Exploration of surface glycoprotein to design multi-epitope vaccine for the prevention of Covid-19

Leveraging immunoinformatics for developing a multi-epitope subunit vaccine against Helicobacter pylori and Fusobacterium nucleatum

Gastric ulcers caused by Helicobacter pylori and Fusobacterium nucleatum remain a significant global health concern without an established vaccine. In this study, we utilized immunoinformatics methods to design a multi-epitope vaccine targeting these pathogens. Outer membrane proteins from H. pylori and F. nucleatum were scrutinized to identify high antigenic T-cell and B-cell epitopes. The resulting vaccine comprised carefully analyzed and evaluated epitopes, including cytotoxic T-lymphocytes, helper T-lymphocytes, and linear B-lymphocytes epitopes. This vaccine exhibited notable antigenicity, suitable immunogenicity, and demonstrated non-allergenicity and non-toxicity. It displayed favorable physiochemical characteristics and high solubility. In interaction studies, the vaccine exhibited robust binding to toll-like receptor 4 (TLR4). Molecular dynamic simulations revealed cohesive structural integrity and stable attachment. Codon adaptation utilizing Escherichia coli K12 host yielded a vaccine with elevated Codon Adaptation Index (CAI) and optimal GC content. In silico cloning into the pET28+(a) vector demonstrated efficient expression. Immune simulations indicated the vaccine's ability to initiate immune responses in humans, mirroring real-life scenarios. Based on these comprehensive findings, we propose that our developed vaccine has the potential to confer robust immunity against H. pylori and F. nucleatum infections.Communicated by Ramaswamy H. Sarma.

Proteome based analysis of circulating SARS-CoV-2 variants: approach to a universal vaccine candidate

The discovery of the first infectious variant in Wuhan, China, in December 2019, has posed concerns over global health due to the spread of COVID-19 and subsequent variants. While the majority of patients experience flu-like symptoms such as cold and fever, a small percentage, particularly those with compromised immune systems, progress from mild illness to fatality. COVID-19 is caused by a RNA virus known as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our approach involved utilizing immunoinformatic to identify vaccine candidates with multiple epitopes and ligand-binding regions in reported SARS-CoV-2 variants. Through analysis of the spike glycoprotein, we identified dominant epitopes for T-cells and B-cells, resulting in a vaccine construct containing two helper T-cell epitopes, six cytotoxic T-cell epitopes, and four linear B-cell epitopes. Prior to conjugation with adjuvants and linkers, all epitopes were evaluated for antigenicity, toxicity, and allergenicity. Additionally, we assessed the vaccine Toll-Like Receptors complex (2, 3, and 4). The vaccine construct demonstrated antigenicity, non-toxicity, and non-allergenicity, thereby enabling the host to generate antibodies with favorable physicochemical characteristics. Furthermore, the 3D structure of the B-cell construct exhibited a ProSA-web z-score plot with a value of -1.71, indicating the reliability of the designed structure. The Ramachandran plot analysis revealed that 99.6% of the amino acid residues in the vaccine subunit were located in the high favored observation region, further establishing its strong candidacy as a vaccination option.

Multi epitope vaccine candidate design against Streptococcus pneumonia

Streptococcus pneumonia, the causative agent of sepsis, meningitis and pneumonia, is held responsible for causing invasive diseases predominantly in children along with adults from both developing and developed countries. The available vaccines coverage in the context of different serotypes is limited and emergence of non-vaccine serotypes could further emerge as a threat in future. Advanced immunoinformatics tools have been used for developing a multi epitope subunit vaccine. In the current study we have subjected these four surface antigenic proteins Ply, PsaA, PspA and PspK to construct vaccine designs. We have predicted different B-cell and T-cell epitopes by using NetCTL 1.2, IEDB (Immune Epitope Databases) and ABCpred. An adjuvant (griselimycin) has been added to the vaccine construct sequence in order to improve its immunogenicity. The vaccine construct has been evaluated for its antigenicity, allergenicity, toxicity and different physio-chemical properties. The bioinformatic tools have been used for prediction, refinement and validation of the 3 D structure. Further, the vaccine structure has been docked with a toll-like receptor (TLR-4) by ClusPro 2.0. In conclusion, the proposed multi-epitope vaccine designs could potentially activate both humoral and cellular immune responses and has a potential to be a vaccine candidate against S.pneumoniae, and requires experimental validation for ensuring immunogenicity and safety profile.Communicated by Ramaswamy H. Sarma.

A comprehensive review on pharmacologic agents, immunotherapies and supportive therapeutics for COVID-19

The emergence of coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has affected many countries throughout the world. As urgency is a necessity, most efforts have focused on identifying small molecule drugs that can be repurposed for use as anti-SARS-CoV-2 agents. Although several drug candidates have been identified using in silico method and in vitro studies, most of these drugs require the support of in vivo data before they can be considered for clinical trials. Several drugs are considered promising therapeutic agents for COVID-19. In addition to the direct-acting antiviral drugs, supportive therapies including traditional Chinese medicine, immunotherapies, immunomodulators, and nutritional therapy could contribute a major role in treating COVID-19 patients. Some of these drugs have already been included in the treatment guidelines, recommendations, and standard operating procedures. In this article, we comprehensively review the approved and potential therapeutic drugs, immune cells-based therapies, immunomodulatory agents/drugs, herbs and plant metabolites, nutritional and dietary for COVID-19.

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.

Bioinformatics, Computational Informatics, and Modeling Approaches to the Design of mRNA COVID-19 Vaccine Candidates

This article is devoted to applying bioinformatics and immunoinformatics approaches for the development of a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. The study’s relevance is dictated by the fact that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) began its global threat at the end of 2019 and since then has had a devastating impact on the whole world. Measures to reduce threats from the pandemic include social restrictions, restrictions on international travel, and vaccine development. In most cases, vaccine development depends on the spike glycoprotein, which serves as a medium for its entry into host cells. Although several variants of SARS-CoV-2 have emerged from mutations crossing continental boundaries, about 6000 delta variants have been reported along the coast of more than 20 countries in Africa, with South Africa accounting for the highest percentage. This also applies to the omicron variant of the SARS-CoV-2 virus in South Africa. The authors suggest that bioinformatics and immunoinformatics approaches be used to develop a multi-epitope mRNA vaccine against the spike glycoproteins of circulating SARS-CoV-2 variants in selected African countries. Various immunoinformatics tools have been used to predict T- and B-lymphocyte epitopes. The epitopes were further subjected to multiple evaluations to select epitopes that could elicit a sustained immunological response. The candidate vaccine consisted of seven epitopes, a highly immunogenic adjuvant, an MHC I-targeting domain (MITD), a signal peptide, and linkers. The molecular weight (MW) was predicted to be 223.1 kDa, well above the acceptable threshold of 110 kDa on an excellent vaccine candidate. In addition, the results showed that the candidate vaccine was antigenic, non-allergenic, non-toxic, thermostable, and hydrophilic. The vaccine candidate has good population coverage, with the highest range in East Africa (80.44%) followed by South Africa (77.23%). West Africa and North Africa have 76.65% and 76.13%, respectively, while Central Africa (75.64%) has minimal coverage. Among seven epitopes, no mutations were observed in 100 randomly selected SARS-CoV-2 spike glycoproteins in the study area. Evaluation of the secondary structure of the vaccine constructs revealed a stabilized structure showing 36.44% alpha-helices, 20.45% drawn filaments, and 33.38% random helices. Molecular docking of the TLR4 vaccine showed that the simulated vaccine has a high binding affinity for TLR-4, reflecting its ability to stimulate the innate and adaptive immune response.

A fractal scaling analysis of the SARS-CoV-2 genome sequence

An approach based on fractal scaling analysis to characterize the organization of the SARS-CoV-2 genome sequence was used. The method is based on the detrended fluctuation analysis (DFA) implemented on a sliding window scheme to detect variations of long-range correlations over the genome sequence regions. The nucleotides sequence is mapped in a numerical sequence by using four different assignation rules: amino-keto, purine-pyrimidine, hydrogen-bond and hydrophobicity patterns. The originally reported sequence from Wuhan isolates (Wuhan Hu-1) was considered as a reference to contrast the structure of the 2002-2004 SARS-CoV-1 strain. Long-range correlations, quantified in terms of a scaling exponent, depended on both the mapping rule and the sequence region. Deviations from randomness were attributed to serial correlations or anti-correlations, which can be ascribed to ordered regions of the genome sequence. It was found that the Wuhan Hu-1 sequence was more random than the SARS-CoV-1 sequence, which suggests that the SARS-CoV-2 possesses a more efficient genomic structure for replication and infection. In general, the virus isolated in the early 2020 months showed slight correlation differences with the Wuhan Hu-1 sequence. However, early isolates from India and Italy presented visible differences that led to a more ordered sequence organization. It is apparent that the increased sequence order, particularly in the spike region, endowed some early variants with a more efficient mechanism to spreading, replicating and infecting. Overall, the results showed that the DFA provides a suitable framework to assess long-term correlations hidden in the internal organization of the SARS-CoV-2 genome sequence.

SARS-CoV-2 subunit vaccine adjuvants and their signaling pathways

INTRODUCTION

Vaccines are the agreed upon weapon against the COVID-19 pandemic. This review discusses about COVID-19 subunit vaccines adjuvants and their signaling pathways, which could provide a glimpse into the selection of appropriate adjuvants for prospective vaccine development studies.

AREAS COVERED

In the introduction, a brief background about the SARS-CoV-2 pandemic, the vaccine development race and classes of vaccine adjuvants were provided. . The antigen, trial stage, and types of adjuvants were extracted from the included articles and thun assimilated. Finally, the pattern recognition receptors (PRRs), their classes, cognate adjuvants, and potential signaling pathways were comprehended.

EXPERT OPINION

Adjuvants are unsung heroes of subunit vaccines. The in silico studies are very vital in avoiding several costly trial errors and save much work times. The majority of the (pre)clinical studies are promising. It is encouraging that most of the selected adjuvants are novel. Much emphasis must be paid to the optimal paring of antigen-adjuvant-PRRs for obtaining the desired vaccine effect. A good subunit vaccine/adjuvant is one that has high efficacy, safety, dose sparing, and rapid seroconversion rate and broad spectrum of immune response. In the years to come, COVID-19 adjuvanted subunit vaccines are expected to have superior utility than any other vaccines for various reasons.

COVID-19 and Toll-Like Receptor 4 (TLR4): SARS-CoV-2 May Bind and Activate TLR4 to Increase ACE2 Expression, Facilitating Entry and Causing Hyperinflammation

Causes of mortality from COVID-19 include respiratory failure, heart failure, and sepsis/multiorgan failure. TLR4 is an innate immune receptor on the cell surface that recognizes pathogen-associated molecular patterns (PAMPs) including viral proteins and triggers the production of type I interferons and proinflammatory cytokines to combat infection. It is expressed on both immune cells and tissue-resident cells. ACE2, the reported entry receptor for SARS-CoV-2, is only present on ~1-2% of the cells in the lungs or has a low pulmonary expression, and recently, the spike protein has been proposed to have the strongest protein-protein interaction with TLR4. Here, we review and connect evidence for SARS-CoV-1 and SARS-CoV-2 having direct and indirect binding to TLR4, together with other viral precedents, which when combined shed light on the COVID-19 pathophysiological puzzle. We propose a model in which the SARS-CoV-2 spike glycoprotein binds TLR4 and activates TLR4 signalling to increase cell surface expression of ACE2 facilitating entry. SARS-CoV-2 also destroys the type II alveolar cells that secrete pulmonary surfactants, which normally decrease the air/tissue surface tension and block TLR4 in the lungs thus promoting ARDS and inflammation. Furthermore, SARS-CoV-2-induced myocarditis and multiple-organ injury may be due to TLR4 activation, aberrant TLR4 signalling, and hyperinflammation in COVID-19 patients. Therefore, TLR4 contributes significantly to the pathogenesis of SARS-CoV-2, and its overactivation causes a prolonged or excessive innate immune response. TLR4 appears to be a promising therapeutic target in COVID-19, and since TLR4 antagonists have been previously trialled in sepsis and in other antiviral contexts, we propose the clinical trial testing of TLR4 antagonists in the treatment of severe COVID-19. Also, ongoing clinical trials of pulmonary surfactants in COVID-19 hold promise since they also block TLR4.

Designing a conserved peptide-based subunit vaccine against SARS-CoV-2 using immunoinformatics approach

The widespread of coronavirus (COVID-19) is a new global health crisis that poses a threat to the world. The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) originated in bats and was discovered first in Wuhan, Hubei province, China in December 2019. Immunoinformatics and bioinformatics tools were employed for the construction of a multi-epitope subunit vaccine to prevent the diseases. The antigenicity, toxicity and allergenicity of all epitopes used in the construction of the vaccine were predicted and then conjugated with adjuvants and linkers. Vaccine Toll-Like Receptors (2, 3, 4, 8 and 9) complex was also evaluated. The vaccine construct was antigenic, non-toxic and non-allergic, which indicates the vaccines ability to induce antibodies in the host, making it an effective vaccine candidate.

Supplementary Information

The online version contains supplementary material available at 10.1007/s40203-020-00062-x.