Immunoinformatics-guided design of an epitope-based vaccine against severe acute respiratory syndrome coronavirus 2 spike glycoprotein

LNP-RNA-mediated antigen presentation leverages SARS-CoV-2-specific immunity for cancer treatment

Lipid nanoparticle (LNP)-mRNA vaccines have demonstrated protective capability in combating SARS-CoV-2. Their extensive deployment across the global population leads to the broad presence of T-cell immunity against the SARS-CoV-2 spike protein, presenting an opportunity to harness this immunological response as a universal antigen target for cancer treatment. Herein, we design and synthesize a series of amino alcohol- or amino acid-derived ionizable lipids (AA lipids) and develop an LNP-RNA-based antigen presentation platform to redirect spike-specific T-cell immunity against cancer in mouse models. First, in a prime-boost regimen, AA2 LNP encapsulating spike mRNA elicit stronger T-cell immunity against the spike epitopes compared to FDA-approved LNPs (ALC-0315 and SM-102), highlighting the superior delivery efficiency of AA2 LNP. Next, AA15V LNP efficiently delivers self-amplifying RNAs (saRNAs) encoding spike epitope-loaded single-chain trimer (sSE-SCT) MHC I molecules into tumor tissues, thereby inducing the presentation of spike epitopes. Our results show that a single intratumoral (i.t.) treatment of AA15V LNP-sSE-SCTs suppresses tumor growth and extends the survival of B16F10 melanoma and A20 lymphoma tumor-bearing mice vaccinated with AA2 LNP-spike mRNA. Additionally, AA15V LNP-sSE-SCTs enable SE-SCT expression in ex vivo human glioblastoma and lung cancer samples, suggesting its potential in clinical translation.

Revealing Dynamics of Protein Phosphorylation: A Study on the Cashmere Fineness Disparities in Liaoning Cashmere Goats

Exploring the landscape of protein phosphorylation, this investigation focuses on skin samples from LCG (Liaoning Cashmere Goats), characterized by different levels of cashmere fineness. Employing LC-MS/MS technology, we meticulously scrutinized FT-LCG (fine-type Liaoning Cashmere Goats) and CT-LCG (coarse-type Liaoning Cashmere Goats). Identifying 512 modified proteins, encompassing 1368 phosphorylated peptide segments and 1376 quantifiable phosphorylation sites, our exploration further revealed consistent phosphorylation sites in both groups. Analysis of phosphorylated peptides unveiled kinase substrates, prominently featuring Protein Kinase C, Protein Kinase B and MAPK3-MAPK1-MAPK7-NLK-group. Differential analysis spotlighted 28 disparate proteins, comprising six upregulated and twenty-two downregulated. Cluster analysis showcased the robust clustering efficacy of the two sample groups. GO (Gene Ontology) and KEGG (Kyoto Encyclopedia of Genes and Genomes) enrichment analyses underscored the significance of the purine metabolism pathway, suggesting its pivotal role in modulating cashmere fineness in LCG. Notably, through differential protein analysis, two crucial proteins were identified: HSL-X (hormone-sensitive lipase isoform X1) and KPRP (keratinocyte proline-rich protein). Further evidence supports LIPE and KPRP as key genes regulating cashmere fineness, paving the way for promising avenues in further research. These findings not only contribute to a nuanced understanding of protein-level dynamics in cashmere but also provide a theoretical foundation for the selective breeding of superior Liaoning Cashmere Goat strands.

Design of a novel multiepitope vaccine with CTLA-4 extracellular domain against Mycoplasma pneumoniae: A vaccine-immunoinformatics approach

BACKGROUND

Community-acquired pneumonia often stems from the macrolide-resistant strain of Mycoplasma pneumoniae, yet no effective vaccine exists against it.

METHODS

This study proposes a vaccine-immunoinformatics strategy for Mycoplasma pneumoniae and other pathogenic microbes. Specifically, dominant B and T cell epitopes of the Mycoplasma pneumoniae P30 adhesion protein were identified through immunoinformatics method. The vaccine sequence was then constructed by coupling with CTLA-4 extracellular region, a novel molecular adjuvant for antigen-presenting cells. Subsequently, the vaccine's physicochemical properties, antigenicity, and allergenicity were verified. Molecular dynamics modeling was employed to confirm interaction with TLR-2, TLR-4, B7-1, and B7-2. Finally, the vaccine underwent in silico cloning for expression.

RESULTS

The vaccine exhibited both antigenicity and non-allergenicity. Molecular dynamics simulation, post-docking with TLR-2, TLR-4, B7-1, and B7-2, demonstrated stable interaction between the vaccine and these molecules. In silico cloning confirmed effective expression of the vaccine gene in insect baculovirus vectors.

CONCLUSION

This vaccine-immunoinformatics approach holds promise for the development of vaccines against Mycoplasma pneumoniae and other pathogenic non-viral and non-bacterial microbes.

Naringenin-4'-glucuronide as a new drug candidate against the COVID-19 Omicron variant: a study based on molecular docking, molecular dynamics, MM/PBSA and MM/GBSA

This study aimed to identify natural bioactive compounds (NBCs) as potential inhibitors of the spike (S1) receptor binding domain (RBD) of the COVID-19 Omicron variant using computer simulations (in silico). NBCs with previously proven biological in vitro activity were obtained from the ZINC database and analyzed through virtual screening, molecular docking, molecular dynamics (MD), molecular mechanics/Poisson-Boltzmann surface area (MM/PBSA), and molecular mechanics/generalized Born surface area (MM/GBSA). Remdesivir was used as a reference drug in docking and MD calculations. A total of 170,906 compounds were analyzed. Molecular docking screening revealed the top four NBCs with a high affinity with the spike (affinity energy <-7 kcal/mol) to be ZINC000045789238, ZINC000004098448, ZINC000008662732, and ZINC000003995616. In the MD analysis, the four ligands formed a complex with the highest dynamic equilibrium S1 (mean RMSD <0.3 nm), lowest fluctuation of the complex amino acid residues (RMSF <1.3), and solvent accessibility stability. However, the ZINC000045789238-spike complex (naringenin-4'-O glucuronide) was the only one that simultaneously had minus signal (-) MM/PBSA and MM/GBSA binding free energy values (-3.74 kcal/mol and -15.65 kcal/mol, respectively), indicating favorable binding. This ligand (naringenin-4'-O glucuronide) was also the one that produced the highest number of hydrogen bonds in the entire dynamic period (average = 4601 bonds per nanosecond). Six mutant amino acid residues formed these hydrogen bonds from the RBD region of S1 in the Omicron variant: Asn417, Ser494, Ser496, Arg403, Arg408, and His505. Naringenin-4'-O-glucuronide showed promising results as a potential drug candidate against COVID-19. In vitro and preclinical studies are needed to confirm these findings.Communicated by Ramaswamy H. Sarma.

Self-Assembled Multiepitope Nanovaccine Provides Long-Lasting Cross-Protection against Influenza Virus

Seasonal influenza vaccines typically provide strain-specific protection and are reformulated annually, which is a complex and time-consuming process. Multiepitope vaccines, combining multiple conserved antigenic epitopes from a pathogen, can trigger more robust, diverse, and effective immune responses, providing a potential solution. However, their practical application is hindered by low immunogenicity and short-term effectiveness. In this study, multiple linear epitopes from the conserved stem domain of hemagglutinin and the ectodomain of matrix protein 2 are combined with the Helicobacter pylori ferritin, a stable self-assembled nanoplatform, to develop an influenza multiepitope nanovaccine, named MHF. MHF is prokaryotically expressed in a soluble form and self-assembles into uniform nanoparticles. The subcutaneous immunization of mice with adjuvanted MHF induces cross-reactive neutralizing antibodies, antibody-dependent cell-mediated cytotoxicity, and cellular immunity, offering complete protection against H3N2 as well as partial protection against H1N1. Importantly, the vaccine cargo delivered by ferritin triggers epitope-specific memory B-cell responses, with antibody level persisting for over 6 months post-immunization. These findings indicate that self-assembled multiepitope nanovaccines elicit potent and long-lasting immune responses while significantly reducing the risk of vaccine escape mutants, and offer greater practicality in terms of scalable manufacturing and genetic manipulability, presenting a promising and effective strategy for future vaccine development.

Predicting TCR sequences for unseen antigen epitopes using structural and sequence features

T-cell receptor (TCR) recognition of antigens is fundamental to the adaptive immune response. With the expansion of experimental techniques, a substantial database of matched TCR-antigen pairs has emerged, presenting opportunities for computational prediction models. However, accurately forecasting the binding affinities of unseen antigen-TCR pairs remains a major challenge. Here, we present convolutional-self-attention TCR (CATCR), a novel framework tailored to enhance the prediction of epitope and TCR interactions. Our approach utilizes convolutional neural networks to extract peptide features from residue contact matrices, as generated by OpenFold, and a transformer to encode segment-based coded sequences. We introduce CATCR-D, a discriminator that can assess binding by analyzing the structural and sequence features of epitopes and CDR3-β regions. Additionally, the framework comprises CATCR-G, a generative module designed for CDR3-β sequences, which applies the pretrained encoder to deduce epitope characteristics and a transformer decoder for predicting matching CDR3-β sequences. CATCR-D achieved an AUROC of 0.89 on previously unseen epitope-TCR pairs and outperformed four benchmark models by a margin of 17.4%. CATCR-G has demonstrated high precision, recall and F1 scores, surpassing 95% in bidirectional encoder representations from transformers score assessments. Our results indicate that CATCR is an effective tool for predicting unseen epitope-TCR interactions. Incorporating structural insights enhances our understanding of the general rules governing TCR-epitope recognition significantly. The ability to predict TCRs for novel epitopes using structural and sequence information is promising, and broadening the repository of experimental TCR-epitope data could further improve the precision of epitope-TCR binding predictions.

Integrating Reinforcement Learning and Monte Carlo Tree Search for enhanced neoantigen vaccine design

Recent advances in cancer immunotherapy have highlighted the potential of neoantigen-based vaccines. However, the design of such vaccines is hindered by the possibility of weak binding affinity between the peptides and the patient's specific human leukocyte antigen (HLA) alleles, which may not elicit a robust adaptive immune response. Triggering cross-immunity by utilizing peptide mutations that have enhanced binding affinity to target HLA molecules, while preserving their homology with the original one, can be a promising avenue for neoantigen vaccine design. In this study, we introduced UltraMutate, a novel algorithm that combines Reinforcement Learning and Monte Carlo Tree Search, which identifies peptide mutations that not only exhibit enhanced binding affinities to target HLA molecules but also retains a high degree of homology with the original neoantigen. UltraMutate outperformed existing state-of-the-art methods in identifying affinity-enhancing mutations in an independent test set consisting of 3660 peptide-HLA pairs. UltraMutate further showed its applicability in the design of peptide vaccines for Human Papillomavirus and Human Cytomegalovirus, demonstrating its potential as a promising tool in the advancement of personalized immunotherapy.

Exploring structural antigens of yellow fever virus to design multi-epitope subunit vaccine candidate by utilizing an immuno-informatics approach

BACKGROUND

Yellow fever is a mosquito-borne viral hemorrhagic disease transmitted by several species of virus-infected mosquitoes endemic to tropical regions of Central and South America and Africa. Earlier in the twentieth century, mass vaccination integrated with mosquito control was implemented to eradicate the yellow fever virus. However, regular outbreaks occur in these regions which pose a threat to travelers and residents of Africa and South America. There is no specific antiviral therapy, but there can be an effective peptide-based vaccine candidate to combat infection caused by the virus. Therefore, the study aims to design a multi-epitope-based subunit vaccine (MESV) construct against the yellow fever virus to reduce the time and cost using reverse vaccinology (RV) approach.

METHODS

Yellow fever virus contains 10,233 nucleotides that encode for 10 proteins (C, prM, E, NS1, NS2A, NS2B, NS3, NS4A, NS4B, and NS5) including 3 structural and 7 non-structural proteins. Structural proteins-precursor membrane protein (prM) and envelope protein (E)-were taken as a target for B cell and T cell epitope screening. Further, various immunoinformatics approaches were employed to FASTA sequences of structural proteins to retrieve B cell and T cell epitopes. MESV was constructed from these epitopes based on allergenicity, antigenicity and immunogenicity, toxicity, conservancy, and population coverage followed by structure prediction. The efficacy of the MESV construct to bind with human TLR-3, TLR-4, and TLR-8 were evaluated using molecular docking and simulation studies. Finally, in-silico cloning of vaccine construct was performed withpBR322 Escherichia coli expression system using codon optimization.

RESULTS

Predicted epitopes evaluated and selected for MESV construction were found stable, non-allergenic, highly antigenic, and global population coverage of 68.03% according to in-silico analysis. However, this can be further tested in in-vitro and in-vivo investigations. Epitopes were sequentially merged to construct a MESV consisting of 393 amino acids using adjuvant and linkers. Molecular docking and simulation studies revealed stable and high-affinity interactions. Furthermore, in-silico immune response graphs showed effective immune response generation. Finally, higher CAI value ensured high gene expression of vaccine in the host cell.

CONCLUSION

The designed MESV construct in the present in-silico study can be effective in generating an immune response against the yellow fever virus. Therefore, to prevent yellow fever, it can be an effective vaccine candidate. However, further downstream, in-vitro study is required.

Recent Updates on Viral Oncogenesis: Available Preventive and Therapeutic Entities

Human viral oncogenesis is a complex phenomenon and a major contributor to the global cancer burden. Several recent findings revealed cellular and molecular pathways that promote the development and initiation of malignancy when viruses cause an infection. Even, antiviral treatment has become an approach to eliminate the viral infections and prevent the activation of oncogenesis. Therefore, for a better understanding, the molecular pathogenesis of various oncogenic viruses like, hepatitis virus, human immunodeficiency viral (HIV), human papillomavirus (HPV), herpes simplex virus (HSV), and Epstein-Barr virus (EBV), could be explored, especially, to expand many potent antivirals that may escalate the apoptosis of infected malignant cells while sparing normal and healthy ones. Moreover, contemporary therapies, such as engineered antibodies antiviral agents targeting signaling pathways and cell biomarkers, could inhibit viral oncogenesis. This review elaborates the recent advancements in both natural and synthetic antivirals to control viral oncogenesis. The study also highlights the challenges and future perspectives of using antivirals in viral oncogenesis.

Drug target of natural products and COVID-19: how far has science progressed?

The new coronavirus [severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)] that caused a viral disease with a high risk of mortality (coronavirus disease 2019) was found toward the end of 2019. This was a significant acute respiratory syndrome. In a brief period, this virus spread throughout the entire planet, causing tremendous loss of life and economic damage. The process of developing new treatments takes time, and there are presently no recognized specific treatments to treat this infection. The most promising participants, who subsequently developed into prospective leads, were dropped from the clinical research in their latter phases. Medication that has previously acquired permission may only be repurposed for use for various medical reasons following a thorough investigation for safety and effectiveness. Because there are now no effective treatments available, natural products are being used haphazardly as antiviral medications and immunity boosters. The fundamental statement that most natural compounds have powerful antiviral action does not apply to SARS-CoV-2. Middle East respiratory syndrome coronavirus and severe acute respiratory syndrome coronavirus infections are inhibited by natural treatments. According to an in silico study, the virus' nonstructural proteins, including PLpro, Mpro, and RdRp, as well as structural proteins like the spike (S) protein, have been shown to have a strong affinity for several natural products and to be inhibited by them. The virus also suggests that it is a valid candidate for therapeutic research since it utilizes the intracellular angiotensin-converting enzyme 2 receptor of the host cell. In this study, interesting targets for SARS-CoV-2 medication development are explored, as well as the antiviral properties of some well-known natural compounds.

Advances in Computational and Bioinformatics Tools and Databases for Designing and Developing a Multi-Epitope-Based Peptide Vaccine

A vaccine is defined as a biologic preparation that trains the immune system, boosts immunity, and protects against a deadly microbial infection. They have been used for centuries to combat a variety of contagious illnesses by means of subsiding the disease burden as well as eradicating the disease. Since infectious disease pandemics are a recurring global threat, vaccination has emerged as one of the most promising tools to save millions of lives and reduce infection rates. The World Health Organization reports that immunization protects three million individuals annually. Currently, multi-epitope-based peptide vaccines are a unique concept in vaccine formulation. Epitope-based peptide vaccines utilize small fragments of proteins or peptides (parts of the pathogen), called epitopes, that trigger an adequate immune response against a particular pathogen. However, conventional vaccine designing and development techniques are too cumbersome, expensive, and time-consuming. With the recent advancement in bioinformatics, immunoinformatics, and vaccinomics discipline, vaccine science has entered a new era accompanying a modern, impressive, and more realistic paradigm in designing and developing next-generation strong immunogens. In silico designing and developing a safe and novel vaccine construct involves knowledge of reverse vaccinology, various vaccine databases, and high throughput techniques. The computational tools and techniques directly associated with vaccine research are extremely effective, economical, precise, robust, and safe for human use. Many vaccine candidates have entered clinical trials instantly and are available prior to schedule. In light of this, the present article provides researchers with up-to-date information on various approaches, protocols, and databases regarding the computational designing and development of potent multi-epitope-based peptide vaccines that can assist researchers in tailoring vaccines more rapidly and cost-effectively.

Computer Analysis of the Inhibition of ACE2 by Flavonoids and Identification of Their Potential Antiviral Pharmacophore Site

In the present study, we investigated the antiviral activities of 17 flavonoids as natural products. These derivatives were evaluated for their in vitro antiviral activities against HIV and SARS-CoV-2. Their antiviral activity was evaluated for the first time based on POM (Petra/Osiris/Molispiration) theory and docking analysis. POM calculation was used to analyze the atomic charge and geometric characteristics. The side effects, drug similarities, and drug scores were also assumed for the stable structure of each compound. These results correlated with the experimental values. The bioinformatics POM analyses of the relative antiviral activities of these derivatives are reported for the first time.

Potential of a novel flagellin epitope as a broad-spectrum vaccine candidate against enteric fever

Relentless emergence of antibiotic resistant Salmonella strains, coupled with the drawbacks associated with currently available vaccines against enteric fever, warrants an urgent need to look for new vaccine candidates. Out of the multiple virulence factors harbored by Salmonella, flagella are regarded as one of the most important targets of innate as well as adaptive immune response. Individual Salmonella serotypes alternate between expression of two different antigenic forms encoded by fliC and fljB genes, respectively thereby employing this as a strategy to escape the host immune response. In the present study, using various immunoinformatic approaches, a flagellin epitope, present in both antigenic forms of typhoidal Salmonellae has been targeted. Following B-cell epitope and B-cell derived T-cell epitope prediction and interaction studies with major histocompatibility complexes using molecular docking, a peptide epitope was selected. Further, it was screened for its presence in majority of typhoidal serovars along with other useful attributes, in silico. Thereafter, safety studies were performed with the synthesized peptide. Subsequently, immunization studies were carried out using S. Typhi as well as S. Paratyphi A induced murine peritonitis model. Active immunization with peptide-BSA conjugate resulted in 75% and 80% mice survival following lethal challenge with S. Typhi and S. Paratyphi A respectively, along with a significant IgG antibody titer, thereby highlighting its immunogenic potential. Reduced bacterial burden in vital organs along with improved histoarchitecture and cytokine levels further substantiated the protective efficacy of the proposed candidate. Passive immunization studies with the candidate verified the protective efficacy of the generated antibodies against lethal challenge of bacteria in mice. Given the endemic nature of enteric fever and the antigenic variability observed in Salmonella serotypes, present study highlights the importance of using a vaccine candidate, which, along with generating a strong immune response, also exhibits a broad coverage against both, S. Typhi as well as S. Paratyphi A strains.

An Immunoinformatics Approach to Design a Potent Multi-Epitope Vaccine against Asia-1 Genotype of Crimean-Congo Haemorrhagic Fever Virus Using the Structural Glycoproteins as a Target

Crimean-Congo haemorrhagic fever (CCHF), caused by Crimean-Congo haemorrhagic fever virus (CCHFV), is a disease of worldwide importance (endemic yet not limited to Asia, Middle East, and Africa) and has triggered several outbreaks amounting to a case fatality rate of 10-40% as per the World Health Organization. Genetic diversity and phylogenetic data revealed that the Asia-1 genotype of CCHFV remained dominant in Pakistan, where 688 confirmed cases were reported between the 2012-2022 period. Currently, no approved vaccine is available to tackle the viral infection. Epitope-based vaccine design has gained significant attention in recent years due to its safety, timeliness, and cost efficiency compared to conventional vaccines. In the present study, we employed a robust immunoinformatics-based approach targeting the structural glycoproteins G1 and G2 of CCHFV (Asia-1 genotype) to design a multi-epitope vaccine construct. Five B-cells and six cytotoxic T-lymphocytes (CTL) epitopes were mapped and finalized from G1 and G2 and were fused with suitable linkers (EAAAK, GGGS, AAY, and GPGPG), a PADRE sequence (13 aa), and an adjuvant (50S ribosomal protein L7/L12) to formulate a chimeric vaccine construct. The selected CTL epitopes showed high affinity and stable binding with the binding groove of common human HLA class I molecules (HLA-A*02:01 and HLA-B*44:02) and mouse major histocompatibility complex class I molecules. The chimeric vaccine was predicted to be an antigenic, non-allergenic, and soluble molecule with a suitable physicochemical profile. Molecular docking and molecular dynamics simulation indicated a stable and energetically favourable interaction between the constructed antigen and Toll-like receptors (TLR2, TLR3, and TLR4). Our results demonstrated that innate, adaptive, and humoral immune responses could be elicited upon administration of such a potent muti-epitope vaccine construct. These results could be helpful for an experimental vaccinologist to develop an effective vaccine against the Asia-1 genotype of CCHFV.

Synthesis, In Vitro α-Glucosidase Inhibitory Activity and Molecular Docking Study of New Benzotriazole-Based Bis-Schiff Base Derivatives

This study was carried out to synthesize benzotriazole-based bis-Schiff base scaffolds (1-20) and assess them in vitro for α-glucosidase inhibitory potentials. All the synthetics analogs based on benzotriazole-based bis-Schiff base scaffolds were found to display an outstanding inhibition profile on screening against the α-glucosidase enzyme. The synthetic scaffolds showed a varied range of inhibition profiles having IC₅₀ values ranging from 1.10 ± 0.05 µM to 28.30 ± 0.60 µM when compared to acarbose as a standard drug (IC₅₀ = 10.30 ± 0.20 µM). Among the series, fifteen scaffolds 1-3, 5, 6, 9-16, 18-20 were identified to be more potent than standard acarbose, while the five remaining scaffolds 4, 7, 8, 16, and 17, also showed potency against the α-glucosidase enzyme but were found to be less potent than standard acarbose. The structure of all the newly synthesized scaffolds was confirmed using different spectroscopic techniques such as HREI-MS and ¹H- and ¹³C- NMR spectroscopy. To find a structure-activity relationship, molecular docking studies were carried out to understand the binding mode of the active inhibitors with the active sites of the enzyme and the results supported the experimental data.

Exploiting reverse vaccinology approach for the design of a multiepitope subunit vaccine against the major SARS-CoV-2 variants

The current COVID-19 pandemic, an infectious disease caused by the novel coronavirus (SARS-CoV-2), poses a threat to global health because of its high rate of spread and death. Currently, vaccination is the most effective method to prevent the spread of this disease. In the present study, we developed a novel multiepitope vaccine against SARS-CoV-2 containing Alpha (B.1.1.7), Beta (B.1.351), Gamma (P.1), Delta (B.1.617.2), and Omicron (BA.1) variants. To this end, we performed a robust immunoinformatics approach based on multiple epitopes of the four structural proteins of SARS-CoV-2 (S, M, N, and E) from 475 SARS-CoV-2 genomes sequenced from the regions with the highest number of registered cases, namely the United States, India, Brazil, France, Germany, and the United Kingdom. To investigate the best immunogenic epitopes for linear B cells, cytotoxic T lymphocytes (CTL), and helper T lymphocytes (HTL), we evaluated antigenicity, allergenicity, conservation, immunogenicity, toxicity, human population coverage, IFN-inducing, post-translational modifications, and physicochemical properties. The tertiary structure of a vaccine prototype was predicted, refined, and validated. Through docking experiments, we evaluated its molecular coupling to the key immune receptor Toll-Like Receptor 3 (TLR3). To improve the quality of docking calculations, quantum mechanics/molecular mechanics calculations (QM/MM) were used, with the QM part of the simulations performed using the density functional theory formalism (DFT). Cloning and codon optimization were performed for the successful expression of the vaccine in E. coli. Finally, we investigated the immunogenic properties and immune response of our SARS-CoV-2 multiepitope vaccine. The results of the simulations show that administering our prototype three times significantly increases the antibody response and decreases the amount of antigens. The proposed vaccine candidate should therefore be tested in clinical trials for its efficacy in neutralizing SARS-CoV-2.

SARS-CoV-2 Omicron (BA.1 and BA.2) specific novel CD8+ and CD4+ T cell epitopes targeting spike protein

The Omicron (BA.1/B.1.1.529) variant of SARS-CoV-2 harbors an alarming 37 mutations on its spike protein, reducing the efficacy of current COVID-19 vaccines. In this study, we identified CD8+ and CD4+ T cell epitopes from SARS-CoV-2 S protein mutants. To identify the highest quality CD8 and CD4 epitopes from the Omicron variant, we selected epitopes with a high binding affinity towards both MHC I and MHC II molecules. We applied other clinical checkpoint predictors, including immunogenicity, antigenicity, allergenicity, instability and toxicity. Subsequently, we found eight Omicron (BA.1/B.1.1.529) specific CD8+ and eleven CD4+ T cell epitopes with a world population coverage of 76.16% and 97.46%, respectively. Additionally, we identified common epitopes across Omicron BA.1 and BA.2 lineages that target mutations critical to SARS-CoV-2 virulence. Further, we identified common epitopes across B.1.1.529 and other circulating SARS-CoV-2 variants, such as B.1.617.2 (Delta). We predicted CD8 epitopes' binding affinity to murine MHC alleles to test the vaccine candidates in preclinical models. The CD8 epitopes were further validated using our previously developed software tool PCOptim. We then modeled the three-dimensional structures of our top CD8 epitopes to investigate the binding interaction between peptide-MHC and peptide-MHC-TCR complexes. Notably, our identified epitopes are targeting the mutations on the RNA-binding domain and the fusion sites of S protein. This could potentially eliminate viral infections and form long-term immune responses compared to relatively short-lived mRNA vaccines and maximize the efficacy of vaccine candidates against the current pandemic and potential future variants.

Potential SARS-CoV-2 RdRp inhibitors of cytidine derivatives: Molecular docking, molecular dynamic simulations, ADMET, and POM analyses for the identification of pharmacophore sites

The RNA-dependent RNA polymerase (RdRp) of SARS-CoV-2 is one of the optimum targets for antiviral drug design and development. The hydroxyl groups of cytidine structures were modified with different aliphatic and aromatic groups to obtain 5´-O-acyl and 2´,3´-di-O-acyl derivatives, and then, these derivatives were employed in molecular modeling, antiviral prediction, molecular docking, molecular dynamics, pharmacological and POM studies. Density functional theory (DFT) at the B3LYP/6-31G++ level analyzed biochemical behavior and molecular electrostatic potential (MESP) of the modified cytidine derivatives. The antiviral parameters of the mutated derivatives revealed promising drug properties compared with those of standard antiviral drugs. Molecular docking has determined binding affinities and interactions between the cytidine derivatives and SARS-CoV-2 RdRp. The modified derivatives strongly interacted with prime Pro620 and Lys621 residues. The binding conformation and interactions stability were investigated by 200 ns of molecular dynamics simulations and predicted the compounds to firmly dock inside the RdRp binding pocket. Interestingly, the binding residues of the derivatives were revealed in high equilibrium showing an enhanced binding affinity for the molecules. Intermolecular interactions are dominated by both Van der Waals and electrostatic energies. Finally, the pharmacokinetic characterization of the optimized inhibitors confirmed the safety of derivatives due to their improved kinetic properties. The selected cytidine derivatives can be suggested as potential inhibitors against SARS-CoV-2. The POM Theory supports the hypothesis above by confirming the existence of an antiviral (Oδ--O'δ-) pharmacophore site of Hits.

Mapping Potential Vaccine Candidates Predicted by VaxiJen for Different Viral Pathogens between 2017-2021-A Scoping Review

Reverse vaccinology (RV) is a promising alternative to traditional vaccinology. RV focuses on in silico methods to identify antigens or potential vaccine candidates (PVCs) from a pathogen's proteome. Researchers use VaxiJen, the most well-known RV tool, to predict PVCs for various pathogens. The purpose of this scoping review is to provide an overview of PVCs predicted by VaxiJen for different viruses between 2017 and 2021 using Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) guidelines. We used the term 'vaxijen' to search PubMed, Scopus, Web of Science, EBSCOhost, and ProQuest One Academic. The protocol was registered at the Open Science Framework (OSF). We identified articles on this topic, charted them, and discussed the key findings. The database searches yielded 1033 articles, of which 275 were eligible. Most studies focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), published between 2020 and 2021. Only a few articles (8/275; 2.9%) conducted experimental validations to confirm the predictions as vaccine candidates, with 2.2% (6/275) articles mentioning recombinant protein expression. Researchers commonly targeted parts of the SARS-CoV-2 spike (S) protein, with the frequently predicted epitopes as PVCs being major histocompatibility complex (MHC) class I T cell epitopes WTAGAAAYY, RQIAPGQTG, IAIVMVTIM, and B cell epitope IAPGQTGKIADY, among others. The findings of this review are promising for the development of novel vaccines. We recommend that vaccinologists use these findings as a guide to performing experimental validation for various viruses, with SARS-CoV-2 as a priority, because better vaccines are needed, especially to stay ahead of the emergence of new variants. If successful, these vaccines could provide broader protection than traditional vaccines.

A common allele of HLA mediates asymptomatic SARS-CoV-2 infection

Despite some inconsistent reporting of symptoms, studies have demonstrated that at least 20% of individuals infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) will remain asymptomatic. Although most global efforts have focused on understanding factors underlying severe illness in COVID-19 (coronavirus disease of 2019), the examination of asymptomatic infection provides a unique opportunity to consider early disease and immunologic features promoting rapid viral clearance. Owing to its critical role in the immune response, we postulated that variation in the human leukocyte antigen (HLA) loci may underly processes mediating asymptomatic infection. We enrolled 29,947 individuals registered in the National Marrow Donor Program for whom high-resolution HLA genotyping data were available in the UCSF Citizen Science smartphone-based study designed to track COVID-19 symptoms and outcomes. Our discovery cohort (n=1428) was comprised of unvaccinated, self-identified subjects who reported a positive test result for SARS-CoV-2. We tested for association of five HLA loci (HLA-A, -B, -C, -DRB1, -DQB1) with disease course and identified a strong association of HLA-B*15:01 with asymptomatic infection, and reproduced this association in two independent cohorts. Suggesting that this genetic association is due to pre-existing T-cell immunity, we show that T cells from pre-pandemic individuals carrying HLA-B*15:01 were reactive to the immunodominant SARS-CoV-2 S-derived peptide NQKLIANQF, and 100% of the reactive cells displayed memory phenotype. Finally, we characterize the protein structure of HLA-B*15:01-peptide complexes, demonstrating that the NQKLIANQF peptide from SARS-CoV-2, and the highly homologous NQKLIANAF from seasonal coronaviruses OC43-CoV and HKU1-CoV, share similar ability to be stabilized and presented by HLA-B*15:01, providing the molecular basis for T-cell cross-reactivity and HLA-B*15:01-mediated pre-existing immunity.

Missense mutations in spike protein of SARS-CoV-2 delta variant contribute to the alteration in viral structure and interaction with hACE2 receptor

INTRODUCTION

Many of the global pandemics threaten human existence over the decades among which coronavirus disease (COVID-19) is the newest exposure circulating worldwide. The RNA encoded severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus is referred as the pivotal agent of this deadly disease that induces respiratory tract infection by interacting host ACE2 receptor with its spike glycoprotein. Rapidly evolving nature of this virus modified into new variants helps in perpetrating immune escape and protection against host defense mechanism. Consequently, a new isolate, delta variant originated from India is spreading perilously at a higher infection rate.

METHODS

In this study, we focused to understand the conformational and functional significance of the missense mutations found in the spike glycoprotein of SARS-CoV-2 delta variant performing different computational analysis.

RESULTS

From physiochemical analysis, we found that the acidic isoelectric point of the virus elevated to basic pH level due to the mutations. The targeted mutations were also found to change the interactive bonding pattern and conformational stability analyzed by the molecular dynamic's simulation. The molecular docking study also revealed that L452R and T478K mutations found in the RBD domain of delta variant spike protein contributed to alter interaction with the host ACE2 receptor.

CONCLUSIONS

Overall, this study provided insightful evidence to understand the morphological and attributive impact of the mutations on SARS-CoV-2 delta variant.

Identification of Antigenic Properties of Acinetobacter baumannii Proteins as Novel Putative Vaccine Candidates Using Reverse Vaccinology Approach

Multidrug-resistant Acinetobacter baumannii (A. baumannii) infections are becoming more prevalent all over the world. As a cost-effective and preventative method, vaccination seems to be required against this bacterium. In the present study, subtractive proteomics along with reverse vaccinology approaches was used to predict suitable therapeutics against A. baumannii. Using the Vaxign online tool, we studied over 35 genomes of A. baumannii strains and chose outer membrane and secreted proteins of A. baumannii 1656-2 as possible vaccine candidates. Then, investigations were performed on the immunogenicity, antigenic characteristics, physicochemical properties, B-cell and MHC class I, and MHC class II molecules epitope densities of proteins. After optimizing the codon of the proteins, the pcDNA3.1( +) expression construct was designed and the immunogenicity, allergenicity, and physicochemical properties of the vaccine construct were predicted. Hcp and OmpC proteins were predicted as extracellular and outer membrane proteins, respectively. These proteins interact with 10 other proteins to form a network of protein interactions with virulence properties. Immunoassays of Hcp and OmpC proteins showed antigenicity of 0.88 and 0.79, respectively. These proteins have 5 structural cell epitope points and 5 linear B epitope points. They are also able to bind to different HLA alleles of MCH class I/class II as selected immunogenic proteins and designed non-allergenic structures with solubility of 0.650 and immunogenicity score of 0.91. The results of this "in silico" study indicate high specificity and the development of a significant humoral and cellular immune response. It can be concluded that the Hcp and OmpC dual vaccine construct is one of the promising candidates against A. baumannii. The findings of this "in silico" study show excellent specificity and the emergence of a substantial humoral and cellular immune response. This is a computer-based study that needs to be tested in vitro and in vivo to corroborate the conclusions of the vaccine design procedures.

Computational vaccinology guided design of multi-epitope subunit vaccine against a neglected arbovirus of the Americas

Mayaro virus (MAYV) is an arbovirus found in the Americas that can cause debilitating arthritogenic disease. Although it is an emerging virus, the only current approach is vector control, as there are no approved vaccines to prevent MAYV infection nor therapeutics to treat it. In search of an effective vaccine candidate against MAYV, we used immunoinformatics and molecular modeling to attempt to identify promiscuous T-cell epitopes of the nonstructural polyproteins (nsP1, nsP2, nsP3, and nsP4) from 127 MAYV genomes sequenced in the Americas (08 Bolivia, 72 Brazil, 04 French Guiana, 05 Haiti, 20 Peru, 04 Trinidad and Tobago, and 14 Venezuela). For this purpose, consensus sequences of 360 proteins were used to identify short protein sequences that can bind to MHC I class (MHC II). Our analysis revealed 56 potential MHC-I/TCD8+ (29 MHC-II/TCD4+) epitopes, but only 6 (16) TCD8+ (TCD4+) epitopes showed high antigenicity and conservation, non-allergenicity, non-toxicity, and excellent population coverage. Finally, classical and quantum mechanical calculations (QM:MM) were used to improve the quality of the docking calculations, with the QM part of the simulations performed using the density functional theory formalism (DFT). These results provide insights for the advancement of diagnostic platforms, vaccine development, and immunotherapeutic interventions.Communicated by Ramaswamy H. Sarma.

In silico Designing of an Epitope-Based Vaccine Against Common E. coli Pathotypes

Escherichia coli (E. coli) is a Gram-negative bacterium that belongs to the family Enterobacteriaceae. While E. coli can stay as an innocuous resident in the digestive tract, it can cause a group of symptoms ranging from diarrhea to live threatening complications. Due to the increased rate of antibiotic resistance worldwide, the development of an effective vaccine against E. coli pathotypes is a major health priority. In this study, a reverse vaccinology approach along with immunoinformatics has been applied for the detection of potential antigens to develop an effective vaccine. Based on our screening of 5,155 proteins, we identified lipopolysaccharide assembly protein (LptD) and outer membrane protein assembly factor (BamA) as vaccine candidates for the current study. The conservancy of these proteins in the main E. coli pathotypes was assessed through BLASTp to make sure that the designed vaccine will be protective against major E. coli pathotypes. The multitope vaccine was constructed using cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), and B cell lymphocyte (BCL) epitopes with suitable linkers and adjuvant. Following that, it was analyzed computationally where it was found to be antigenic, soluble, stable, and non-allergen. Additionally, the adopted docking study, as well as all-atom molecular dynamics simulation, illustrated the promising predicted affinity and free binding energy of this constructed vaccine against the human Toll-like receptor-4 (hTLR-4) dimeric state. In this regard, wet lab studies are required to prove the efficacy of the potential vaccine construct that demonstrated promising results through computational validation.

Peptides for Vaccine Development

This review discusses peptide epitopes used as antigens in the development of vaccines in clinical trials as well as future vaccine candidates. It covers peptides used in potential immunotherapies for infectious diseases including SARS-CoV-2, influenza, hepatitis B and C, HIV, malaria, and others. In addition, peptides for cancer vaccines that target examples of overexpressed proteins are summarized, including human epidermal growth factor receptor 2 (HER-2), mucin 1 (MUC1), folate receptor, and others. The uses of peptides to target cancers caused by infective agents, for example, cervical cancer caused by human papilloma virus (HPV), are also discussed. This review also provides an overview of model peptide epitopes used to stimulate non-specific immune responses, and of self-adjuvanting peptides, as well as the influence of other adjuvants on peptide formulations. As highlighted in this review, several peptide immunotherapies are in advanced clinical trials as vaccines, and there is great potential for future therapies due the specificity of the response that can be achieved using peptide epitopes.

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.

Design of a multi-epitope vaccine against SARS-CoV-2: immunoinformatic and computational methods

A novel infectious agent, SARS-CoV-2, is responsible for causing the severe respiratory disease COVID-19 and death in humans. Spike glycoprotein plays a key role in viral particles entering host cells, mediating receptor recognition and membrane fusion, and are considered useful targets for antiviral vaccine candidates. Therefore, computational techniques can be used to design a safe, antigenic, immunogenic, and stable vaccine against this pathogen. Drawing upon the structure of the S glycoprotein, we are trying to develop a potent multi-epitope subunit vaccine against SARS-CoV-2. The vaccine was designed based on cytotoxic T-lymphocyte and helper T-lymphocyte epitopes with an N-terminal adjuvant via conducting immune filters and an extensive immunoinformatic investigation. The safety and immunogenicity of the designed vaccine were further evaluated via using various physicochemical, allergenic, and antigenic characteristics. Vaccine-target (toll-like receptors: TLR2 and TLR4) interactions, binding affinities, and dynamical stabilities were inspected through molecular docking and molecular dynamic (MD) simulation methods. Moreover, MD simulations for dimeric TLRs/vaccine in the membrane-aqueous environment were performed to understand the differential domain organization of TLRs/vaccine. Further, dynamical behaviors of vaccine/TLR systems were inspected via identifying the key residues (named HUB nodes) that control interaction stability and provide a clear molecular mechanism. The obtained results from molecular docking and MD simulation revealed a strong and stable interaction between vaccine and TLRs. The vaccine's ability to stimulate the immune response was assessed by using computational immune simulation. This predicted a significant level of cytotoxic T cell and helper T cell activation, as well as IgG, interleukin 2, and interferon-gamma production. This study shows that the designed vaccine is structurally and dynamically stable and can trigger an effective immune response against viral infections.

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.

Designing of a Multi-epitope Vaccine against the Structural Proteins of Marburg Virus Exploiting the Immunoinformatics Approach

Marburg virus disease (MVD) caused by the Marburg virus (MARV) generally appears with flu-like symptoms and leads to severe hemorrhagic fever. It spreads via direct contact with infected individuals or animals. Despite being considered to be less threatening in terms of appearances and the number of infected patients, the high fatality rate of this pathogenic virus is a major concern. Until now, no vaccine has been developed to combat this deadly virus. Therefore, vaccination for this virus is necessary to reduce its mortality. Our current investigation focuses on the design and formulation of a multi-epitope vaccine based on the structural proteins of MARV employing immunoinformatics approaches. The screening of potential T-cell and B-cell epitopes from the seven structural proteins of MARV was carried out through specific selection parameters. Afterward, we compiled the shortlisted epitopes by attaching them to an appropriate adjuvant and linkers. Population coverage analysis, conservancy analysis, and MHC cluster analysis of the shortlisted epitopes were satisfactory. Importantly, physicochemical characteristics, human homology assessment, and structure validation of the vaccine construct delineated convenient outcomes. We implemented disulfide bond engineering to stabilize the tertiary or quaternary interactions. Furthermore, stability and physical movements of the vaccine protein were explored using normal-mode analysis. The immune simulation study of the vaccine complexes also exhibited significant results. Additionally, the protein-protein docking and molecular dynamics simulation of the final construct exhibited a higher affinity toward toll-like receptor-4 (TLR4). From simulation trajectories, multiple descriptors, namely, root mean square deviations (rmsd), radius of gyration (Rg), root mean square fluctuations (RMSF), solvent-accessible surface area (SASA), and hydrogen bonds, have been taken into account to demonstrate the inflexible and rigid nature of receptor molecules and the constructed vaccine. Inclusively, our findings suggested the vaccine constructs' ability to regulate promising immune responses against MARV pathogenesis.

Immunoinformatics mapping of potential epitopes in SARS-CoV-2 structural proteins

All approved coronavirus disease 2019 (COVID-19) vaccines in current use are safe, effective, and reduce the risk of severe illness. Although data on the immunological presentation of patients with COVID-19 is limited, increasing experimental evidence supports the significant contribution of B and T cells towards the resolution of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. Despite the availability of several COVID-19 vaccines with high efficacy, more effective vaccines are still needed to protect against the new variants of SARS-CoV-2. Employing a comprehensive immunoinformatic prediction algorithm and leveraging the genetic closeness with SARS-CoV, we have predicted potential immune epitopes in the structural proteins of SARS-CoV-2. The S and N proteins of SARS-CoV-2 and SARS-CoVs are main targets of antibody detection and have motivated us to design four multi-epitope vaccines which were based on our predicted B- and T-cell epitopes of SARS-CoV-2 structural proteins. The cardinal epitopes selected for the vaccine constructs are predicted to possess antigenic, non-allergenic, and cytokine-inducing properties. Additionally, some of the predicted epitopes have been experimentally validated in published papers. Furthermore, we used the C-ImmSim server to predict effective immune responses induced by the epitope-based vaccines. Taken together, the immune epitopes predicted in this study provide a platform for future experimental validations which may facilitate the development of effective vaccine candidates and epitope-based serological diagnostic assays.

Designing an epitope vaccine against Dermatophagoides pteronyssinus: An in silico study

The house dust mite, Dermatophagoides pteronyssinus, is a major source of the inhaled allergen Der p 1, which causes immunoglobulin E (IgE)-mediated hypersensitivity reactions manifesting in allergic diseases. To date, no drugs or vaccines effectively treat or prevent Der p 1 sensitization. We applied in silico immunoinformatics to design T-cell and B-cell epitopes that were specified and developed from the allergen Der p 1 of D. pteronyssinus. We identified the conserved epitope areas by predicting the accessibility and flexibility of B-cell epitopes, and the percentage of human leukocyte antigen representing T cells. Molecular docking using HADDOCK software indicated three optimal clusters: cluster 6 (z-score: -2.1), cluster 1 (z-score: -1.2), and cluster 3 (z-score: -0.6). The most negative Z-score was found in cluster 6, which represented three epitopes. The interaction between A chain proteins (IgE protein residues) and B chains (Der p 1 protein residues) exhibited a knowledge-based FADE and contact value >1, suggesting the best protein interactions occurred in the conserved area. Molecular dynamic simulation further predicted the stable nature of Der p 1 protein. The IQRDNGYQP region is the best candidate to be utilized as a D. pteronyssinus epitope vaccine, which could be used in the development of allergen-specific immunotherapy.

Computational Design and Analysis of a Multi-epitope Against Influenza A virus

Influenza A viruses are among the most studied viruses, however no effective prevention against influenza infection has been developed. So, designing an effective vaccine against Influenza A virus is a critical issue in the field of medical biotechnology. For this reason, to combat this disease, we have designed a novel multi-epitope vaccine candidate based on the several conserved and potential linear B-cell and T-cell binding epitopes by using the in silico approach. This vaccine consists of an ER signal conserved sequence, the PADRE conserved epitope and two conserved epitopes of Influenza matrix protein 2. T-cell binding epitopes from Matrix protein 2 were predicted by in silico tools of epitope prediction. The selected epitopes were joined by flexible linkers and physicochemical properties, toxicity, and allergenecity were investigated. The designed vaccine was antigenic, immunogenic, and non-allergenic with suitable physicochemical properties and has higher solubility. The final multi-epitope construct was modeled, confirmed by different programs and the molecular interactions with immune receptors were considered. The molecular docking assay indicated the interactions with immune-stimulatory toll-like receptor 3 (TLR3) and major histocompatibility complex class I (MHCI). The HADDOCK and H DOCK servers were used to make docking analysis, respectively. The docking analysis indicated a strong and stable binding interaction between the vaccine construct with major histocompatibility complex (MHC) class I and toll-like receptor 3. Overall, the findings suggest that the current vaccine may be a promising vaccine to prevent Influenza infection.

Phytochemicals from Leucas zeylanica Targeting Main Protease of SARS-CoV-2: Chemical Profiles, Molecular Docking, and Molecular Dynamics Simulations

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), a contemporary coronavirus, has impacted global economic activity and has a high transmission rate. As a result of the virus's severe medical effects, developing effective vaccinations is vital. Plant-derived metabolites have been discovered as potential SARS-CoV-2 inhibitors. The SARS-CoV-2 main protease (Mpro) is a target for therapeutic research because of its highly conserved protein sequence. Gas chromatography-mass spectrometry (GC-MS) and molecular docking were used to screen 34 compounds identified from Leucas zeylanica for potential inhibitory activity against the SARS-CoV-2 Mpro. In addition, prime molecular mechanics-generalized Born surface area (MM-GBSA) was used to screen the compound dataset using a molecular dynamics simulation. From molecular docking analysis, 26 compounds were capable of interaction with the SARS-CoV-2 Mpro, while three compounds, namely 11-oxa-dispiro[4.0.4.1]undecan-1-ol (-5.755 kcal/mol), azetidin-2-one 3,3-dimethyl-4-(1-aminoethyl) (-5.39 kcal/mol), and lorazepam, 2TMS derivative (-5.246 kcal/mol), exhibited the highest docking scores. These three ligands were assessed by MM-GBSA, which revealed that they bind with the necessary Mpro amino acids in the catalytic groove to cause protein inhibition, including Ser144, Cys145, and His41. The molecular dynamics simulation confirmed the complex rigidity and stability of the docked ligand-Mpro complexes based on the analysis of mean radical variations, root-mean-square fluctuations, solvent-accessible surface area, radius of gyration, and hydrogen bond formation. The study of the postmolecular dynamics confirmation also confirmed that lorazepam, 11-oxa-dispiro[4.0.4.1]undecan-1-ol, and azetidin-2-one-3, 3-dimethyl-4-(1-aminoethyl) interact with similar Mpro binding pockets. The results of our computerized drug design approach may assist in the fight against SARS-CoV-2.

Immunogenicity and antigenicity based T-cell and B-cell epitopes identification from conserved regions of 10664 SARS-CoV-2 genomes

The surge of SARS-CoV-2 has created a wave of pandemic around the globe due to its high transmission rate. To contain this virus, researchers are working around the clock for a solution in the form of vaccine. Due to the impact of this pandemic, the economy and healthcare have immensely suffered around the globe. Thus, an efficient vaccine design is the need of the hour. Moreover, to have a generalised vaccine for heterogeneous human population, the virus genomes from different countries should be considered. Thus, in this work, we have performed genome-wide analysis of 10,664 SARS-CoV-2 genomes of 73 countries around the globe in order to identify the potential conserved regions for the development of peptide based synthetic vaccine viz. epitopes with high immunogenic and antigenic scores. In this regard, multiple sequence alignment technique viz. Clustal Omega is used to align the 10,664 SARS-CoV-2 virus genomes. Thereafter, entropy is computed for each genomic coordinate of the aligned genomes. The entropy values are then used to find the conserved regions. These conserved regions are refined based on the criteria that their lengths should be greater than or equal to 60 nt and their corresponding protein sequences are without any stop codons. Furthermore, Nucleotide BLAST is used to verify the specificity of the conserved regions. As a result, we have obtained 17 conserved regions that belong to NSP3, NSP4, NSP6, NSP8, RdRp, Helicase, endoRNAse, 2'-O-RMT, Spike glycoprotein, ORF3a protein, Membrane glycoprotein and Nucleocapsid protein. Finally, these conserved regions are used to identify the T-cell and B-cell epitopes with their corresponding immunogenic and antigenic scores. Based on these scores, the most immunogenic and antigenic epitopes are then selected for each of these 17 conserved regions. Hence, we have obtained 30 MHC-I and 24 MHC-II restricted T-cell epitopes with 14 and 13 unique HLA alleles and 21 B-cell epitopes for the 17 conserved regions. Moreover, for validating the relevance of these epitopes, the binding conformation of the MHC-I and MHC-II restricted T-cell epitopes are shown with respect to HLA alleles. Also, the physico-chemical properties of the epitopes are reported along with Ramchandran plots and Z-Scores and the population coverage is shown as well. Overall, the analysis shows that the identified epitopes can be considered as potential candidates for vaccine design.

Lessons Learned from Cutting-Edge Immunoinformatics on Next-Generation COVID-19 Vaccine Research

Presently, immunoinformatics and bioinformatics approaches are contributing actively to COVID-19 vaccine research. The first immunoinformatics-based vaccine construct against SARS-CoV-2 was published in February 2020. Following this, immunoinformatics and bioinformatics approaches have created a new direction in COVID-19 vaccine research. Several researchers have designed the next-generation COVID-19 vaccines using these approaches. Presently, immunoinformatics has accelerated immunology research immensely in the area of COVID-19. Hence, we have tried to depict the current scenario of immunoinformatics and bioinformatics in COVID-19 vaccine research.

Plant-Based Phytochemical Screening by Targeting Main Protease of SARS-CoV-2 to Design Effective Potent Inhibitors

Currently, a worldwide pandemic has been declared in response to the spread of coronavirus disease 2019 (COVID-19), a fatal and fast-spreading viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The low availability of efficient vaccines and treatment options has resulted in a high mortality rate, bringing the world economy to its knees. Thus, mechanistic investigations of drugs capable of counteracting this disease are in high demand. The main protease (Mpro) expressed by SARS-CoV-2 has been targeted for the development of potential drug candidates due to the crucial role played by Mpro in viral replication and transcription. We generated a phytochemical library containing 1672 phytochemicals derived from 56 plants, which have been reported as having antiviral, antibacterial, and antifungal activity. A molecular docking program was used to screen the top three candidate compounds: epicatechin-3-O-gallate, psi-taraxasterol, and catechin gallate, which had respective binding affinities of -8.4, -8.5, and -8.8 kcal/mol. Several active sites in the targeted protein, including Cys145, His41, Met49, Glu66, and Met165, were found to interact with the top three candidate compounds. The multiple simulation profile, root-mean-square deviation, root-mean-square fluctuation, radius of gyration, and solvent-accessible surface area values supported the inflexible nature of the docked protein-compound complexes. The toxicity and carcinogenicity profiles were assessed, which showed that epicatechin-3-O-gallate, psi-taraxasterol, and catechin gallate had favorable pharmacological properties with no adverse effects. These findings suggest that these compounds could be developed as part of an effective drug development pathway to treat COVID-19.

A comprehensive review on global contributions and recognition of pharmacy professionals amidst COVID-19 pandemic: moving from present to future

BACKGROUND

COVID-19, a respiratory tract infection caused by SARS-CoV-2, is a burning question worldwide as it gives rise to a pandemic situation. No specific medications are still recommended for COVID-19; however, healthcare support is crucial for ameliorating the disease condition. Pharmacists are the frontline fighters who are responsible for providing healthcare support to the COVID-19 infected patients around the world. This review endeavored to briefly rationalize the contributions of several pharmacy professionals in diverse fields along with their collaborative efforts and dedication regarding their limitations during the COVID-19 situation and view the prospects of pharmaceutical care services in the post-pandemic period.

MAIN BODY OF THE ABSTRACT

Online databases were utilized to search for scholarly articles and organizational websites, to sum up the information about the contemporary and expanded role of pharmacists. Key articles were retrieved from Google Scholar, PubMed, and Science Direct databases using terms: "COVID-19," "novel coronavirus," "community," "industrial," "hospital," "clinical," "recognition," "obstacles," "collaboration," "SARS-CoV-2," "healthcare," and "outbreak" in combination with "pharmacist." The articles were included from the inception of the pandemic to January 25, 2021. The current review found pharmacist's global contributions and involvements with other professionals to provide healthcare services amidst COVID-19. This included testing of suspects, providing medical information, psycho-social support, debunking myths, mitigating drug shortage events, telemedicine, e-prescription, infection control, and controlling the drug supply chain. In many countries, pharmacists' activities were much appreciated but in some countries, they were not properly acknowledged for their contributions amidst COVID-19 outbreak. They played additional roles such as participating in the antimicrobial stewardship team, improving value-added services, conducting clinical data analysis to suppress the outspread of the SARS-CoV-2.

SHORT CONCLUSION

During the COVID-19 pandemic while the whole world is fighting against an invisible virus, the pharmacists are the earnest hero to serve their responsibilities along with additional activities. They need to be prepared and collaborate with other healthcare professionals further to meet the challenges of post-pandemic circumstances.

An Immunoinformatics Approach for SARS-CoV-2 in Latam Populations and Multi-Epitope Vaccine Candidate Directed towards the World's Population

The coronavirus pandemic is a major public health crisis affecting global health systems with dire socioeconomic consequences, especially in vulnerable regions such as Latin America (LATAM). There is an urgent need for a vaccine to help control contagion, reduce mortality and alleviate social costs. In this study, we propose a rational multi-epitope candidate vaccine against SARS-CoV-2. Using bioinformatics, we constructed a library of potential vaccine peptides, based on the affinity of the most common major human histocompatibility complex (HLA) I and II molecules in the LATAM population to predict immunological complexes among antigenic, non-toxic and non-allergenic peptides extracted from the conserved regions of 92 proteomes. Although HLA-C, had the greatest antigenic peptide capacity from SARS-CoV-2, HLA-B and HLA-A, could be more relevant based on COVID-19 risk of infection in LATAM countries. We also used three-dimensional structures of SARS-CoV-2 proteins to identify potential regions for antibody production. The best HLA-I and II predictions (with increased coverage in common alleles and regions evoking B lymphocyte responses) were grouped into an optimized final multi-epitope construct containing the adjuvants Beta defensin-3, TpD, and PADRE, which are recognized for invoking a safe and specific immune response. Finally, we used Molecular Dynamics to identify the multi-epitope construct which may be a stable target for TLR-4/MD-2. This would prove to be safe and provide the physicochemical requirements for conducting experimental tests around the world.

Appraisals of the Bangladeshi Medicinal Plant Calotropis gigantea Used by Folk Medicine Practitioners in the Management of COVID-19: A Biochemical and Computational Approach

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was first recognized in Wuhan in late 2019 and, since then, had spread globally, eventually culminating in the ongoing pandemic. As there is a lack of targeted therapeutics, there is certain opportunity for the scientific community to develop new drugs or vaccines against COVID-19 and so many synthetic bioactive compounds are undergoing clinical trials. In most of the countries, due to the broad therapeutic spectrum and minimal side effects, medicinal plants have been used widely throughout history as traditional healing remedy. Because of the unavailability of synthetic bioactive antiviral drugs, hence all possible efforts have been focused on the search for new drugs and alternative medicines from different herbal formulations. In recent times, it has been assured that the Mpro, also called 3CLpro, is the SARS-CoV-2 main protease enzyme responsible for viral reproduction and thereby impeding the host's immune response. As such, Mpro represents a highly specified target for drugs capable of inhibitory action against coronavirus disease 2019 (COVID-19). As there continue to be no clear options for the treatment of COVID-19, the identification of potential candidates has become a necessity. The present investigation focuses on the in silico pharmacological activity of Calotropis gigantea, a large shrub, as a potential option for COVID-19 Mpro inhibition and includes an ADME/T profile analysis of that ligand. For this study, with the help of gas chromatography-mass spectrometry analysis of C. gigantea methanolic leaf extract, a total of 30 bioactive compounds were selected. Our analyses unveiled the top four options that might turn out to be prospective anti-SARS-CoV-2 lead molecules; these warrant further exploration as well as possible application in processes of drug development to combat COVID-19.

How to face COVID-19: proposed treatments based on remdesivir and hydroxychloroquine in the presence of zinc sulfate. Docking/DFT/POM structural analysis

Remdesivir and hydroxychloroquine derivatives form two important classes of heterocyclic compounds. They are known for their anti-malarial biological activity. This research aims to analyze the physicochemical properties of remdesivir and hydroxychloroquine compounds by the computational approach. DFT, docking, and POM analyses also identify antiviral pharmacophore sites of both compounds. The antiviral activity of hydroxychloroquine compound's in the presence of zinc sulfate and azithromycin is evaluated through its capacity to coordinate transition metals (M = Cu, Ni, Zn, Co, Ru, Pt). The obtained bioinformatic results showed the potent antiviral/antibacterial activity of the prepared mixture (Hydroxychloroquine/Azithromycin/Zinc sulfate) for all the opportunistic Gram-positive, Gram-negative in the presence of coronavirus compared with the complexes Polypyridine-Ruthenium-di-aquo. The postulated zinc(II) complex of hydroxychloroquine derivatives are indeed an effective antibacterial and antiviral agent against coronavirus and should be extended to other pathogens. The combination of a pharmacophore site with a redox [Metal(OH₂)₂] moiety is of crucial role to fight against viruses and bacteria strains. [Formula: see text]Communicated by Ramaswamy H. Sarma.

Immunoinformatics-guided design of a multi-epitope vaccine based on the structural proteins of severe acute respiratory syndrome coronavirus 2

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), resulting in a contagious respiratory tract infection that has become a global burden since the end of 2019. Notably, fewer patients infected with SARS-CoV-2 progress from acute disease onset to death compared with the progression rate associated with two other coronaviruses, SARS-CoV and Middle East respiratory syndrome coronavirus (MERS-CoV). Several research organizations and pharmaceutical industries have attempted to develop successful vaccine candidates for the prevention of COVID-19. However, increasing evidence indicates that the SARS-CoV-2 genome undergoes frequent mutation; thus, an adequate analysis of the viral strain remains necessary to construct effective vaccines. The current study attempted to design a multi-epitope vaccine by utilizing an approach based on the SARS-CoV-2 structural proteins. We predicted the antigenic T- and B-lymphocyte responses to four structural proteins after screening all structural proteins according to specific characteristics. The predicted epitopes were combined using suitable adjuvants and linkers, and a secondary structure profile indicated that the vaccine shared similar properties with the native protein. Importantly, the molecular docking analysis and molecular dynamics simulations revealed that the constructed vaccine possessed a high affinity for toll-like receptor 4 (TLR4). In addition, multiple descriptors were obtained from the simulation trajectories, including the root-mean-square deviation (RMSD), root-mean-square fluctuation (RMSF), solvent-accessible surface area (SASA), and radius of gyration (R g), demonstrating the rigid nature and inflexibility of the vaccine and receptor molecules. In addition, codon optimization, based on Escherichia coli K12, was used to determine the GC content and the codon adaptation index (CAI) value, which further followed for the incorporation into the cloning vector pET28+(a). Collectively, these findings suggested that the constructed vaccine could be used to modulate the immune reaction against SARS-CoV-2.

Prospective Role of Peptide-Based Antiviral Therapy Against the Main Protease of SARS-CoV-2

The recently emerged coronavirus (SARS-CoV-2) has created a crisis in world health, and economic sectors as an effective treatment or vaccine candidates are still developing. Besides, negative results in clinical trials and effective cheap solution against this deadly virus have brought new challenges. The viral protein, the main protease from SARS-CoV-2, can be effectively targeted due to its viral replication and pathogenesis role. In this study, we have enlisted 88 peptides from the AVPdb database. The peptide molecules were modeled to carry out the docking interactions. The four peptides molecules, P14, P39, P41, and P74, had more binding energy than the rest of the peptides in multiple docking programs. Interestingly, the active points of the main protease from SARS-CoV-2, Cys145, Leu141, Ser139, Phe140, Leu167, and Gln189, showed nonbonded interaction with the peptide molecules. The molecular dynamics simulation study was carried out for 200 ns to find out the docked complex’s stability where their stability index was proved to be positive compared to the apo and control complex. Our computational works based on peptide molecules may aid the future development of therapeutic options against SARS-CoV-2.

Diverse Immunological Factors Influencing Pathogenesis in Patients with COVID-19: A Review on Viral Dissemination, Immunotherapeutic Options to Counter Cytokine Storm and Inflammatory Responses

The pathogenesis of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is still not fully unraveled. Though preventive vaccines and treatment methods are out on the market, a specific cure for the disease has not been discovered. Recent investigations and research studies primarily focus on the immunopathology of the disease. A healthy immune system responds immediately after viral entry, causing immediate viral annihilation and recovery. However, an impaired immune system causes extensive systemic damage due to an unregulated immune response characterized by the hypersecretion of chemokines and cytokines. The elevated levels of cytokine or hypercytokinemia leads to acute respiratory distress syndrome (ARDS) along with multiple organ damage. Moreover, the immune response against SARS-CoV-2 has been linked with race, gender, and age; hence, this viral infection's outcome differs among the patients. Many therapeutic strategies focusing on immunomodulation have been tested out to assuage the cytokine storm in patients with severe COVID-19. A thorough understanding of the diverse signaling pathways triggered by the SARS-CoV-2 virus is essential before contemplating relief measures. This present review explains the interrelationships of hyperinflammatory response or cytokine storm with organ damage and the disease severity. Furthermore, we have thrown light on the diverse mechanisms and risk factors that influence pathogenesis and the molecular pathways that lead to severe SARS-CoV-2 infection and multiple organ damage. Recognition of altered pathways of a dysregulated immune system can be a loophole to identify potential target markers. Identifying biomarkers in the dysregulated pathway can aid in better clinical management for patients with severe COVID-19 disease. A special focus has also been given to potent inhibitors of proinflammatory cytokines, immunomodulatory and immunotherapeutic options to ameliorate cytokine storm and inflammatory responses in patients affected with COVID-19.

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

The current dynamics of the COVID-19 pandemic have become a serious concern with the emergence of a series of mutant variants of the SARS-CoV-2 virus. Unlike the previous strain, it is reported that the descendants are associated with increased risk of transmission yet causing less impact in terms of hospital admission, the severity of illness, or mortality. Moreover, the vaccine efficacy is also not believed to vary among the population depending on the variants of the virus and ethnicity. It has been determined that the mutations recorded in the spike gene and protein of the newly evolved viruses are specificallyresponsible for this transformation in the behavior of the virus and its disease condition. Hence, this study aimed to compare the immunogenic profiles of the spike protein from the latest variants of the SARS-CoV-2 virus concerning the probability of COVID-19 severity. Genome sequences of the latest SARS-CoV-2 variants were obtained from GISAID and NCBI repositories. The translated protein sequences were run against T-cell and B-cell epitope prediction tools. Subsequently, antigenicity, immunogenicity, allergenicity, toxicity, and conservancy of the identified epitopes were ascertained using various prediction servers. Only the non-allergic and non-toxic potential epitopes were matched for population relevance by using the Human Leucocyte Antigen population registry in IEDB. Finally, the selected epitopes were validated by docking and simulation studies. The evaluated immunological parameters would concurrently reveal the severity of COVID-19, determining the infection rate of the pathogen. Our immunoinformatics approach disclosed that spike protein of the five variants was capable of forming potential T and B-cell epitopes with varying immune responses. Although the Wuhan strain showed a high number of epitope/HLA combinations, relatively less antigenicity and higher immunogenicity results in poor neutralizing capacity, which could be associated with increased disease severity. Our data demonstrate that increased viral antigenicity with moderate to high immunogenicity, and several potential epitope/HLA combinations in England strain, the USA, India, and South Africa variants, could possess a high neutralizing ability. Therefore, our findings reinforce that the newly circulating variants of SARS-CoV-2 might be associated with more infectiousness and less severe disease condition despite their greater viremia, as reported in the recent COVID-19 cases, whichconsequently determine their increased epidemiological fitness.

Role of Inflammatory Cytokines in COVID-19 Patients: A Review on Molecular Mechanisms, Immune Functions, Immunopathology and Immunomodulatory Drugs to Counter Cytokine Storm

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a severe pandemic of the current century. The vicious tentacles of the disease have been disseminated worldwide with unknown complications and repercussions. Advanced COVID-19 syndrome is characterized by the uncontrolled and elevated release of pro-inflammatory cytokines and suppressed immunity, leading to the cytokine storm. The uncontrolled and dysregulated secretion of inflammatory and pro-inflammatory cytokines is positively associated with the severity of the viral infection and mortality rate. The secretion of various pro-inflammatory cytokines such as TNF-α, IL-1, and IL-6 leads to a hyperinflammatory response by recruiting macrophages, T and B cells in the lung alveolar cells. Moreover, it has been hypothesized that immune cells such as macrophages recruit inflammatory monocytes in the alveolar cells and allow the production of large amounts of cytokines in the alveoli, leading to a hyperinflammatory response in severely ill patients with COVID-19. This cascade of events may lead to multiple organ failure, acute respiratory distress, or pneumonia. Although the disease has a higher survival rate than other chronic diseases, the incidence of complications in the geriatric population are considerably high, with more systemic complications. This review sheds light on the pivotal roles played by various inflammatory markers in COVID-19-related complications. Different molecular pathways, such as the activation of JAK and JAK/STAT signaling are crucial in the progression of cytokine storm; hence, various mechanisms, immunological pathways, and functions of cytokines and other inflammatory markers have been discussed. A thorough understanding of cytokines' molecular pathways and their activation procedures will add more insight into understanding immunopathology and designing appropriate drugs, therapies, and control measures to counter COVID-19. Recently, anti-inflammatory drugs and several antiviral drugs have been reported as effective therapeutic drug candidates to control hypercytokinemia or cytokine storm. Hence, the present review also discussed prospective anti-inflammatory and relevant immunomodulatory drugs currently in various trial phases and their possible implications.

Predicting COVID-19 Severity with a Specific Nucleocapsid Antibody plus Disease Risk Factor Score

Effective methods for predicting COVID-19 disease trajectories are urgently needed. Here, enzyme-linked immunosorbent assay (ELISA) and coronavirus antigen microarray (COVAM) analysis mapped antibody epitopes in the plasma of COVID-19 patients (n = 86) experiencing a wide range of disease states. The experiments identified antibodies to a 21-residue epitope from nucleocapsid (termed Ep9) associated with severe disease, including admission to the intensive care unit (ICU), requirement for ventilators, or death. Importantly, anti-Ep9 antibodies can be detected within 6 days post-symptom onset and sometimes within 1 day. Furthermore, anti-Ep9 antibodies correlate with various comorbidities and hallmarks of immune hyperactivity. We introduce a simple-to-calculate, disease risk factor score to quantitate each patient's comorbidities and age. For patients with anti-Ep9 antibodies, scores above 3.0 predict more severe disease outcomes with a 13.42 likelihood ratio (96.7% specificity). The results lay the groundwork for a new type of COVID-19 prognostic to allow early identification and triage of high-risk patients. Such information could guide more effective therapeutic intervention.IMPORTANCE The COVID-19 pandemic has resulted in over two million deaths worldwide. Despite efforts to fight the virus, the disease continues to overwhelm hospitals with severely ill patients. Diagnosis of COVID-19 is readily accomplished through a multitude of reliable testing platforms; however, prognostic prediction remains elusive. To this end, we identified a short epitope from the SARS-CoV-2 nucleocapsid protein and also a disease risk factor score based upon comorbidities and age. The presence of antibodies specifically binding to this epitope plus a score cutoff can predict severe COVID-19 outcomes with 96.7% specificity.

Immunoinformatics approach for multi-epitope vaccine design against P. falciparum malaria

Plasmodium falciparum (P. falciparum) is a leading causative agent of malaria, an infectious disease that can be fatal. Unfortunately, control measures are becoming less effective over time. A vaccine is needed to effectively control malaria and lead towards the total elimination of the disease. There have been multiple attempts to develop a vaccine, but to date, none have been certified as appropriate for wide-scale use. In this study, an immunoinformatics method is presented to design a multi-epitope vaccine construct predicted to be effective against P. falciparum malaria. This was done through the prediction of 12 CD4+ T-cell, 10 CD8+ T-cell epitopes and, 1 B-cell epitope which were assessed for predicted high antigenicity, immunogenicity, and non-allergenicity through in silico methods. The Human Leukocyte Antigen (HLA) population coverage showed that the alleles associated with the epitopes accounted for 78.48% of the global population. The CD4+ and CD8+ T-cell epitopes were docked to HLA-DRB1*07:01 and HLA-A*32:01 successfully. Therefore, the epitopes were deemed to be suitable as components of a multi-epitope vaccine construct. Adjuvant RS09 was added to the construct to generate a stronger immune response, as confirmed by an immune system simulation. Finally, the structural stability of the predicted multi-epitope vaccine was assessed using molecular dynamics simulations. The results show a promising vaccine design that should be further synthesised and assessed for its efficacy in an experimental laboratory setting.

Efficacy of Phytochemicals Derived from Avicennia officinalis for the Management of COVID-19: A Combined In Silico and Biochemical Study

The recent coronavirus disease 2019 (COVID-19) pandemic is a global threat for healthcare management and the economic system, and effective treatments against the pathogenic severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus responsible for this disease have not yet progressed beyond the developmental phases. As drug refinement and vaccine progression require enormously broad investments of time, alternative strategies are urgently needed. In this study, we examined phytochemicals extracted from Avicennia officinalis and evaluated their potential effects against the main protease of SARS-CoV-2. The antioxidant activities of A. officinalis leaf and fruit extracts at 150 µg/mL were 95.97% and 92.48%, respectively. Furthermore, both extracts displayed low cytotoxicity levels against Artemia salina. The gas chromatography-mass spectroscopy analysis confirmed the identifies of 75 phytochemicals from both extracts, and four potent compounds, triacontane, hexacosane, methyl linoleate, and methyl palminoleate, had binding free energy values of -6.75, -6.7, -6.3, and -6.3 Kcal/mol, respectively, in complexes with the SARS-CoV-2 main protease. The active residues Cys145, Met165, Glu166, Gln189, and Arg188 in the main protease formed non-bonded interactions with the screened compounds. The root-mean-square difference (RMSD), root-mean-square fluctuations (RMSF), radius of gyration (Rg), solvent-accessible surface area (SASA), and hydrogen bond data from a molecular dynamics simulation study confirmed the docked complexes' binding rigidity in the atomistic simulated environment. However, this study's findings require in vitro and in vivo validation to ensure the possible inhibitory effects and pharmacological efficacy of the identified compounds.

A molecular modelling approach for identifying antiviral selenium-containing heterocyclic compounds that inhibit the main protease of SARS-CoV-2: an in silico investigation

Coronavirus disease 2019 (COVID-19), an infectious disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been declared a global pandemic by the World Health Organization, and the situation worsens daily, associated with acute increases in case fatality rates. The main protease (Mpro) enzyme produced by SARS-CoV-2 was recently demonstrated to be responsible for not only viral reproduction but also impeding host immune responses. The element selenium (Se) plays a vital role in immune functions, both directly and indirectly. Thus, we hypothesised that Se-containing heterocyclic compounds might curb the activity of SARS-CoV-2 Mpro. We performed a molecular docking analysis and found that several of the selected selenocompounds showed potential binding affinities for SARS-CoV-2 Mpro, especially ethaselen (49), which exhibited a docking score of -6.7 kcal/mol compared with the -6.5 kcal/mol score for GC376 (positive control). Drug-likeness calculations suggested that these compounds are biologically active and possess the characteristics of ideal drug candidates. Based on the binding affinity and drug-likeness results, we selected the 16 most effective selenocompounds as potential anti-COVID-19 drug candidates. We also validated the structural integrity and stability of the drug candidate through molecular dynamics simulation. Using further in vitro and in vivo experiments, we believe that the targeted compound identified in this study (ethaselen) could pave the way for the development of prospective drugs to combat SARS-CoV-2 infections and trigger specific host immune responses.

Exploration and validation of related hub gene expression during SARS-CoV-2 infection of human bronchial organoids

Background

In the novel coronavirus pandemic, the high infection rate and high mortality have seriously affected people’s health and social order. To better explore the infection mechanism and treatment, the three-dimensional structure of human bronchus has been employed in a better in-depth study on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Methods

We downloaded a separate microarray from the Integrated Gene Expression System (GEO) on a human bronchial organoids sample to identify differentially expressed genes (DEGS) and analyzed it with R software. After processing with R software, Gene Ontology (GO) and Kyoto PBMCs of Genes and Genomes (KEGG) were analyzed, while a protein–protein interaction (PPI) network was constructed to show the interactions and influence relationships between these differential genes. Finally, the selected highly connected genes, which are called hub genes, were verified in CytoHubba plug-in.

Results

In this study, a total of 966 differentially expressed genes, including 490 upregulated genes and 476 downregulated genes were used. Analysis of GO and KEGG revealed that these differentially expressed genes were significantly enriched in pathways related to immune response and cytokines. We construct protein-protein interaction network and identify 10 hub genes, including IL6, MMP9, IL1B, CXCL8, ICAM1, FGF2, EGF, CXCL10, CCL2, CCL5, CXCL1, and FN1. Finally, with the help of GSE150728, we verified that CXCl1, CXCL8, CXCL10, CCL5, EGF differently expressed before and after SARS-CoV-2 infection in clinical patients.

Conclusions

In this study, we used mRNA expression data from GSE150819 to preliminarily confirm the feasibility of hBO as an in vitro model to further study the pathogenesis and potential treatment of COVID-19. Moreover, based on the mRNA differentiated expression of this model, we found that CXCL8, CXCL10, and EGF are hub genes in the process of SARS-COV-2 infection, and we emphasized their key roles in SARS-CoV-2 infection. And we also suggested that further study of these hub genes may be beneficial to treatment, prognostic prediction of COVID-19.