19 virulent proteins (spike protein, nucleocapsid protein, and membrane proteins, respectively) based on C-terminal cleavage and MHC binding scores. These predicted epitopes were amalgamated by AYY and GPGPG linkers, and a β-defensins adjuvant was inserted into the N-terminus of this vaccine. This analysis shows that the recommended vaccine can produce immune responses against SARS-COV-2. Designing and developing of the mentioned vaccine will require further experimental validation.

Identification of fungus-growing termite-associated halogenated-PKS maduralactomycin a as a potential inhibitor of MurF protein of multidrug-resistant Acinetobacter baumannii

Multidrug-resistant Acinetobacter baumannii infections have become a major public health concern globally. Inhibition of its essential MurF protein has been proposed as a potential target for broad-spectrum drugs. This study aimed to evaluate the potential of a novel ecological niche of 374 fungus-growing termite associated Natural Products (NPs). The molecular docking and computational pharmacokinetics screened four compounds, i.e., Termstrin B, Fridamycin A, Maduralactomycin A, and Natalenamide C, as potential compounds that have higher binding affinities and favourable protein-ligand interactions. The compound Maduralactomycin A induced more stability based on its lowest average RMSD value (2.31 Å) and low standard deviation (0.35) supported by the consistent flexibility and β-factor during the protein's time-dependent motion. While hydrogen bond analysis indicated that Termstrin B has formed the strongest intra-protein interaction, solvent accessibility was in good agreement with Maduralactomycin A compactness. Maduralactomycin A has the strongest binding energy among all the compounds (-348.48 kcal/mol) followed by Termstrin B (-321.19 kcal/mol). Since these findings suggest Maduralactomycin A and Termstrin B as promising candidates for inhibition of MurF protein, the favourable binding energies of Maduralactomycin A make it a more important compound to warrant further investigation. However, experimental validation using animal models and clinical trials is recommended before reaching any final conclusions.

Characterization and phylogenetic analysis of Iranian SARS-CoV-2 genomes: A phylogenomic study

Background and Aim

Characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) based on analyzing the evolution and mutations of viruses is crucial for tracking viral infections, potential mutants, and other pathogens. The purpose was to study the complete sequences of SARS-CoV-2 to reveal genetic distance and mutation rate among different provinces of Iran.

Methods

As of March 2020-April 2021, a total of 131 SARS-CoV-2 whole genome sequences submitted from Tehran and 133 SARS-CoV-2 full-length sequences from 24 cities with high coverage submitted to EpiCoV GISAID database were analyzed to infer clades and mutation annotation compared with the wild-type variant Wuhan-Hu-1.

Results

The results of variant annotation were revealed 11,204 and 9468 distinct genomes were identified among the samples from different cities and Tehran, respectively. The phylogenetic analysis of genomic sequences showed the presence of eight GISAID clades, namely GH, GR, O, GRY, G, GK, L, and GV, and six Nextstrain clades; that is, 19A, 20A, 20B, 20I (alpha, V1), 20H (Beta, V2), and 21I (Delta) in Iran. The GH (GISAID clade), 20A (Nextstrain clade), and B.1 (Pango lineage) were predominant in Iran. Notably, analysis of the spike protein revealed D614G mutation (S_D614G) in 56% of the sequences. Also, the delta variant of the coronavirus, the super-infectious strain that was first identified among the sequences submitted from the southern cities of the country such as Zahedan, Yazd and Bushehr, and most likely from these places to other cities of Iran as well has expanded.

Conclusions

Our results indicate that most of the circulated viruses in Iran in the early time of the pandemic had collected in eight GISAID clades. Therefore, a continuous and extensive genome sequence analysis would be necessary to understand the genomic epidemiology of SARS-CoV-2 in Iran.

Smart Nanostructured Materials for SARS-CoV-2 and Variants Prevention, Biosensing and Vaccination

The coronavirus disease 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has raised great concerns about human health globally. At the current stage, prevention and vaccination are still the most efficient ways to slow down the pandemic and to treat SARS-CoV-2 in various aspects. In this review, we summarize current progress and research activities in developing smart nanostructured materials for COVID-19 prevention, sensing, and vaccination. A few established concepts to prevent the spreading of SARS-CoV-2 and the variants of concerns (VOCs) are firstly reviewed, which emphasizes the importance of smart nanostructures in cutting the virus spreading chains. In the second part, we focus our discussion on the development of stimuli-responsive nanostructures for high-performance biosensing and detection of SARS-CoV-2 and VOCs. The use of nanostructures in developing effective and reliable vaccines for SARS-CoV-2 and VOCs will be introduced in the following section. In the conclusion, we summarize the current research focus on smart nanostructured materials for SARS-CoV-2 treatment. Some existing challenges are also provided, which need continuous efforts in creating smart nanostructured materials for coronavirus biosensing, treatment, and vaccination.

Structural Evaluation and Conformational Dynamics of ZNF141T474I Mutation Provoking Postaxial Polydactyly Type A

Postaxial Polydactyly (PAP) is a congenital disorder of limb abnormalities characterized by posterior extra digits. Mutations in the N-terminal region of the Zinc finger protein 141 (ZNF141) gene were recently linked with PAP type A. Zinc finger proteins exhibit similarity at their N-terminal regions due to C2-H2 type Zinc finger domains, but their functional preferences vary significantly by the binding patterns of DNA. Methods: This study delineates the pathogenic association, miss-fold aggregation, and conformational paradigm of a missense variant (c.1420C > T; p.T474I) in ZNF141 gene segregating PAP through a molecular dynamics simulations approach. Results: In ZNF141 protein, helices play a crucial role by attaching three specific target DNA base pairs. In ZNF141T474I protein, H1, H3, and H6 helices attain more flexibility by acquiring loop conformation. The outward disposition of the proximal portion of H9-helix in mutant protein occurs due to the loss of prior beta-hairpins at the C terminal region of the C2-H2 domain. The loss of hydrogen bonds and exposure of hydrophobic residues to solvent and helices turning to loops cause dysfunction of ZNF141 protein. These significant changes in the stability and conformation of the mutant protein were validated using essential dynamics and cross-correlation maps, which revealed that upon point mutation, the overall motion of the proteins and the correlation between them were completely different, resulting in Postaxial polydactyly type A. Conclusions: This study provides molecular insights into the structural association of ZNF141 protein with PAP type A. Identification of active site residues and legends offers new therapeutic targets for ZNF141 protein. Further, it reiterates the functional importance of the last residue of a protein.

Molecular Insights into the Role of Pathogenic nsSNPs in GRIN2B Gene Provoking Neurodevelopmental Disorders

The GluN2B subunit of N-methyl-D-aspartate receptors plays an important role in the physiology of different neurodevelopmental diseases. Genetic variations in the GluN2B coding gene (GRIN2B) have consistently been linked to West syndrome, intellectual impairment with focal epilepsy, developmental delay, macrocephaly, corticogenesis, brain plasticity, as well as infantile spasms and Lennox–Gastaut syndrome. It is unknown, however, how GRIN2B genetic variation impacts protein function. We determined the cumulative pathogenic impact of GRIN2B variations on healthy participants using a computational approach. We looked at all of the known mutations and calculated the impact of single nucleotide polymorphisms on GRIN2B, which encodes the GluN2B protein. The pathogenic effect, functional impact, conservation analysis, post-translation alterations, their driving residues, and dynamic behaviors of deleterious nsSNPs on protein models were then examined. Four polymorphisms were identified as phylogenetically conserved PTM drivers and were related to structural and functional impact: rs869312669 (p.Thr685Pro), rs387906636 (p.Arg682Cys), rs672601377 (p.Asn615Ile), and rs1131691702 (p.Ser526Pro). The combined impact of protein function is accounted for by the calculated stability, compactness, and total globularity score. GluN2B hydrogen occupancy was positively associated with protein stability, and solvent-accessible surface area was positively related to globularity. Furthermore, there was a link between GluN2B protein folding, movement, and function, indicating that both putative high and low local movements were linked to protein function. Multiple GRIN2B genetic variations are linked to gene expression, phylogenetic conservation, PTMs, and protein instability behavior in neurodevelopmental diseases. These findings suggest the relevance of GRIN2B genetic variations in neurodevelopmental problems.

Structural topological analysis of spike proteins of SARS-CoV-2 variants of concern highlight distinctive amino acid substitution patterns

Since the onset of pandemic in 2019, SARS-CoV-2 has diverged into numerous variants driven by antigenic and infectivity-oriented selection. Some variants have accumulated fitness-enhancing mutations, evaded immunity and spread despite global vaccination campaigns. The spike (S) glycoprotein of SARS-CoV-2 demonstrated the greatest immunogenicity and amino acid substitution diversity owing to its importance in the interaction with human angiotensin receptor 2 (hACE2). The S protein consistently emerges as an amino acid substitution (AAS) hotspot in all six lineages, however, in Omicron this enrichment is significantly higher. This study attempts to design and validate a method of mapping S-protein substitution profile across variants to identify the conserved and AAS regions. A substitution matrix was created based on publicly available databases, and the substitution localization was illustrated on a cryo-electron microscopy generated S-protein model. Our analyses indicated that the diversity of N-terminal (NTD) and receptor-binding (RBD) domains exceeded that of any other regions but still contained extended low substitution density regions particularly considering significantly broader substitution profiles of Omicron BA.2 and BA.4/5. Finally, the substitution matrix was compared to a random sample alignment of variant sequences, revealing discrepancies. Therefore, it was suggested to improve matrix accuracy by processing a large number of S-protein sequences using an automated algorithm. Several critical immunogenic and receptor-interacting residues were identified in the conserved regions within NTD and RBD. In conclusion, the structural and topological analysis of S proteins of SARS-CoV-2 variants highlight distinctive amino acid substitution patterns which may be foundational in predicting future variants.