Immunoinformatics and molecular modeling approach to design universal multi-epitope vaccine for SARS-CoV-2

Designing a multi-epitope universal vaccine for concurrent infections of SARS-CoV-2 and influenza viruses using an immunoinformatics approach

BACKGROUND

Severe acute respiratory syndrome coronavirus 2 (SARS‑CoV‑2) and influenza viruses share several conserved epitopes that can be utilized for the development of universal vaccines. Our previous research demonstrated that recombinant M2e-HA2 (Matrix-2 ectodomain-Hemagglutinin subunit 2) proteins derived from influenza elicited an immune response against the virus, suggesting their potential use in universal influenza vaccine formulations. Given the lack of a specific vaccine to address SARS‑CoV‑2 and influenza co-infections, this study aimed to design a universal vaccine using immunoinformatics methodologies.

METHODS

In this study, B-cell and T-cell epitopes were identified from the nucleocapsid (N) protein of SARS‑CoV‑2. Additionally, the N-terminal segments of M2e (SLLTEVET) and HA2 (GLFGAIAGF) from influenza were incorporated to construct a multi-epitope vaccine. Suitable linkers were designed, and human beta-defensin-2 was selected as an adjuvant. Further evaluations were conducted, focusing on key parameters such as stability, allergenicity, and antigenicity.

RESULTS

The major histocompatibility complex (MHC) class I and II binding epitopes exhibited broad population coverage for the vaccine on a global scale. The vaccine structure was found to interact with toll-like receptor 3 (TLR-3), and the docked conformation of the vaccine/TLR-3 complex demonstrated high stability during molecular dynamics (MD) simulations. The constructed vaccine exhibited thermal stability across cold, ambient, and human body temperatures. Additionally, in silico cloning of the vaccine candidate into the pET-28a(+) vector was performed to facilitate production within the Escherichia coli expression system.

CONCLUSION

Overall, the findings suggest that the designed vaccine has the potential to serve as an effective universal vaccine and a promising strategy for controlling both Coronavirus disease 2019 (COVID-19) and influenza on a global scale.

Subtractive proteomics and reverse-vaccinology approaches for novel drug targets and designing a chimeric vaccine against Ruminococcus gnavus strain RJX1120

Mediterraneibacter gnavus, also known as Ruminococcus gnavus, is a Gram-positive anaerobic bacterium that resides in the human gut microbiota. Notably, this bacterium plays dual roles in health and disease. On one side it supports nutrient metabolism essential for bodily functions and on the other it contributes to the development of Inflammatory Bowel Disease (IBD) and other gastrointestinal disorders. R. gnavus strain RJX1120 is an encapsulated strain and has been linked to develop IBD. Despite the advances made on its role in gut homeostasis, limited information is available on strain-specific virulence factors, metabolic pathways, and regulatory mechanisms. The study of such aspects is crucial to make microbiota-targeted therapy and understand its implications in host health. A multi-epitope vaccine against R. gnavus strain RJX1120 was designed using reverse vaccinology-based subtractive proteomics approach. Among the 3,219 proteins identified in the R. gnavus strain RJX1120, two critical virulent and antigenic proteins, a Single-stranded DNA-binding protein SSB (A0A2N5PT08) and Cell division ATP-binding protein FtsE (A0A2N5NK05) were screened and identified as potential targets. The predicted B-cell and T-cell epitopes from these proteins were screened for essential immunological properties such as antigenicity, allergenicity, solubility, MHC binding affinity, and toxicity. Epitopes chosen were cross-linked using suitable spacers and an adjuvant to develop a multi-epitope vaccine. Structural refinement of the construct revealed that 95.7% of the amino acid residues were located in favored regions, indicating a high-quality structural model. Molecular docking analysis demonstrated a robust interaction between the vaccine construct and the human Toll-like receptor 4 (TLR4), with a binding energy of -1277.0 kcal/mol. The results of molecular dynamics simulations further confirmed the stability of the vaccine-receptor complex under physiological conditions. In silico cloning of the vaccine construct yielded a GC content of 48% and a Codon Adaptation Index (CAI) value of 1.0, indicating optimal expression in the host system. These results indicate the possibility of the designed vaccine construct as a candidate for the prevention of R. gnavus-associated diseases. However, experimental validation is required to confirm its immunogenicity and protective efficacy.

Immunoinformatics based designing of a multi-epitope cancer vaccine targeting programmed cell death ligand 1

Tumor cells express programmed cell death ligand 1 (PD-L1), which recognizes the immune checkpoint molecule programmed cell death 1 (PD-1) on T cells, suppressing the antitumor immune response. Inhibiting the PD-1:PD-L1 interaction has the potential to reactivate the immune response against tumors. Recent advancements in cancer therapy have demonstrated remarkable promise of immunotherapy, which exploits immune checkpoint inhibition by small molecules or monoclonal antibodies. This strategy has shown impressive clinical success in treating a wide range of cancer subtypes, albeit with certain limitations. This study aims to design a novel multi-epitope vaccine against PD-L1 by using an immunoinformatics approach. For attaining enhanced efficacy and minimize side effects, the vaccine was constructed using antigenic, non-allergenic, and non-toxic epitopes (5 CTL, 3 HTL, and 2 B-cell epitopes) predicted from the IgV domain of PD-L1. The vaccine design includes a large ribosomal subunit protein bL12 adjuvant, a 6xHis tag for purification, and appropriate linkers to connect the epitopes. The modelled 3D structure of the vaccine construct was docked with TLR4 immune receptor, demonstrating strong antigenic properties and stable binding, as validated by molecular dynamics simulations. Immune simulation studies suggest that the vaccine construct could potentially elicit significant immune regulators such as B cells, T-cells, and memory cells. Thus, the findings indicate that the vaccine may effectively suppress the PD-1:PD-L1 axis by targeting PD-L1, restoring the anticancer immune response. However, its efficacy needs to be validated in both in vitro and in vivo settings.

Multi-epitope Based Peptide Vaccine Candidate Against Babesia Infection From Rhoptry-Associated Protein 1 (RAP-1) Antigen Using Immuno-Informatics: An In Silico Approach

Objective

Babesiosis is a significant haemoparasitic infection caused by apicomplexan parasites of the genus Babesia. This infection has continuously threatened cattle farmers owing to its devastating effects on productivity and severe economic implications. Failure to curb the increase of the infection has been attributed to largely ineffective vaccines. This study was designed to develop a potential vaccine candidate.

Method

Rhoptry-associated protein-1 (RAP-1) was used to identify and design a potential multi-epitope vaccine candidate due to its immunogenic properties through an immunoinformatics approach.

Results and conclusions

A multi-epitope vaccine comprising 11 CD8+, 17 CD4+, and 3 B-cell epitopes was constructed using the AAY, GPGPG, and KK linkers. Beta-defensin-3 was added as an adjuvant to potentiate the immune response using the EAAK linker. The designed vaccine was computationally predicted to be antigenic (antigenicity scores: 0.6), soluble (solubility index: 0.730), and non-allergenic. The vaccine construct comprises 595 amino acids with a molecular weight of 64 152 kDa, an instability and aliphatic index of 13.89 and 65.82, which confers stability with a Grand average of hydropathicity (GRAVY) value of 0.122, indicating the hydrophobicity of the construct. Europe has the highest combined class population coverage, with a percentage of 96.07%, while Central America has the lowest population coverage, with a value of 22.94%. The DNA sequence of the vaccine construct was optimized and successfully cloned into a pET-28a (+) plasmid vector. Analysis of binding interactions indicated the stability of the complex when docked with Toll-like receptor-2 (TLR-2). The subunit vaccine construct was predicted to induce and boost sufficient host cellular and humoral responses in silico. However, further experimental research and analysis is required to validate the findings.

Limitation

This study is purely computational, and further experimental validation of these findings through in vivo and in vitro conditions is required.

Novel SARS-COV2 poly epitope phage-based candidate vaccine and its immunogenicity

Background and purpose

The global emergence of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has prompted widespread concern. Bacteriophages have recently gained attention as a cost-effective and stable alternative for vaccine development due to their adjuvant properties. This study aimed to design and validate a poly epitope composed of viral proteins.

Experimental approach

SARS-CoV-2 proteins (spike, nucleocapsid, membrane, envelope, papain-like protease, and RNA-dependent RNA polymerase) were selected for analysis. Immunoinformatic methods were employed to predict B and T cell epitopes, assessing their antigenicity, allergenicity, and toxicity. Epitopes meeting criteria for high antigenicity, non-allergenicity, and non-toxicity were linked to form poly epitopes. These sequences were synthesized and cloned into pHEN4 plasmids to generate Poly1 and Poly2 phagemid vectors. Recombinant Poly1 and Poly2 phages were produced by transforming M13ΔIII plasmids and phagemid vectors into E. coli TG1. Female Balb/c mice were immunized with a cocktail of Poly1 and Poly2 phages, and their serum was collected for ELISA testing. Interferon-gamma (IFN-γ) testing was performed on spleen-derived lymphocytes to evaluate immune system activation.

Findings/Results

Recombinant Poly1 and Poly2 phages were produced, and their titer was determined as 1013 PFU/mL. Efficient humoral immune responses and cellular immunity activation in mice were achieved following phage administration.

Conclusion and implication

Poly epitopes displayed on phages exhibit adjuvant properties, enhancing humoral and cellular immunity in mice. This suggests that phages could serve as adjuvants to bolster immunity against SARS-Cov-2. Recombinant phages could be applied as effective candidates for injectable and oral vaccine development strategies.

Design of multivalent-epitope vaccine models directed toward the world's population against HIV-Gag polyprotein: Reverse vaccinology and immunoinformatics

Significant progress has been made in HIV-1 research; however, researchers have not yet achieved the objective of eradicating HIV-1 infection. Accordingly, in this study, eucaryotic and procaryotic in silico vaccines were developed for HIV-Gag polyproteins from 100 major HIV subtypes and CRFs using immunoinformatic techniques to simulate immune responses in mice and humans. The epitopes located in the conserved domains of the Gag polyprotein were evaluated for allergenicity, antigenicity, immunogenicity, toxicity, homology, topology, and IFN-γ induction. Adjuvants, linkers, CTLs, HTLs, and BCL epitopes were incorporated into the vaccine models. Strong binding affinities were detected between HLA/MHC alleles, TLR-2, TLR-3, TLR-4, TLR-7, and TLR-9, and vaccine models. Immunological simulation showed that innate and adaptive immune cells elicited active and consistent responses. The human vaccine model was matched with approximately 93.91% of the human population. The strong binding of the vaccine to MHC/HLA and TLR molecules was confirmed through molecular dynamic stimulation. Codon optimization ensured the successful translation of the designed constructs into human cells and E. coli hosts. We believe that the HIV-1 Gag vaccine formulated in our research can reduce the challenges faced in developing an HIV-1 vaccine. Nevertheless, experimental verification is necessary to confirm the effectiveness of these vaccines in these models.

Reverse vaccinology approaches to design a potent multiepitope vaccine against the HIV whole genome: immunoinformatic, bioinformatics, and molecular dynamics approaches

Substantial advances have been made in the development of promising HIV vaccines to eliminate HIV-1 infection. For the first time, one hundred of the most submitted HIV subtypes and CRFs were retrieved from the LANL database, and the consensus sequences of the eleven HIV proteins were obtained to design vaccines for human and mouse hosts. By using various servers and filters, highly qualified B-cell epitopes, as well as HTL and CD8 + epitopes that were common between mouse and human alleles and were also located in the conserved domains of HIV proteins, were considered in the vaccine constructs. With 90% coverage worldwide, the human vaccine model covers a diverse allelic population, making it widely available. Codon optimization and in silico cloning in prokaryotic and eukaryotic vectors guarantee high expression of the vaccine models in human and E. coli hosts. Molecular dynamics confirmed the stable interaction of the vaccine constructs with TLR3, TLR4, and TLR9, leading to a substantial immunogenic response to the designed vaccine. Vaccine models effectively target the humoral and cellular immune systems in humans and mice; however, experimental validation is needed to confirm these findings in silico.

Engineering receptor-binding domain and heptad repeat domains towards the development of multi-epitopes oral vaccines against SARS-CoV-2 variants

The inability of existing vaccines to cope with the mutation rate has highlighted the need for effective preventative strategies for COVID-19. Through the secretion of immunoglobulin A, mucosal delivery of vaccines can effectively stimulate mucosal immunity for better protection against SARS-CoV-2 infection. In this study, various immunoinformatic tools were used to design a multi-epitope oral vaccine against SARS-CoV-2 based on its receptor-binding domain (RBD) and heptad repeat (HR) domains. T and B lymphocyte epitopes were initially predicted from the RBD and HR domains of SARS-CoV-2, and potential antigenic, immunogenic, non-allergenic, and non-toxic epitopes were identified. Epitopes that are highly conserved and have no significant similarity to human proteome were selected. The epitopes were joined with appropriate linkers, and an adjuvant was added to enhance the vaccine efficacy. The vaccine 3D structure constructs were docked with toll-like receptor 4 (TLR-4) and TLR1-TLR2, and the binding affinity was calculated. The designed multi-epitope vaccine construct (MEVC) consisted of 33 antigenic T and B lymphocyte epitopes. The results of molecular dockings and free binding energies confirmed that the MEVC effectively binds to TLR molecules, and the complexes were stable. The results suggested that the designed MEVC is a potentially safe and effective oral vaccine against SARS-CoV-2. This in silico study presents a novel approach for creating an oral multi-epitope vaccine against the rapidly evolving SARS-CoV-2 variants. These findings offer valuable insights for developing an effective strategy to combat COVID-19. Further preclinical and clinical studies are required to confirm the efficacy of the MEVC vaccine.

Structure and dynamics of whole-sequence homology model of ORF3a protein of SARS-CoV-2: An insight from microsecond molecular dynamics simulations

The ORF3a is a large accessory protein in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which plays an important role in virulence and viral replication; especially in inflammasome activation and apoptosis. However,, the existing cryo-EM structure of SARS-CoV-2 ORF3a is incomplete, . making it challenging to understand its structural and functional features. The aim of this study is to investigate the dynamic behaviors of the full-sequence homology model of ORF3a and compare it with the cryo-EM structure using microsecond molecular dynamics simulations. The previous studies indicated that the unresolved residues of the cryo-EM structure are not only involved in the pathogenesis of the SARS-CoV-2 but also exhibit a significant antigenicity. The dynamics scenario of homology model revealed higher RMSD, Rg, and SASA values with stable pattern when compared to the cryo-EM structure. Moreover, the RMSF analysis demonstrated higher fluctuations at specific positions (1-43, 97-110, 172-180, 219-243) in the model structure, whereas the cryo-EM structure displayed lower overall drift (except 1-43) in comparison to the model structure.Secondary structural features indicated that a significant unfolding in the transmembrane domains and β-strand at positions 166 to 172, affecting the stability and compactness of the cryo-EM structure , whereas the model exhibited noticeable unfolding in transmembrane domains and small-coiled regions in the N-terminal. , The results from molecular docking and steered molecular dynamics investigations showed the model structure had a greater number of non-bonding interactions, leading to enhanced stability when compared to the cryo-EM structure. Consequently, higher forces were necessary for unbinding of the baricitinib and ruxolitinib inhibitors from the model structure.. Our findings can help better understanding of the significance of unresolved residues at the molecular level. Additionally, this information can guide researchers for experimental endeavors aimed at completing the full-sequence structure of the ORF3a.Communicated by Ramaswamy H. Sarma.

Immuno-informatics study identifies conserved T cell epitopes in non-structural proteins of Bluetongue virus serotypes: formulation of a computationally optimized next-generation broad-spectrum multi-epitope vaccine

Introduction

Bluetongue (BT) poses a significant threat to the livestock industry, affecting various animal species and resulting in substantial economic losses. The existence of numerous BT virus (BTV) serotypes has hindered control efforts, highlighting the need for broad-spectrum vaccines.

Methodology

In this study, we evaluated the conserved amino acid sequences within key non-structural (NS) proteins of BTV and identified numerous highly conserved murine- and bovine-specific MHC class I-restricted (MHC-I) CD8+ and MHC-II-restricted CD4+ epitopes. We then screened these conserved epitopes for antigenicity, allergenicity, toxicity, and solubility. Using these epitopes, we developed in silico-based broad-spectrum multiepitope vaccines with Toll-like receptor (TLR-4) agonists. The predicted proinflammatory cytokine response was assessed in silico using the C-IMMSIM server. Structural modeling and refinement were achieved using Robetta and GalaxyWEB servers. Finally, we assessed the stability of the docking complexes through extensive 100-nanosecond molecular dynamics simulations before considering the vaccines for codon optimization and in silico cloning.

Results

We found many epitopes that meet these criteria within NS1 and NS2 proteins and developed in silico broad-spectrum vaccines. The immune simulation studies revealed that these vaccines induce high levels of IFN-γ and IL-2 in the vaccinated groups. Protein-protein docking analysis demonstrated promising epitopes with strong binding affinities to TLR-4. The docked complexes were stable, with minimal Root Mean Square Deviation and Root Mean Square Fluctuation values. Finally, the in silico-cloned plasmids have high % of GC content with > 0.8 codon adaptation index, suggesting they are suitable for expressing the protein vaccines in prokaryotic system.

Discussion

These next-generation vaccine designs are promising and warrant further investigation in wet lab experiments to assess their immunogenicity, safety, and efficacy for practical application in livestock. Our findings offer a robust framework for developing a comprehensive, broad-spectrum vaccine, potentially revolutionizing BT control and prevention strategies in the livestock industry.

Designing a Conserved Immunogenic Peptide Construct from the Nucleocapsid Protein of Puumala orthohantavirus

Puumala orthohantavirus (PUUV) is an emerging zoonotic virus endemic to Europe and Russia that causes nephropathia epidemica, a mild form of hemorrhagic fever with renal syndrome (HFRS). There are limited options for treatment and diagnosis of orthohantavirus infection, making the search for potential immunogenic candidates crucial. In the present work, various bioinformatics tools were employed to design conserved immunogenic peptides containing multiple epitopes of PUUV nucleocapsid protein. Eleven conserved peptides (90% conservancy) of the PUUV nucleocapsid protein were identified. Three conserved peptides containing multiple T and B cell epitopes were selected using a consensus epitope prediction algorithm. Molecular docking using the HPEP dock server demonstrated strong binding interactions between the epitopes and HLA molecules (ten alleles for each class I and II HLA). Moreover, an analysis of population coverage using the IEDB database revealed that the identified peptides have over 90% average population coverage across six continents. Molecular docking and simulation analysis reveal a stable interaction with peptide constructs of chosen immunogenic peptides and Toll-like receptor-4. These computational analyses demonstrate selected peptides' immunogenic potential, which needs to be validated in different experimental systems.

Design and characterization of a multi-epitope vaccine against Clostridium botulinum A3 Loch Maree intoxication in humans

Clostridium botulinum Loch Maree expresses an extremely potent botulinum neurotoxin subtype, A3 causing botulism and several gastrointestinal disorders in mammals. Several recombinant vaccines have been developed for human botulism and no vaccine is currently available for the treatment of diseases caused by other virulence factors. Hence, we designed, constructed, and characterized a multi-epitope vaccine from new virulence proteins identified from this organism using an immunoinformatics approach. The vaccine construct used in this study was designed from 6B cell linear epitopes, 12 cytotoxic T cell lymphocyte epitopes, and 15 helper T cell lymphocyte epitopes, with a defensin adjuvant and adjusting linker sequences. A molecular modeling approach was used to model, refine, and validate the 3D structure of the vaccine construct. Molecular docking studies were performed to determine the stability of the molecular interactions between the vaccine construct and human toll-like receptor 7. The in silico molecular cloning was used to clone a codon-optimized synthetic vaccine gene in pCYB1 vector and expressed in Escherichia coli. The results of this study identified six new virulence proteins: peptidoglycan hydrolase, SCP-like extracellular protein, N-acetylmuramoyl-l-alanine amidase, putative membrane protein, drug/metabolite exporter, and bacillolysin. The top B-cell, cytotoxic T-cell lymphocyte, and helper T-lymphocyte epitopes were predicted from these virulence proteins with greater accuracy and reliability. HLA-A*02:01 and HLA-A*03:01 were identified as HLA-A-binding alleles for cytotoxic T-cell lymphocyte epitopes. DRB1*0110 and DRB1*0115 are the dominant alleles that bind to helper T-cell lymphocyte epitopes. The synthetic gene construct was highly expressed in a heterologous host and produced considerable amounts of antigenic protein. The multi-epitope vaccine is more conservative in the sequence-structure-function link, immunogenic with less allergenicity, and possibly provokes cellular and humoral immunity. The present study suggests that the designed multi-epitope vaccine is a promising prophylactic candidate for the virulence and intoxication caused by subtype A3 strains.

Revolutionizing Vaccine Development for COVID-19: A Review of AI-Based Approaches

The evolvement of COVID-19 vaccines is rapidly being revolutionized using artificial intelligence-based technologies. Small compounds, peptides, and epitopes are collected to develop new therapeutics. These substances can also guide artificial intelligence-based modeling, screening, or creation. Machine learning techniques are used to leverage pre-existing data for COVID-19 drug detection and vaccine advancement, while artificial intelligence-based models are used for these purposes. Models based on artificial intelligence are used to evaluate and recognize the best candidate targets for future therapeutic development. Artificial intelligence-based strategies can be used to address issues with the safety and efficacy of COVID-19 vaccine candidates, as well as issues with manufacturing, storage, and logistics. Because antigenic peptides are effective at eliciting immune responses, artificial intelligence algorithms can assist in identifying the most promising COVID-19 vaccine candidates. Following COVID-19 vaccination, the first phase of the vaccine-induced immune response occurs when major histocompatibility complex (MHC) class II molecules (typically bind peptides of 12–25 amino acids) recognize antigenic peptides. Therefore, AI-based models are used to identify the best COVID-19 vaccine candidates and ensure the efficacy and safety of vaccine-induced immune responses. This study explores the use of artificial intelligence-based approaches to address logistics, manufacturing, storage, safety, and effectiveness issues associated with several COVID-19 vaccine candidates. Additionally, we will evaluate potential targets for next-generation treatments and examine the role that artificial intelligence-based models can play in identifying the most promising COVID-19 vaccine candidates, while also considering the effectiveness of antigenic peptides in triggering immune responses. The aim of this project is to gain insights into how artificial intelligence-based approaches could revolutionize the development of COVID-19 vaccines and how they can be leveraged to address challenges associated with vaccine development. In this work, we highlight potential barriers and solutions and focus on recent improvements in using artificial intelligence to produce COVID-19 drugs and vaccines, as well as the prospects for intelligent training in COVID-19 treatment discovery.

In silico design of an epitope-based vaccine against PspC in Streptococcus pneumoniae using reverse vaccinology

BACKGROUND

Streptococcus pneumoniae is a major pathogen that poses a significant hazard to global health, causing a variety of infections including pneumonia, meningitis, and sepsis. The emergence of antibiotic-resistant strains has increased the difficulty of conventional antibiotic treatment, highlighting the need for alternative therapies such as multi-epitope vaccines. In this study, immunoinformatics algorithms were used to identify potential vaccine candidates based on the extracellular immunogenic protein Pneumococcal surface protein C (PspC).

METHOD

The protein sequence of PspC was retrieved from NCBI for the development of the multi-epitope vaccine (MEV), and potential B cell and T cell epitopes were identified. Linkers including EAAAK, AAY, and CPGPG were used to connect the epitopes. Through molecular docking, molecular dynamics, and immunological simulation, the affinity between MEV and Toll-like receptors was determined. After cloning the MEV construct into the PET28a ( +) vector, SnapGene was used to achieve expression in Escherichia coli.

RESULT

The constructed MEV was discovered to be stable, non-allergenic, and antigenic. Microscopic interactions between ligand and receptor are confirmed by molecular docking and molecular dynamics simulation. The use of an in-silico cloning approach guarantees the optimal expression and translation efficiency of the vaccine within an expression vector.

CONCLUSION

Our study demonstrates the potential of in silico approaches for designing effective multi-epitope vaccines against S. pneumoniae. The designated vaccine exhibits the required physicochemical, structural, and immunological characteristics of a successful vaccine against SPN. However, laboratory validation is required to confirm the safety and immunogenicity of the proposed vaccine design.

Vaccinomics to design a multi-epitope-based vaccine against monkeypox virus using surface-associated proteins

In 2022, the ongoing multi-country outbreak of monkeypox virus-now occurring outside Africa, too is a global health concern. Monkeypox is a zoonotic virus, which causes disease mainly in animals, and then it is transferred to humans. Recently, in the monkeypox epidemic, a large number of human cases emerged while the global health community worked to tackle the outbreak and save lives. Herein, a multi-epitope-based vaccine is designed against monkeypox virus using two surface-associated proteins: MPXVgp002 accession number > YP_010377003.1 and MPXVgp008 accession number > YP_010377007.1 proteins. These proteins were utilized for B- and T-cell epitopes prediction. The epitopes were further screened, and the screen filtered KCKDNEYRSR, RSCNTTHNR, and RTRRETGAS with the antigenicity scores of 0.5279, 0.5604, and 0.7628, respectively. Overall, the epitopes can induce immunity in 99.74% population of the world. Further, GPGPG linkers were used for joining the epitopes and EAAAK linker was used for adjuvant attachment. It has a three-dimensional structure modelled for retaining the structural stability. Three pairs of amino acid residues that were able to make disulfide bonds were chosen: Gly1-Ser82, Cys7-Tyr10, and Phe51-Ile55. Molecular docking of vaccine was done with toll-like receptors, viz., 2, 3, 4, and 8 immune cell receptors. The docking results revealed that the vaccine as potential molecule due to its better binding affinity with toll-like receptors 2, 3, 4 and 8. Top complex in docking in with each receptor was selected based on lowest energy scores- -888.7 kcal/mol (TLR-2), -976.3 kcal/mol (TLR-3), -801.9 kcal/mol (TLR-4), and -955.4 kcal/mol (TLR-4)-were subjected to simulation. The docked complexes were evaluated in 500 ns of MD simulation. Throughout the simulation time, no significant deviation occurred. This confirmed that the vaccine as potential vaccine candidate to interact with immune cell receptors. This interaction is important for the immune system activation. In conclusion, the proposed vaccine construct against monkeypox could induce an effective immune response and speed up the vaccine development process. However, the study is completely based on the computational approach, hence, the experimental validation is required.Communicated by Ramaswamy H. Sarma.

Screening the B- and T-cell epitope map of TP0136 and exploring their effect in a Treponema pallidum rabbit model

The systemic immune response, including B- and T-cell reactions, plays a corresponding role in syphilis infections. The TP0136 protein is a target of the immune response in infected hosts and may mediate the immune response. Here, we developed a method that combining reverse vaccine approach with Pepscan/T-cell proliferation to screen and identify three B-cell and two T-cell epitopes of TP0136, and explore the role of the B- and T-cell epitopes in immunized-infected animals. The results showed that immunized with B-cell epitopes not only had no protective effect but also aggravated the syphilitic lesion development. While immunized with T-cell epitopes of TP0136 could induce a strong Th1-cellular immunity response, which could attenuate syphilitic lesion development to a certain extent. The variation in exacerbation or attenuation of skin lesions, induced by distinct B- and T-cell epitopes of Tp0136, within the host's defense against syphilis warrants in-depth exploration.

Identification of conserved immunogenic peptides of SARS-CoV-2 nucleocapsid protein

The emergence of the new SARS-CoV-2 variants has led to major concern regarding the efficacy of approved vaccines. Nucleocapsid is a conserved structural protein essential for replication of the virus. This study focuses on identifying conserved epitopes on the nucleocapsid (N) protein of SARS-CoV-2. Using 510 unique amino acid sequences of SARS-CoV-2 N protein, two peptides (193 and 215 aa) with 90% conservancy were selected for T cell epitope prediction. Three immunogenic peptides containing multiple T cell epitopes were identified which were devoid of autoimmune and allergic immune response. These peptides were also conserved (100%) in recent Omicron variants reported in Jan-August 2023. HLA analysis reveals that these peptides are predicted as binding to large number of HLA alleles and 71-90% population coverage in six continents. Identified peptides displayed good binding score with both HLA class I and HLA class II molecules in the docking study. Also, a vaccine construct docked with TLR-4 receptor displays strong interaction with 20 hydrogen bonds and molecular simulation analysis reveals that docked complex are stable. Additionally, the immunogenicity of these N protein peptides was confirmed using SARS-CoV-2 convalescent serum samples. We conclude that the identified N protein peptides contain highly conserved and antigenic epitopes which could be used as a target for the future vaccine development against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

Multi-epitope vaccine against drug-resistant strains of Mycobacterium tuberculosis: a proteome-wide subtraction and immunoinformatics approach

Mycobacterium tuberculosis (Mtb) is the causative agent of tuberculosis, one of the most deadly infections in humans. The emergence of multidrug-resistant and extensively drug-resistant Mtb strains presents a global challenge. Mtb has shown resistance to many frontline antibiotics, including rifampicin, kanamycin, isoniazid, and capreomycin. The only licensed vaccine, Bacille Calmette-Guerin, does not efficiently protect against adult pulmonary tuberculosis. Therefore, it is urgently necessary to develop new vaccines to prevent infections caused by these strains. We used a subtractive proteomics approach on 23 virulent Mtb strains and identified a conserved membrane protein (MmpL4, NP_214964.1) as both a potential drug target and vaccine candidate. MmpL4 is a non-homologous essential protein in the host and is involved in the pathogen-specific pathway. Furthermore, MmpL4 shows no homology with anti-targets and has limited homology to human gut microflora, potentially reducing the likelihood of adverse effects and cross-reactivity if therapeutics specific to this protein are developed. Subsequently, we constructed a highly soluble, safe, antigenic, and stable multi-subunit vaccine from the MmpL4 protein using immunoinformatics. Molecular dynamics simulations revealed the stability of the vaccine-bound Toll-like receptor-4 complex on a nanosecond scale, and immune simulations indicated strong primary and secondary immune responses in the host. Therefore, our study identifies a new target that could expedite the design of effective therapeutics, and the designed vaccine should be validated. Future directions include an extensive molecular interaction analysis, in silico cloning, wet-lab experiments, and evaluation and comparison of the designed candidate as both a DNA vaccine and protein vaccine.

COVID-19 associated thyroid dysfunction and other comorbidities and its management using phytochemical-based therapeutics: a natural way

The present severe acute respiratory syndrome-2 (SARS-CoV-2) mediated Coronavirus pandemic (COVID-19) and post-COVID-19 complications affect human life drastically. Patients who have been cured of COVID-19 infection are now experiencing post-COVID-19 associated comorbidities, which have increased mortality rates. The SARS-CoV-2 infection distresses the lungs, kidneys, gastrointestinal tract, and various endocrine glands, including the thyroid. The emergence of variants which includes Omicron (B.1.1.529) and its lineages threaten the world severely. Among different therapeutic approaches, phytochemical-based therapeutics are not only cost-effective but also have lesser side effects. Recently a plethora of studies have shown the therapeutic efficacy of various phytochemicals for the treatment of COVID-19. Besides this, various phytochemicals have been found efficacious in treating several inflammatory diseases, including thyroid-related anomalies. The method of the phytochemical formulation is quick and facile and the raw materials for such herbal preparations are approved worldwide for human use against certain disease conditions. Owing to the advantages of phytochemicals, this review primarily discusses the COVID-19-related thyroid dysfunction and the role of key phytochemicals to deal with thyroid anomaly and post-COVID-19 complications. Further, this review shed light on the mechanism via which COVID-19 and its related complication affect organ function of the body, along with the mechanistic insight into the way by which phytochemicals could help to cure post-COVID-19 complications in thyroid patients. Considering the advantages offered by phytochemicals as a safer and cost-effective medication they can be potentially used to combat COVID-19-associated comorbidities.

Development of a candidate multi-epitope vaccine against Sphingobacterium spiritivorum : Reverse vaccinology and immunoinformatics approach

OBJECTIVES

To develop a candidate vaccine aginst the Sphingobacterium spiritivorum.

METHODS

Since there is currently no vaccine against this pathogen, we employed in-silico methods to extensively explore the outer membrane toxin-producing proteins found specifically in S. spiritivorum to forecast a multi-epitope chimeric vaccine design. This computational study was conducted in Saudi Arabia in 2022 (study design: computational; ethical approval not applicable).

RESULTS

TThe vaccine peptide comprises multiple linear and conformational B-cell epitopes, which have the potential to elicit humoral immunity. Projected B-cell- derived T-cell epitopes for outer membrane proteins are present in the produced protein. The docking and molecular dynamic simulation results indicating that the chimeric vaccine had adequate binding stability with TLR-4. Following the immunological simulation, significant levels of immune cell expression were observed as immunoglobulin (Ig) M and IgG, IgM, IgM1, and IgM2, and independently IgG1 and IgG2.

CONCLUSION

The developed vaccine candidate is suitable for further testing and can assist experimental vaccinologists in developing an effective vaccine against S. spiritivorum.

Internet-of-medical-things integrated point-of-care biosensing devices for infectious diseases: Toward better preparedness for futuristic pandemics

Microbial pathogens have threatened the world due to their pathogenicity and ability to spread in communities. The conventional laboratory-based diagnostics of microbes such as bacteria and viruses need bulky expensive experimental instruments and skilled personnel which limits their usage in resource-limited settings. The biosensors-based point-of-care (POC) diagnostics have shown huge potential to detect microbial pathogens in a faster, cost-effective, and user-friendly manner. The use of various transducers such as electrochemical and optical along with microfluidic integrated biosensors further enhances the sensitivity and selectivity of detection. Additionally, microfluidic-based biosensors offer the advantages of multiplexed detection of analyte and the ability to deal with nanoliters volume of fluid in an integrated portable platform. In the present review, we discussed the design and fabrication of POCT devices for the detection of microbial pathogens which include bacteria, viruses, fungi, and parasites. The electrochemical techniques and current advances in this field in terms of integrated electrochemical platforms that include mainly microfluidic- based approaches and smartphone and Internet-of-things (IoT) and Internet-of-Medical-Things (IoMT) integrated systems have been highlighted. Further, the availability of commercial biosensors for the detection of microbial pathogens will be briefed. In the end, the challenges while fabrication of POC biosensors and expected future advances in the field of biosensing have been discussed. The integrated biosensor-based platforms with the IoT/IoMT usually collect the data to track the community spread of infectious diseases which would be beneficial in terms of better preparedness for current and futuristic pandemics and is expected to prevent social and economic losses.

State of the art in epitope mapping and opportunities in COVID-19

The understanding of any disease calls for studying specific biological structures called epitopes. One important tool recently drawing attention and proving efficiency in both diagnosis and vaccine development is epitope mapping. Several techniques have been developed with the urge to provide precise epitope mapping for use in designing sensitive diagnostic tools and developing rpitope-based vaccines (EBVs) as well as therapeutics. In this review, we will discuss the state of the art in epitope mapping with a special emphasis on accomplishments and opportunities in combating COVID-19. These comprise SARS-CoV-2 variant analysis versus the currently available immune-based diagnostic tools and vaccines, immunological profile-based patient stratification, and finally, exploring novel epitope targets for potential prophylactic, therapeutic or diagnostic agents for COVID-19.

A multiepitope vaccine candidate against infectious bursal disease virus using immunoinformatics-based reverse vaccinology approach

Infectious bursal disease virus is the causative agent of infectious bursal disease (Gumboro disease), a highly contagious immunosuppressive disease of chicken with a substantial economic impact on small- and large-scale poultry industries worldwide. Currently, live attenuated vaccines are widely used to control the disease in chickens despite their issues with safety (immunosuppression and bursal atrophy) and efficiency (breaking through the maternally-derived antibody titer). To overcome the drawbacks, the current study has, for the first time, attempted to construct a computational model of a multiepitope based vaccine candidate against infectious bursal disease virus, which has the potential to overcome the safety and protection issues found in the existing live-attenuated vaccines. The current study used a reverse vaccinology based immunoinformatics approach to construct the vaccine candidate using major and minor capsid proteins of the virus, VP2 and VP3, respectively. The vaccine construct was composed of four CD8⁺ epitopes, seven CD4⁺ T-cell epitopes, 11 B-cell epitopes and a Cholera Toxin B adjuvant, connected using appropriate flexible peptide linkers. The vaccine construct was evaluated as antigenic with VaxiJen Score of 0.6781, immunogenic with IEDB score of 2.89887 and non-allergenic. The 55.64 kDa construct was further evaluated for its physicochemical characteristics, which revealed that it was stable with an instability index of 16.24, basic with theoretical pI of 9.24, thermostable with aliphatic index of 86.72 and hydrophilic with GRAVY score of -0.256. The docking and molecular dynamics simulation studies of the vaccine construct with Toll-like receptor-3 revealed fair structural interaction (binding affinity of -295.94 kcal/mol) and complex stability. Further, the predicted induction of antibodies and cytokines by the vaccine construct indicated the possible elicitation of the host's immune response against the virus. The work is a significant attempt to develop next-generation vaccines against the infectious bursal disease virus though further experimental studies are required to assess the efficacy and protectivity of the proposed vaccine candidate in vivo.

In-silico design and evaluation of an epitope-based serotype-independent promising vaccine candidate for highly cross-reactive regions of pneumococcal surface protein A

BACKGROUND

The pathogenicity of pneumococcus with high morbidity, mortality, and multi-drug resistance patterns has been increasing. The limited coverage of the licensed polysaccharide-based vaccines and the replacement of the non-vaccine serotypes are the main reasons for producing a successful serotype-independent vaccine. Pneumococcal surface protein A (PspA) is an extremely important virulence factor and an interesting candidate for conserved protein-based pneumococcal vaccine classified into two prominent families containing five clades. PspA family-elicited immunity is clade-dependent, and the level of the PspA cross-reactivity is restricted to the same family.

METHODS

To cover and overcome the clade-dependent immunity of the PspAs in this study, we designed and tested a PspA_1-5c+p vaccine candidate composed of the highest immunodominant coverage of B- and T-cell epitope truncated domain of each clade focusing on two cross-reactive B and C regions of the PspAs. The antigenicity, toxicity, physicochemical properties, 3D structure prediction, stability and flexibility of the designed protein using molecular dynamic (MD) simulation, molecular docking of the construct withHLADRB1*(01:01) and human lactoferrin N-lop, and immune simulation were assessed using immunoinformatics tools. In the experimental section, after intraperitoneal immunization of the mice with Alum adjuvanted recombinant PspA_1-5c+p, we evaluated the immune response, cross-reactivity, and functionality of the Anti-PspA_1-5c+p antibody using ELISA, Opsonophagocytic killing activity, and serum bactericidal assay.

RESULTS

For the first time, this work suggested a novel PspA-based vaccine candidate using immunoinformatics tools. The designed PspA_1-5c+p protein is predicted to be highly antigenic, non-toxic, soluble, stable with low flexibility in MD simulation, and able to stimulate both humoral and cellular immune responses. The designed protein also could interact strongly with HLADRB1*(01:01) and human lactoferrin N-lop in the docking study. Our immunoinformatics predictions were validated using experimental data. Results showed that the anti-PspA_1-5c+p IgG not only had a high titer with strong and same cross-reactivity coverage against all pneumococcal serotypes used but also had high and effective bioactivity for pneumococcal clearance using complement system and phagocytic cells.

CONCLUSION

Our findings elucidated the potential application of the PspA_1-5c+p vaccine candidate as a serotype-independent pneumococcal vaccine with a strong cross-reactivity feature. Further in-vitro and in-vivo investigations against other PspA clades should be performed to confirm the full protection of the PspA_1-5c+p vaccine candidate.

MXene-based aptasensor for the detection of aflatoxin in food and agricultural products

The detection of toxins that contaminate food needs highly sensitive and selective techniques to prevent substantial monitory loss. In this regard, various nanostructured material-enabled biosensors, have recently been developed to improve the detection of food toxins among them aflatoxin is the prevalent one. The biosensor-based detection of aflatoxin is quick, cheaper, and needs less skilled personnel, therefore overcoming the shortcomings of conventional techniques such as LC/MS-MS, HPLC, and ELISA assays. 2D MXenes manifest as an efficient material for biosensing due to their desirable biocompatibility, magnificent mechanical strength, easiness of surface functionalization, and tuneable optical and electronic features. Contrary to this, aptamers as biorecognition elements (BREs) possess high selectivity, sensitivity, and ease of synthesis when compared to conventional BREs. In this review, we explored the most cutting-edge aptamer-based MXene-enabled biosensing technologies for the detection of the most poisonous mycotoxins (i.e., Aflatoxins) in food and environmental matrices. The discussion begins with the synthesis processes and surface functionalization/modification of MXenes. Computational approaches for designing aptasensors and advanced data analysis based on artificial intelligence and machine learning with special emphasis over Internet-of-Thing integrated biosensing devices has been presented. Besides, the advantages of aptasensors over conventional methods along with their limitations have been briefed. Their benefits, drawbacks, and future potential are discussed concerning their analytical performance, utility, and on-site adaptability. Additionally, next-generation MXene-enabled biosensing technologies that provide end users with simple handling and improved sensitivity and selectivity have been emphasized. Owing to massive applicability, economic/commercial potential of MXene in current and future perspective have been highlighted. Finally, the existing difficulties are scrutinized and a roadmap for developing sophisticated biosensing technologies to detect toxins in various samples in the future is projected.

Identification of new inhibitors of NS5 from dengue virus using saturation transfer difference (STD-NMR) and molecular docking studies

The rapid spread of dengue virus has now emerged as a major health problem worldwide, particularly in tropical and sub-tropical regions. Nearly half of the human population is at risk of getting infection. Among the proteomes of dengue virus, nonstructural protein NS5 is conserved across the genus Flavivirus. NS5 comprises methyltransferase enzyme (MTase) domain, which helps in viral RNA capping, and RNA-dependent RNA polymerase (RdRp) domain, which is important for the virus replication. Negative modulation of NS5 decreases its activity and associated functions. Despite recent advances, there is still an immense need for effective approaches toward drug discovery against dengue virus. Drug repurposing is an approach to identify the new therapeutic indications of already approved drugs, for the treatment of both common and rare diseases, and can potentially lower the cost, and time required for drug discovery and development. In this study, we evaluated 75 compounds (grouped into 15 mixtures), including 13 natural compounds and 62 drugs, by using biophysical methods, for their ability to interact with NS5 protein, which were further validated by molecular docking and simulation studies. Our current study led to the identification of 12 ligands, including both 9 US-FDA approved drugs and 3 natural products that need to be further studied as potential antiviral agents against dengue virus.

Biosensors based detection of novel biomarkers associated with COVID-19: Current progress and future promise

The pandemic situation of COVID-19 has caused global alarm in health care, devastating loss of lives, strangled economy, and paralysis of normal livelihood. The high inter-individual transmission rate created havoc in the global community. Although tremendous efforts are pitching in from across the globe to understand this disease, the clinical features seemed to have a wide range including fever, cough, and fatigue are the prominent features. Congestion, rhinorrhea, sore throat, and diarrhea are other less common features observed. The challenge of this disease lies in the difficulty in maneuvering the clinical course causing severe complications. One of the major causative factors for multi-organ failure in patients with severe COVID-19 complications is systemic vasculitis and cytokine-mediated coagulation disorders. Hence, effective markers trailing the disease severity and disease prognosis are urgently required for prompt medical treatment. In this review article, we have emphasized currently identified inflammatory, hematological, immunological, and biochemical biomarkers of COVID-19. We also discussed currently available biosensors for the detection of COVID-19-associated biomarkers & risk factors and the detection methods as well as their performances. These could be effective tools for rapid and more promising diagnoses in the current pandemic situation. Effective biomarkers and their rapid, scalable, & sensitive detection might be beneficial for the prevention of serious complications and the clinical management of the disease.

3D printed human organoids: High throughput system for drug screening and testing in current COVID-19 pandemic

In the current pandemic, scenario the world is facing a huge shortage of effective drugs and other prophylactic medicine to treat patients which created havoc in several countries with poor resources. With limited demand and supply of effective drugs, researchers rushed to repurpose the existing approved drugs for the treatment of COVID-19. The process of drug screening and testing is very costly and requires several steps for validation and treatment efficacy evaluation ranging from in-vitro to in-vivo setups. After these steps, a clinical trial is mandatory for the evaluation of treatment efficacy and side effects in humans. These processes enhance the overall cost and sometimes the lead molecule show adverse effects in humans and the trial ends up in the final stages. Recently with the advent of three-dimensional (3D) organoid culture which mimics the human tissue exactly the process of drug screening and testing can be done in a faster and cost-effective manner. Further 3D organoids prepared from stems cells taken from individuals can be beneficial for personalized drug therapy which could save millions of lives. This review discussed approaches and techniques for the synthesis of 3D-printed human organoids for drug screening. The key findings of the usage of organoids for personalized medicine for the treatment of COVID-19 have been discussed. In the end, the key challenges for the wide applicability of human organoids for drug screening with prospects of future orientation have been included.

In silico designing of a novel epitope-based candidate vaccine against Streptococcus pneumoniae with introduction of a new domain of PepO as adjuvant

BACKGROUND

Streptococcus pneumoniae is the leading reason for invasive diseases including pneumonia and meningitis, and also secondary infections following viral respiratory diseases such as flu and COVID-19. Currently, serotype-dependent vaccines, which have several insufficiency and limitations, are the only way to prevent pneumococcal infections. Hence, it is plain to need an alternative effective strategy for prevention of this organism. Protein-based vaccine involving conserved pneumococcal protein antigens with different roles in virulence could provide an eligible alternative to existing vaccines.

METHODS

In this study, PspC, PhtD and PsaA antigens from pneumococcus were taken to account to predict B-cell and helper T-cell epitopes, and epitope-rich regions were chosen to build the construct. To enhance the immunogenicity of the epitope-based vaccine, a truncated N-terminal fragment of pneumococcal endopeptidase O (PepO) was used as a potential TLR2/4 agonist which was identified by molecular docking studies. The ultimate construct was consisted of the chosen epitope-rich regions, along with the adjuvant role (truncated N-PepO) and suitable linkers.

RESULTS

The epitope-based vaccine was assessed as regards physicochemical properties, allergenicity, antigenicity, and toxicity. The 3D structure of the engineered construct was modeled, refined, and validated. Molecular docking and simulation of molecular dynamics (MD) indicated the proper and stable interactions between the vaccine and TLR2/4 throughout the simulation periods.

CONCLUSIONS

For the first time this work presents a novel vaccine consisting of epitopes of PspC, PhtD, and PsaA antigens which is adjuvanted with a new truncated domain of PepO. The computational outcomes revealed that the suggested vaccine could be deemed an efficient therapeutic vaccine for S. pneumoniae; nevertheless, in vitro and in vivo examinations should be performed to prove the potency of the candidate vaccine.

An exploration on the topologies of SARS-CoV-2/human protein-protein interaction network

Network biology is an important finding that uncovers the significant elements in viral infection control. Since viruses use the proteins on their surfaces to attach and enter into the host cell, the establishment of virus-host protein interactions is a potent regulator of the global organization of the viral life cycle after virus entry into host cells. In this instance, a topological study on the SARS-CoV-2/Human Protein-Protein Interaction Network (PPIN) evacuates much information about the protein-protein interactions. By making some interruptions to the interaction between proteins and hosts, we can quickly reduce the spread of the disease and get an insight into the target protein for drug development. This paper mainly focused on the graphical and structural complexity of the SARS-CoV-2/Human PPIN. For this purpose, the various primary (distance, radius, diameter, etc…) and advanced levels of graph measures (density, modularity, clustering coefficient, etc…) as well as a few fractal (box dimension, multifractal analysis) and entropy measures have been used. In addition, several graph descriptions and distribution graphs of PPIN offered to gain a thorough understanding of the SARS-CoV-2/Human PPIN. Conclusively, based on our work, we have discovered that PPIN is moderately complex and identified that hiring Nsp8 as a target node will positively affect the PPIN and has pointed out that mathematically found target proteins are matched with already suggested target proteins in the previous survey.Communicated by Ramaswamy H. Sarma.

Phytochemicals-based targeting RdRp and main protease of SARS-CoV-2 using docking and steered molecular dynamic simulation: A promising therapeutic approach for Tackling COVID-19

The ongoing COVID-19 pandemic has affected millions of people worldwide and caused substantial socio-economic losses. Few successful vaccine candidates have been approved against SARS-CoV-2; however, their therapeutic efficacy against the mutated strains of the virus remains questionable. Furthermore, the limited supply of vaccines and promising antiviral drugs have created havoc in the present scenario. Plant-based phytochemicals (bioactive molecules) are promising because of their low side effects and high therapeutic value. In this study, we aimed to screen for suitable phytochemicals with higher therapeutic value using the two most crucial proteins of SARS-CoV-2, the RNA-dependent RNA polymerase (RdRp) and main protease (Mpro). We used computational tools such as molecular docking and steered molecular dynamics simulations to gain insights into the different types of interactions and estimated the relative binding forces between the phytochemicals and their respective targets. To the best of our knowledge, this is the first report that not only involves a search for a therapeutic bioactive molecule but also sheds light on the mechanisms underlying target inhibition in terms of calculations of force and work needed to extractthe ligand from the pocket of its target. The complexes showing higher binding forces were subjected to 200 ns molecular dynamic simulations to check the stability of the ligand inside the binding pocket. Our results suggested that isoskimmiwallin and terflavin A are potential inhibitors of RdRp, whereas isoquercitrin and isoorientin are the lead molecules against Mpro. Collectively, our findings could potentially aid in the development of novel therapeutics against COVID-19.

Microfluidics-Based Point-of-Care Testing (POCT) Devices in Dealing with Waves of COVID-19 Pandemic: The Emerging Solution

Recent advances in microfluidics-based point-of-care testing (POCT) technology such as paper, array, and beads have shown promising results for diagnosing various infectious diseases. The fast and timely detection of viral infection has proven to be a critical step for deciding the therapeutic outcome in the current COVID-19 pandemic, which in turn not only enhances the patient survival rate but also reduces the disease-associated comorbidities. In the present scenario, rapid, noninvasive detection of the virus using low cost and high throughput microfluidics-based POCT devices embraces the advantages over existing diagnostic technologies, for which a centralized lab facility, expensive instruments, sample pretreatment, and skilled personnel are required. Microfluidic-based multiplexed POCT devices can be a boon for clinical diagnosis in developing countries that lacks a centralized health care system and resources. The microfluidic devices can be used for disease diagnosis and exploited for the development and testing of drug efficacy for disease treatment in model systems. The havoc created by the second wave of COVID-19 led several countries' governments to the back front. The lack of diagnostic kits, medical devices, and human resources created a huge demand for a technology that can be remotely operated with single touch and data that can be analyzed on a phone. Recent advancements in information technology and the use of smartphones led to a paradigm shift in the development of diagnostic devices, which can be explored to deal with the current pandemic situation. This review sheds light on various approaches for the development of cost-effective microfluidics POCT devices. The successfully used microfluidic devices for COVID-19 detection under clinical settings along with their pros and cons have been discussed here. Further, the integration of microfluidic devices with smartphones and wireless network systems using the Internet-of-things will enable readers for manufacturing advanced POCT devices for remote disease management in low resource settings.

Prediction and evaluation of multi epitope based sub-unit vaccine against Salmonella typhimurium

Salmonella enteric serovar Typhimurium is the most common enteric pathogen in humans and animals. Consumption of contaminated food or water triggers inflammation that allows Salmonella to spread into the gut and causes gastrointestinal diseases. The infection spreads by intestinal invasion, phagocyte internalization and subsequent dissemination in many other patients. This research used TolA, a Salmonella typhimurium membrane protein, to computationally design a multi-epitope vaccine against the pathogen. Complete consistency of the candidate vaccine was checked In silico, and molecular dynamics simulations confirmed the vaccine's stability. According to docking report, the vaccine has a good affinity with toll-like receptors. In silico cloning and codon optimization techniques improved the vaccine's efficacy in Salmonella typhimurium manifestation process. The candidate vaccine induced an efficient immune response, as determined by In silico immune simulation. Computational studies revealed that the engineered multi-epitope vaccine is structurally stable, capable of eliciting particular immunological reactions, and therefore a candidate for a latent Salmonella typhimurium vaccine. However, wet lab studies and further investigations are required to confirm the results.

Attitude of parents toward vaccination against COVID-19 for own children in Jordan: A cross-sectional study

Aim

To evaluate parents' attitudes toward the COVID-19 vaccination for their children and determine predictors of parents’ attitudes towards their children receiving the Vaccine against COVID-19.

Method

This study used a cross-sectional design. The subjects were Jordanian parents with a child less than 18 years old. The survey was made available on different social media platforms and other networks such as community organizations, academic posts, and private groups.

Results

There was a difference in the attitude of parents toward COVID-19 vaccination for their children according to their demographic and personal characteristics (p = .05). Attitude of parents toward vaccination against COVID-19 for their own children was more likely to be significant and impacted by gender, nationality, job status, level of income and if their child had previously received influenza vaccine.

Conclusion

This is a large national study regarding the attitude of parents toward vaccination against COVID-19 for their own children in Jordan. This study found that more than fifty percent of the parents were hesitant to allow their children to receive COVID-19 vaccination.

Clinically available/under trial drugs and vaccines for treatment of SARS-COV-2

Prior 2019 to work date entire world is seriously influenced by an appalling illness called COVID sickness [Coronavirus disease-2019 (COVID-19)] which is brought about by another strain of coronavirus known as severe acute respiratory syndrome-Coronavirus-2. This pandemic was first seen in the Hubei area in Wuhan city of China. To date above 170 million individuals have been influenced by this infection and more than 3 million individuals died. The race of finding specific therapeutic drugs and efficacious vaccine candidates is still going on to tackle the pandemic-associated morbidities. This chapter discussed different clinically accessible medications (remdesivir, hydroxychloroquine, azithromycin, etc.) and immunizations (mRNA-1273, Sputanik, Pfizer, etc.) which are either in use or under trial for the treatment of COVID-19.

Immunoinformatics and reverse vaccinomic approaches for effective design

The emergence of mutagenic strains of severe acute respiratory syndrome-Coronavirus-2 (SARS-CoV-2) worst hit the world which already suffered from the Coronavirus disease-2019 (COVID-19) pandemic for 2 years. Due to recent advances in vaccinomics, many vaccine candidates are available but their efficacy against a mutant version of SARS-CoV-2 has remained uncertain. The immune-informatics-based reverse vaccinomic approaches have shown promising investigations recently for the development of cost-effective vaccinomics candidates in a very short period of time. The strategic vaccine development of selected epitopes using artificial intelligence for both B- and T-cells is a very crucial step in this process. This approach provides a highly effective and immunogenic vaccine that offers immunological safety against autoimmunity and other adverse effects over ethnicities, pregnant women, and vulnerable age groups. Several researchers have developed effective vaccine candidates using computational vaccinology and the immune-informatics approach. In this process, a unique peptide sequence of viral proteins such as Nucleocapsid, spike, envelope protein was identified by various in silico tools which are acting as immunological epitopes against TLRs, T-cells, and B-cells. While the conventional immunological vaccine studies take years for vaccine candidature, the immunoinformatics approach is a time-efficient way for the next generation research to study host-pathogen interactions and vaccine development. It is also cost-effective and leads to a better understanding of disease pathogenesis, diagnosis, and immunological response. Owing to the advantage of immunoinformatics-based vaccine approaches the present chapter aimed to discuss vaccine development using immunoinformatics approaches. Besides, the current challenges and future aspects have also been discussed herewith.

Development of Multi-epitope Subunit Vaccine Against Pseudomonas aeruginosa Using OprF/OprI and PopB Proteins

Background: The emerging problem of antibiotic resistance in Pseudomonas aeruginosa is a global health concern; hence, revealing innovative therapeutic approaches (such as designing an immunogenic vaccine candidate) is needed. There is no evidence of the availability of an effective vaccine that can combat the infection caused by this microorganism. Objectives: This research was conducted to develop a potential chimeric vaccine against P. aeruginosa using reverse vaccinology approaches. Methods: The present vaccine candidate comprised outer membrane protein F and I (OprF/OprI) and PopB with appropriate linkers. After applying meticulous immune-informatics investigation, the multi-epitope vaccine was created, including helper T lymphocyte (HTL), cytotoxic T lymphocyte (CTL), interferon gamma (IFN-γ), and interleukin 4 (IL-4) epitopes. Then, the physicochemical characteristics, allergenicity, toxicity, and antigenicity were analyzed. After investigating the secondary structure, the tertiary structure (3D) model was generated, refined, and validated via computational methods. Besides, the strong protein-ligand interaction and stability between the vaccine candidate and toll-like receptor 4 (TLR4) were determined via molecular docking and dynamics analyses. Moreover, in silico cloning accompanied by pET-22b (+) was used to achieve high translation efficiency. Results: Our results presumed that the chimeric-designed vaccine was thermostable and contained optimal physicochemical properties. This vaccine candidate was nontoxic and highly soluble and had stable protein and TLR4 interaction, adequately overexpressed in Escherichia coli. Overall, it could induce immune responses and repress this microorganism. Conclusions: Therefore, to inhibit Pseudomonas infections experimentally, the efficacy and safety of the vaccine design need to be validated.

Immunoinformatics Analysis of SARS-CoV-2 ORF1ab Polyproteins to Identify Promiscuous and Highly Conserved T-Cell Epitopes to Formulate Vaccine for Indonesia and the World Population

SARS-CoV-2 and its variants caused the COVID-19 pandemic. Vaccines that target conserved regions of SARS-CoV-2 and stimulate protective T-cell responses are important for reducing symptoms and limiting the infection. Seven cytotoxic (CTL) and five helper T-cells (HTL) epitopes from ORF1ab were identified using NetCTLpan and NetMHCIIpan algorithms, respectively. These epitopes were generated from ORF1ab regions that are evolutionary stable as reflected by zero Shannon's entropy and are presented by 56 human leukocyte antigen (HLA) Class I and 22 HLA Class II, ensuring good coverage for the Indonesian and world population. Having fulfilled other criteria such as immunogenicity, IFNγ inducing ability, and non-homology to human and microbiome peptides, the epitopes were assembled into a vaccine construct (VC) together with β-defensin as adjuvant and appropriate linkers. The VC was shown to have good physicochemical characteristics and capability of inducing CTL as well as HTL responses, which stem from the engagement of the vaccine with toll-like receptor 4 (TLR4) as revealed by docking simulations. The most promiscuous peptide 899WSMATYYLF907 was shown via docking simulation to interact well with HLA-A*24:07, the most predominant allele in Indonesia. The data presented here will contribute to the in vitro study of T-cell epitope mapping and vaccine design in Indonesia.

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

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

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.

Evaluation of Microalgae Antiviral Activity and Their Bioactive Compounds

During the last year, science has been focusing on the research of antivirally active compounds overall after the SARS-CoV-2 pandemic, which caused a great amount of deaths and the downfall of the economy in 2020. Photosynthetic organisms such as microalgae are known to be a reservoir of bioactive secondary metabolites; this feature, coupled with the possibility of achieving very high biomass levels without excessive energetic expenses, make microalgae worthy of attention in the search for new molecules with antiviral effects. In this work, the antiviral effects of microalgae against some common human or animal viruses were considered, focusing our attention on some possible effects against SARS-CoV-2. We summed up the data from the literature on microalgae antiviral compounds, from the most common ones, such as lectins, polysaccharides and photosynthetic pigments, to the less known ones, such as unidentified proteins. We have discussed the effects of a microalgae-based genetic engineering approach against some viral diseases. We have illustrated the potential antiviral benefits of a diet enriched in microalgae.

Immunoinformatics and molecular dynamics approaches: Next generation vaccine design against West Nile virus

West Nile Virus (WNV) is a life threatening flavivirus that causes significant morbidity and mortality worldwide. No preventive therapeutics including vaccines against WNV are available for human use. In this study, immunoinformatics approach was performed to design a multi epitope-based subunit vaccine against this deadly pathogen. Human (HLA) and Mice (H-2) allele specific potential T-cell and B-cell epitopes were shortlisted through a stringent procedure. Molecular docking showed selected epitopes that have stronger binding affinity with human TLR-4. Molecular dynamics simulation confirmed the stable nature of the docked complex. Furthermore, in silico cloning analysis ensures efficient expression of desired gene in the microbial system. Interestingly, previous studies showed that two of our selected epitopes have strong immune response against WNV. Therefore, selected epitopes could be strong vaccine candidates to prevent WNV infections in human. However, further in vitro and in vivo investigations could be strengthening the validation of the vaccine candidate against WNV.