Comparison of Immunological Profiles of SARS-CoV-2 Variants in the COVID-19 Pandemic Trends: An Immunoinformatics Approach

Elucidating the role of N440K mutation in SARS-CoV-2 spike - ACE-2 binding affinity and COVID-19 severity by virtual screening, molecular docking and dynamics approach

COVID-19 has become a public health concern around the world. The frequency of N440K variant was higher during the second wave in South India. The mutation was observed in the Receptor Binding Domain region (RBD) of the Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) spike (S) protein. The binding affinity of SARS-CoV-2-Angiotensin-Converting Enzyme-2 (ACE-2) plays a major role in the transmission and severity of the disease. To understand the binding affinity of the wild and mutant SARS-CoV-2 S with ACE2, molecular modeling studies were carried out. We discovered that the wild SARS-CoV-2 S RBD-ACE-2 complex has a high binding affinity and stability than that of the mutant. The N440K strain escapes from antibody neutralization, which might increase reinfection and decrease vaccine efficiency. To find a potential inhibitor against mutant N440K SARS-CoV-2, a virtual screening process was carried out and found ZINC169293961, ZINC409421825 and ZINC22060839 as the best binding energy compounds. Communicated by Ramaswamy H. Sarma.

Modeling the relationship between SARS-CoV-2 RNA in wastewater or sludge and COVID-19 cases in three New England regions

BACKGROUND

We aimed to compare statistical techniques estimating the association between SARS-CoV-2 RNA in untreated wastewater and sludge and reported coronavirus disease 2019 (COVID-19) cases.

METHODS

SARS-CoV-2 RNA concentrations (copies/mL) were measured from 24-h composite samples of wastewater in Massachusetts (MA) (daily; 8/19/2020-1/19/2021) and Maine (ME) (weekly; 9/1/2020-3/2/2021) and sludge samples in Connecticut (CT) (daily; 3/1/2020-6/1/2020). We fit linear, generalized additive with a cubic regression spline (GAM), Poisson, and negative binomial models to estimate the association between SARS-CoV-2 RNA concentration and reported COVID-19 cases.

RESULTS

The models that fit the data best were linear [adjusted R²=0.85 (MA), 0.16 (CT), 0.63 (ME); root-mean-square error (RMSE)=0.41 (MA), 1.14 (CT), 0.99 (ME)), GAM (adjusted R²=0.86 (MA), 0.16 (CT) 0.65 (ME); RMSE=0.39 (MA), 1.14 (CT), 0.97 (ME)], and Poisson [pseudo R²=0.84 (MA), 0.21 (CT), 0.52 (ME); RMSE=0.39 (MA), 0.67 (CT), 0.79 (ME)].

CONCLUSIONS

Linear, GAM, and Poisson models outperformed negative binomial models when relating SARS-CoV-2 RNA in wastewater or sludge to reported COVID-19 cases.

Rapid Degradation of SARS-CoV-2 Spike S Protein by A Specific Serine Protease

The S protein of SARS-CoV-2 is a crucial structural and functional component for virus entry. Due to the constant mutation of the virus, there are very limited ways to prevent and control COVID-19. This experiment used a macroscopic SDS-PAGE method and proved that the S protein of wild-type SARS-CoV-2 virus, especially the S1 subunit, is very sensitive to alkaline serine protease with acidic pI (ASPNJ), NJ represents Neanthes japonica (Izuka) from which ASP is purified). ASPNJ cleaves proteins when the carbonyl group of the peptide bond is contributed by arginine or lysine. ASPNJ can degrade the S protein very quickly and effectively in vitro with relative selectivity. It can be inferred that the S, S1 and RBD of SARS-CoV-2 variants can also be easily degraded by ASPNJ. This rapid and strong degradation of the S protein by ASPNJ may become a potential new treatment strategy.

Plant-Derived Antiviral Compounds as Potential Entry Inhibitors against Spike Protein of SARS-CoV-2 Wild-Type and Delta Variant: An Integrative in SilicoApproach

The wild-type SARS-CoV-2 has continuously evolved into several variants with increased transmissibility and virulence. The Delta variant which was initially identified in India created a devastating impact throughout the country during the second wave. While the efficacy of the existing vaccines against the latest SARS-CoV-2 variants remains unclear, extensive research is being carried out to develop potential antiviral drugs through approaches like in silico screening and drug-repurposing. This study aimed to conduct the docking-based virtual screening of 50 potential phytochemical compounds against a Spike glycoprotein of the wild-type and the Delta SARS-CoV-2 variant. Subsequently, molecular docking was performed for the five best compounds, such as Lupeol, Betulin, Hypericin, Corilagin, and Geraniin, along with synthetic controls. From the results obtained, it was evident that Lupeol exhibited a remarkable binding affinity towards the wild-type Spike protein (-8.54 kcal/mol), while Betulin showed significant binding interactions with the mutated Spike protein (-8.83 kcal/mol), respectively. The binding energy values of the selected plant compounds were slightly higher than that of the controls. Key hydrogen bonding and hydrophobic interactions of the resulting complexes were visualized, which explained their greater binding affinity against the target proteins-the Delta S protein of SARS-CoV-2, in particular. The lower RMSD, the RMSF values of the complexes and the ligands, Rg, H-bonds, and the binding free energies of the complexes together revealed the stability of the complexes and significant binding affinities of the ligands towards the target proteins. Our study suggests that Lupeol and Betulin could be considered as potential ligands for SARS-CoV-2 spike antagonists. Further experimental validations might provide new insights for the possible antiviral therapeutic interventions of the identified lead compounds and their analogs against COVID-19 infection.

EpiCurator: an immunoinformatic workflow to predict and prioritize SARS-CoV-2 epitopes

The ongoing coronavirus 2019 (COVID-19) pandemic, triggered by the emerging SARS-CoV-2 virus, represents a global public health challenge. Therefore, the development of effective vaccines is an urgent need to prevent and control virus spread. One of the vaccine production strategies uses the in silico epitope prediction from the virus genome by immunoinformatic approaches, which assist in selecting candidate epitopes for in vitro and clinical trials research. This study introduces the EpiCurator workflow to predict and prioritize epitopes from SARS-CoV-2 genomes by combining a series of computational filtering tools. To validate the workflow effectiveness, SARS-CoV-2 genomes retrieved from the GISAID database were analyzed. We identified 11 epitopes in the receptor-binding domain (RBD) of Spike glycoprotein, an important antigenic determinant, not previously described in the literature or published on the Immune Epitope Database (IEDB). Interestingly, these epitopes have a combination of important properties: recognized in sequences of the current variants of concern, present high antigenicity, conservancy, and broad population coverage. The RBD epitopes were the source for a multi-epitope design to in silico validation of their immunogenic potential. The multi-epitope overall quality was computationally validated, endorsing its efficiency to trigger an effective immune response since it has stability, high antigenicity and strong interactions with Toll-Like Receptors (TLR). Taken together, the findings in the current study demonstrated the efficacy of the workflow for epitopes discovery, providing target candidates for immunogen development.

Age and Sex Modulate SARS-CoV-2 Viral Load Kinetics: A Longitudinal Analysis of 1735 Subjects

The COVID-19 pandemic caused by SARS-CoV-2 represents a public health emergency, which became even more challenging since the detection of highly transmissible variants and strategies against COVID-19 were indistinctly established. We characterized the temporal viral load kinetics in individuals infected by original and variant strains. Naso-oropharyngeal swabs from 33,000 individuals (admitted to the IRCCS Santa Lucia Foundation Drive-in, healthcare professionals and hospitalized patients who underwent routinary screening) from November 2020 to June 2021 were analyzed. Of them, 1735 subjects were selected and grouped according to the viral strain. Diagnostic analyses were performed by CE-IVD RT-PCR-based kits. The subgenomic-RNA component was assessed in 36 subjects using digital PCR. Infection duration, viral load decay speed, effects of age and sex were assessed and compared by extensive statistical analyses. Overall, infection duration and viral load differed between the groups (p < 0.05). Male sex was more present among both original and variant carriers affected with high viral load and showing fast decay speed, whereas original strain carriers with slow decay speed resulted in older (p < 0.05). Subgenomic-RNA was detected in the positive samples, including those with low viral load. This study provides a picture of the viral load kinetics, identifying individuals with similar patterns and showing differential effects of age and sex, thus providing potentially useful information for personalized management of infected subjects.

Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population

Coronavirus disease (COVID-19) pandemic caused by the coronavirus SARS-CoV-2 represents an enormous challenge to global public health, with thousands of infections and deaths in over 200 countries worldwide. The purpose of this study was to identify SARS-CoV-2 epitopes with potential to interact in silico with the alleles of the human leukocyte antigen class I (HLA I) and class II (HLA II) commonly found in the Colombian population to promote both CD4 and CD8 immune responses against this virus. The generation and evaluation of the peptides in terms of HLA I and HLA II binding, immune response, toxicity and allergenicity were performed by using computer-aided tools, such as NetMHCpan 4.1, NetMHCIIpan 4.0, VaxiJem, ToxinPred and AllerTop. Furthermore, the interaction between the predicted epitopes with HLA I and HLA II proteins frequently found in the Colombian population was studied through molecular docking simulations in AutoDock Vina and interaction analysis in LigPlot+. One of the promising peptides proposed in this study is the HLA I epitope YQPYRVVVL, which displayed an estimated coverage of over 82% and 96% for the Colombian and worldwide population, respectively. These findings could be useful for the design of new epitope-vaccines that include Colombia among their population target.