Multi-epitope based vaccine against yellow fever virus applying immunoinformatics approaches

Advancing molecular modeling and reverse vaccinology in broad-spectrum yellow fever virus vaccine development

Yellow fever outbreaks are prevalent, particularly in endemic regions. Given the lack of an established treatment for this disease, significant attention has been directed toward managing this arbovirus. In response, we developed a multiepitope vaccine designed to elicit an immune response, utilizing advanced immunoinformatic and molecular modeling techniques. To achieve this, we predicted B- and T-cell epitopes using the sequences from all structural (E, prM, and C) and nonstructural proteins of 196 YFV strains. Through comprehensive analysis, we identified 10 cytotoxic T-lymphocyte (CTL) and 5T-helper (Th) epitopes that exhibited overlap with B-lymphocyte epitopes. These epitopes were further evaluated for their affinity to a wide range of human leukocyte antigen system alleles and were rigorously tested for antigenicity, immunogenicity, allergenicity, toxicity, and conservation. These epitopes were linked to an adjuvant ( β -defensin) and to each other using ligands, resulting in a vaccine sequence with appropriate physicochemical properties. The 3D structure of this sequence was created, improved, and quality checked; then it was anchored to the Toll-like receptor. Molecular Dynamics and Quantum Mechanics/Molecular Mechanics simulations were employed to enhance the accuracy of docking calculations, with the QM portion of the simulations carried out utilizing the density functional theory formalism. Moreover, the inoculation model was able to provide an optimal codon sequence that was inserted into the pET-28a( +) vector for in silico cloning and could even stimulate highly relevant humoral and cellular immunological responses. Overall, these results suggest that the designed multi-epitope vaccine can serve as prophylaxis against the yellow fever virus.

Development of membrane protein-based vaccine against lumpy skin disease virus (LSDV) using immunoinformatic tools

INTRODUCTION

Lumpy skin disease, an economically significant bovine illness, is now found in previously unheard-of geographic regions. Vaccination is one of the most important ways to stop its further spread.

AIM

Therefore, in this study, we applied advanced immunoinformatics approaches to design and develop an effective lumpy skin disease virus (LSDV) vaccine.

METHODS

The membrane glycoprotein was selected for prediction of the different B- and T-cell epitopes by using the immune epitope database. The selected B- and T-cell epitopes were combined with the appropriate linkers and adjuvant resulted in a vaccine chimera construct. Bioinformatics tools were used to predict, refine and validate the 2D, 3D structures and for molecular docking with toll-like receptor 4 using different servers. The constructed vaccine candidate was further processed on the basis of antigenicity, allergenicity, solubility, different physiochemical properties and molecular docking scores.

RESULTS

The in silico immune simulation induced significant response for immune cells. In silico cloning and codon optimization were performed to express the vaccine candidate in Escherichia coli. This study highlights a good signal for the design of a peptide-based LSDV vaccine.

CONCLUSION

Thus, the present findings may indicate that the engineered multi-epitope vaccine is structurally stable and can induce a strong immune response, which should help in developing an effective vaccine towards controlling LSDV infection.

Rational design of multi-epitope-based vaccine by exploring all dengue virus serotypes proteome: an immunoinformatic approach

Millions of people's lives are being devastated by dengue virus (DENV), a severe tropical and subtropical illness spread by mosquitoes and other vectors. Dengue fever may be self-limiting like a common cold or can rapidly progress to catastrophic dengue hemorrhagic fever or dengue shock syndrome. With four distinct dengue serotypes (DENV1-4), each with the potential to contain antibody-boosting complicated mechanisms, developing a dengue vaccine has been an ambitious challenge. Here, we used a computational pan-vaccinomics-based vaccine design strategy (reverse vaccinology) for all 4 DENV serotypes acquired from different regions of the world to develop a new and safe vaccine against DENV. Consequently, only five mapped epitopes from all the 4 serotypes were shown to be extremely effective for the construction of multi-epitope vaccine constructs. The suggested vaccine construct V5 from eight vaccine models was thus classified as an antigenic, non-allergenic, and stable vaccine model. Moreover, molecular docking and molecular dynamics simulation was performed for the V5 vaccine candidate against the HLAs and TRL2 and 4 immunological receptors. Later, the vaccine sequence was transcribed into the cDNA to generate an expression vector for the Escherichia coli K12 strain. Our research suggests that this vaccine design (V5) has promising potential as a dengue vaccine. However, further experimental analysis into the vaccine's efficacy might be required for the V5 proper validation to combat all DENV serotypes.

Integrating core subtractive proteomics and reverse vaccinology for multi-epitope vaccine design against Rickettsia prowazekii endemic typhus

Rickettsia prowazekii is an intracellular, obligate, gram-negative coccobacillus responsible for epidemic typhus. Usually, the infected body louse or its excrement when rubbed into the skin abrasions transmits the disease. The infection with R. prowazekii causes the highest death rate (> 20% without antibiotic treatment and now 1-7%), followed by epidemic typhus, which often manifests in unsanitary conditions (up to 15-30%). Conventionally, vaccine design has required pathogen growth and both assays (in vivo and in vitro), which are costly and time-consuming. However, advancements in bioinformatics and computational biology have accelerated the development of effective vaccine designs, reducing the need for traditional, time-consuming laboratory experiments. Subtractive genomics and reverse vaccinology have become prominent computational methods for vaccine model construction. Therefore, the RefSeq sequence of Rickettsia prowazekii (strain Madrid E) (Proteome ID: UP000002480) was subjected to subtractive genomic analysis, including factors such as non-similarity to host proteome, essentiality, subcellular localization, antigenicity, non-allergenicity, and stability. Based on these parameters, the vaccine design process selected specific proteins such as outer membrane protein R (O05971_RICPR PETR; OmpR). Eventually, the OmpR was subjected to a reverse vaccinology approach that included molecular docking, immunological simulation, and the discovery of B-cell epitopes and MHC-I and MHC-II epitopes. Consequently, a chimeric or multi-epitope-based vaccine was proposed by selecting the V11 vaccine and its 3D structure modeling along with molecular docking against TLR and HLA protein, in silico simulation, and vector designing. The obtained results from this investigation resulted in a new perception of inhibitory ways against Rickettsia prowazekii by instigating novel immunogenic targets. To further assess the efficacy and protective ability of the newly designed V11 vaccine against Rickettsia prowazekii infections, additional evaluation such as in vitro or in vivo immunoassays is recommended.

Combining Phage Display Technology with In Silico-Designed Epitope Vaccine to Elicit Robust Antibody Responses against Emerging Pathogen Tilapia Lake Virus

Antigen epitope identification is a critical step in the vaccine development process and is a momentous cornerstone for the development of safe and efficient epitope vaccines. In particular, vaccine design is difficult when the function of the protein encoded by the pathogen is unknown. The genome of Tilapia lake virus (TiLV), an emerging virus from fish, encodes protein functions that have not been elucidated, resulting in a lag and uncertainty in vaccine development. Here, we propose a feasible strategy for emerging viral disease epitope vaccine development using TiLV. We determined the targets of specific antibodies in serum from a TiLV survivor by panning a Ph.D.-12 phage library, and we identified a mimotope, TYTTRMHITLPI, referred to as Pep3, which provided protection against TiLV after prime-boost vaccination; its immune protection rate was 57.6%. Based on amino acid sequence alignment and structure analysis of the target protein from TiLV, we further identified a protective antigenic site (399TYTTRNEDFLPT410) which is located on TiLV segment 1 (S1). The epitope vaccine with keyhole limpet hemocyanin (KLH-S1399-410) corresponding to the mimotope induced the tilapia to produce a durable and effective antibody response after immunization, and the antibody depletion test confirmed that the specific antibody against S1399-410 was necessary to neutralize TiLV. Surprisingly, the challenge studies in tilapia demonstrated that the epitope vaccine elicited a robust protective response against TiLV challenge, and the survival rate reached 81.8%. In conclusion, this study revealed a concept for screening antigen epitopes of emerging viral diseases, providing promising approaches for development and evaluation of protective epitope vaccines against viral diseases. IMPORTANCE Antigen epitope determination is an important cornerstone for developing efficient vaccines. In this study, we attempted to explore a novel approach for epitope discovery of TiLV, which is a new virus in fish. We investigated the immunogenicity and protective efficacy of all antigenic sites (mimotopes) identified in serum of primary TiLV survivors by using a Ph.D.-12 phage library. We also recognized and identified the natural epitope of TiLV by bioinformatics, evaluated the immunogenicity and protective effect of this antigenic site by immunization, and revealed 2 amino acid residues that play important roles in this epitope. Both Pep3 and S1399-410 (a natural epitope identified by Pep3) elicited antibody titers in tilapia, but S1399-410 was more prominent. Antibody depletion studies showed that anti-S1399-410-specific antibodies were essential for neutralizing TiLV. Our study demonstrated a model for combining experimental and computational screens to identify antigen epitopes, which is attractive for epitope-based vaccine development.

Computational design of candidate multi-epitope vaccine against SARS-CoV-2 targeting structural (S and N) and non-structural (NSP3 and NSP12) proteins

The COVID-19 pandemic caused by SARS-CoV-2 virus has created a global damage and has exposed the vulnerable side of scientific research towards novel diseases. The intensity of the pandemic is huge, with mortality rates of more than 6 million people worldwide in a span of 2 years. Considering the gravity of the situation, scientists all across the world are continuously attempting to create successful therapeutic solutions to combat the virus. Various vaccination strategies are being devised to ensure effective immunization against SARS-CoV-2 infection. SARS-CoV-2 spreads very rapidly, and the infection rate is remarkably high than other respiratory tract viruses. The viral entry and recognition of the host cell is facilitated by S protein of the virus. N protein along with NSP3 is majorly responsible for viral genome assembly and NSP12 performs polymerase activity for RNA synthesis. In this study, we have designed a multi-epitope, chimeric vaccine considering the two structural (S and N protein) and two non-structural proteins (NSP3 and NSP12) of SARS-CoV-2 virus. The aim is to induce immune response by generating antibodies against these proteins to target the viral entry and viral replication in the host cell. In this study, computational tools were used, and the reliability of the vaccine was verified using molecular docking, molecular dynamics simulation and immune simulation studies in silico. These studies demonstrate that the vaccine designed shows steady interaction with Toll like receptors with good stability and will be effective in inducing a strong and specific immune response in the body.Communicated by Ramaswamy H. Sarma.

Designing of cytotoxic T lymphocyte-based multi-epitope vaccine against SARS-CoV2: a reverse vaccinology approach

SARS-CoV2 is a single-stranded RNA virus, gaining much attention after it out broke in China in December 2019. The virus rapidly spread to several countries around the world and caused severe respiratory illness to humans. Since the outbreak, researchers around the world have devoted maximum resources and effort to develop a potent vaccine that would offer protection to uninfected individuals against SARS-CoV2. Reverse vaccinology is a relatively new approach that thrives faster in vaccine research. In this study, we constructed Cytotoxic T Lymphocytes (CTL)-based multi-epitope vaccine using hybrid epitope prediction methods. A total of 121 immunogenic CTL epitopes were screened by various sequence-based prediction methods and docked with their respective HLA alleles using the AutoDock Vina v1.1.2. In all, 17 epitopes were selected based on their binding affinity, followed by the construction of multi-epitope vaccine by placing the appropriate linkers between the epitopes and tuberculosis heparin-binding hemagglutinin (HBHA) adjuvant. The final vaccine construct was modeled by the I-TASSER server and the best model was further validated by ERRAT, ProSA, and PROCHECK servers. Furthermore, the molecular interaction of the constructed vaccine with TLR4 was assessed by ClusPro 2.0 and PROtein binDIng enerGY prediction (PRODIGY) server. The immune simulation analysis confirms that the constructed vaccine was capable of inducing long-lasting memory T helper (Th) and CTL responses. Finally, the nucleotide sequence was codon-optimized by the JCAT tool and cloned into the pET21a (+) vector. The current results reveal that the candidate vaccine is capable of provoking robust CTL response against the SARS-CoV2.Communicated by Ramaswamy H. Sarma.

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.

Reverse vaccinology approach for multi-epitope centered vaccine design against delta variant of the SARS-CoV-2

The ongoing COVID-19 outbreak, initially identified in Wuhan, China, has impacted people all over the globe and new variants of concern continue to threaten hundreds of thousands of people. The delta variant (first reported in India) is currently classified as one of the most contagious variants of SARS-CoV-2. It is estimated that the transmission rate of delta variant is 225% times faster than the alpha variant, and it is causing havoc worldwide (especially in the USA, UK, and South Asia). The mutations found in the spike protein of delta variant make it more infective than other variants in addition to ruining the global efficacy of available vaccines. In the current study, an in silico reverse vaccinology approach was applied for multi-epitope vaccine construction against the spike protein of delta variant, which could induce an immune response against COVID-19 infection. Non-toxic, highly conserved, non-allergenic and highly antigenic B-cell, HTL, and CTL epitopes were identified to minimize adverse effects and maximize the efficacy of chimeric vaccines that could be developed from these epitopes. Finally, V1 vaccine construct model was shortlisted and 3D modeling was performed by refinement, docking against HLAs and TLR4 protein, simulation and in silico expression. In silico evaluation showed that the designed chimeric vaccine could elicit an immune response (i.e., cell-mediated and humoral) identified through immune simulation. This study could add to the efforts of overcoming global burden of COVID-19 particularly the variants of concern.

Design of Multi-Epitope Vaccine for Staphylococcus saprophyticus: Pan-Genome and Reverse Vaccinology Approach

Staphylococcus saprophyticus is a Gram-positive coccus responsible for the occurrence of cystitis in sexually active, young females. While effective antibiotics against this organism exist, resistant strains are on the rise. Therefore, prevention via vaccines appears to be a viable solution to address this problem. In comparison to traditional techniques of vaccine design, computationally aided vaccine development demonstrates marked specificity, efficiency, stability, and safety. In the present study, a novel, multi-epitope vaccine construct was developed against S. saprophyticus by targeting fully sequenced proteomes of its five different strains, which were examined using a pangenome and subtractive proteomic strategy to characterize prospective vaccination targets. The three immunogenic vaccine targets which were utilized to map the probable immune epitopes were verified by annotating the entire proteome. The predicted epitopes were further screened on the basis of antigenicity, allergenicity, water solubility, toxicity, virulence, and binding affinity towards the DRB*0101 allele, resulting in 11 potential epitopes, i.e., DLKKQKEKL, NKDLKKQKE, QDKLKDKSD, NVMDNKDLE, TSGTPDSQA, NANSDGSSS, GSDSSSSNN, DSSSSNNDS, DSSSSDRNN, SSSDRNNGD, and SSDDKSKDS. All these epitopes have the efficacy to cover 99.74% of populations globally. Finally, shortlisted epitopes were joined together with linkers and three different adjuvants to find the most stable and immunogenic vaccine construct. The top-ranked vaccine construct was further scrutinized on the basis of its physicochemical characterization and immunological profile. The non-allergenic and antigenic features of modeled vaccine constructs were initially validated and then subjected to docking with immune receptor major histocompatibility complex I and II (MHC-I and II), resulting in strong contact. In silico cloning validations yielded a codon adaptation index (CAI) value of 1 and an ideal percentage of GC contents (46.717%), indicating a putative expression of the vaccine in E. coli. Furthermore, immune simulation demonstrated that, after injecting the proposed MEVC, powerful antibodies were produced, resulting in the sharpest peaks of IgM + IgG formation (>11,500) within 5 to 15 days. Experimental testing against S. saprophyticus can evaluate the safety and efficacy of these prophylactic vaccination designs.

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.

Cytotoxic T-Cell-Based Vaccine against SARS-CoV-2: A Hybrid Immunoinformatic Approach

This paper presents an alternative vaccination platform that provides long-term cellular immune protection mediated by cytotoxic T-cells. The immune response via cellular immunity creates superior resistance to viral mutations, which are currently the greatest threat to the global vaccination campaign. Furthermore, we also propose a safer, more facile, and physiologically appropriate immunization method using either intranasal or oral administration. The underlying technology is an adaptation of synthetic long peptides (SLPs) previously used in cancer immunotherapy. The overall quality of the SLP constructs was validated using in silico methods. SLPs comprising HLA class I and class II epitopes were designed to stimulate antigen cross-presentation and canonical class II presentation by dendritic cells. The desired effect is a cytotoxic T cell-mediated prompt and specific immune response against the virus-infected epithelia and a rapid and robust virus clearance. Epitopes isolated from COVID-19 convalescent patients were screened for HLA class I and class II binding (NetMHCpan and NetMHCIIpan) and highest HLA population coverage (IEDB Population Coverage). 15 class I and 4 class II epitopes were identified and used for this SLP design. The constructs were characterized based on their toxicity (ToxinPred), allergenicity (AllerCatPro), immunogenicity (VaxiJen 2.0), and physico-chemical parameters (ProtParam). Based on in silico predictions, out of 60 possible SLPs, 36 candidate structures presented a high probability to be immunogenic, non-allergenic, non-toxic, and stable. 3D peptide folding followed by 3D structure validation (PROCHECK) and molecular docking studies (HADDOCK 2.4) with Toll-like receptors 2 and 4 provided positive results, suggestive for favorable antigen presentation and immune stimulation.

Pan-Genome Reverse Vaccinology Approach for the Design of Multi-Epitope Vaccine Construct against Escherichia albertii

Escherichia albertii is characterized as an emerging pathogen, causing enteric infections. It is responsible for high mortality rate, especially in children, elderly, and immunocompromised people. To the best of our knowledge, no vaccine exists to curb this pathogen. Therefore, in current study, we aimed to identify potential vaccine candidates and design chimeric vaccine models against Escherichia albertii from the analysis of publicly available data of 95 strains, using a reverse vaccinology approach. Outer-membrane proteins (n = 4) were identified from core genome as vaccine candidates. Eventually, outer membrane Fimbrial usher (FimD) protein was selected as a promiscuous vaccine candidate and utilized to construct a potential vaccine model. It resulted in three epitopes, leading to the design of twelve vaccine constructs. Amongst these, V6 construct was found to be highly immunogenic, non-toxic, non-allergenic, antigenic, and most stable. This was utilized for molecular docking and simulation studies against six HLA and two TLR complexes. This construct can therefore be used for pan-therapy against different strains of E. albertii and needs to be tested in vitro and in vivo.

A Computational Reverse Vaccinology Approach for the Design and Development of Multi-Epitopic Vaccine Against Avian Pathogen Mycoplasma gallisepticum

Avian mycoplasma is a bacterial disease causing chronic respiratory disease (CRD) in poultry industries with high economic losses. The eradication of this disease still remains as a challenge. A multi-epitope prophylactic vaccine aiming the antigenic proteins of Mycoplasma gallisepticum can be a capable candidate to eradicate this infection. The present study is focused to design a multi-epitope vaccine candidate consisting of cytotoxic T-cell (CTL), helper T-cell (HTL), and B-cell epitopes of antigenic proteins, using immunoinformatics strategies. The multi-epitopic vaccine was designed, and its tertiary model was predcited, which was further refined and validated by computational tools. After initial validation, molecular docking was performed between multi-epitope vaccine construct and chicken TLR-2 and 5 receptors, which predicted effective binding. The in silico results specify the structural stability, precise specificity, and immunogenic response of the designed multi-epitope vaccine, and it could be an appropriate vaccine candidate for the M. gallisepticum infection.

A peptide-based subunit candidate vaccine against SARS-CoV-2 delivered by biodegradable mesoporous silica nanoparticles induced high humoral and cellular immunity in mice

Development of a rapidly scalable vaccine is still an urgent task to halt the spread of COVID-19. We have demonstrated biodegradable mesoporous silica nanoparticles (BMSNs) as a good drug delivery carrier for tumor therapy. In this study, seven linear B cell epitopes and three CD8⁺ T cell epitopes were screened from the spike (S) glycoprotein of SARS-CoV-2 by computer-based immunoinformatic approaches for vaccine design. A nanoparticle-based candidate vaccine (B/T@BMSNs) against SARS-CoV-2 was rapidly prepared by encapsulating these ten epitope peptides within BMSNs, respectively. BMSNs with potential biodegradability, proved to possess excellent safety in vitro and in vivo, could efficiently deliver epitope peptides into the cytoplasm of RAW264.7 cells. Strong Th1-biased humoral and cellular immunity were induced by B/T@BMSNs in mice and all the 10 selected epitopes were identified as effective antigen epitopes, which could induce robust peptide-specific immune response. The elicited functional antibody could bind to the recombinant S protein and block the binding of the S protein to the ACE-2 receptor. These results demonstrate the potential of a nanoparticles vaccine platform based on BMSNs to rapidly develop peptide-based subunit vaccine candidates against SARS-CoV-2.

In silico designing of vaccine candidate against Clostridium difficile

Clostridium difficile is a spore-forming gram-positive bacterium, recognized as the primary cause of antibiotic-associated nosocomial diarrhoea. Clostridium difficile infection (CDI) has emerged as a major health-associated infection with increased incidence and hospitalization over the years with high mortality rates. Contamination and infection occur after ingestion of vegetative spores, which germinate in the gastro-intestinal tract. The surface layer protein and flagellar proteins are responsible for the bacterial colonization while the spore coat protein, is associated with spore colonization. Both these factors are the main concern of the recurrence of CDI in hospitalized patients. In this study, the CotE, SlpA and FliC proteins are chosen to form a multivalent, multi-epitopic, chimeric vaccine candidate using the immunoinformatics approach. The overall reliability of the candidate vaccine was validated in silico and the molecular dynamics simulation verified the stability of the vaccine designed. Docking studies showed stable vaccine interactions with Toll‐Like Receptors of innate immune cells and MHC receptors. In silico codon optimization of the vaccine and its insertion in the cloning vector indicates a competent expression of the modelled vaccine in E. coli expression system. An in silico immune simulation system evaluated the effectiveness of the candidate vaccine to trigger a protective immune response.

Immunoinformatics Identification of B- and T-Cell Epitopes in the RNA-Dependent RNA Polymerase of SARS-CoV-2

SARS-CoV-2 (Severe acute respiratory syndrome coronavirus-2) is a newly emerged beta coronavirus and etiolating agent of COVID-19. Considering the unprecedented increasing number of COVID-19 cases, the World Health Organization declared a public health emergency internationally on 11th March 2020. However, existing drugs are insufficient in dealing with this contagious virus infection; therefore, a vaccine is exigent to curb this pandemic disease. In the present study, B- and T-cell immune epitopes were identified for RdRp (RNA-dependent RNA polymerase) protein using immunoinformatic techniques, which is proved to be a rapid and efficient method to explore the candidate peptide vaccine. Subsequently, antigenicity and interactions with HLA (human leukocyte antigen) alleles were estimated. Further, physicochemical properties, allergenicity, toxicity, and stability of RdRp protein were evaluated to demonstrate the specificity of the epitope candidates. Interestingly, we identified a total of 36 B-cell and 16 T-cell epitopes using epitopes predictive tools. Among the predicted epitopes, 26 B-cell and 9 T-cell epitopes showed non-allergenic, non-toxic, and highly antigenic properties. Altogether, our study revealed that RdRp of SARS-CoV-2 (an epitope-based peptide fragment) can be a potentially good candidate for the development of a vaccine against SARS-CoV-2.

Immunoinformatics analysis to design novel epitope based vaccine candidate targeting the glycoprotein and nucleoprotein of Lassa mammarenavirus (LASMV) using strains from Nigeria

Lassa mammarenavirus (LASMV) is responsible for a specific type of acute viral hemorrhagic fever known as Lassa fever. Lack of effective treatments and counter-measures against the virus has resulted in a high mortality rate in its endemic regions. Therefore, in this study, a novel epitope-based vaccine has been designed using the methods of immunoinformatics targeting the glycoprotein and nucleoprotein of the virus. After numerous robust analyses, two CTL epitopes, eight HTL epitopes and seven B-cell epitopes were finally selected for constructing the vaccine. All these most promising epitopes were found to be antigenic, non-allergenic, nontoxic and non-human homolog, which made them suitable for designing the subunit vaccine. Furthermore, the selected T-cell epitopes which were found to be fully conserved across different isolates of the virus, were also considered for final vaccine construction. After that, numerous validation experiments, i.e. molecular docking, molecular dynamics simulation and immune simulation were conducted, which predicted that our designed vaccine should be stable within the biological environment and effective in combating the LASMV infection. In the end, codon adaptation and in silico cloning studies were performed to design a recombinant plasmid for producing the vaccine industrially. However, further in vitro and in vivo assessments should be done on the constructed vaccine to finally confirm its safety and efficacy.Communicated by Ramaswamy H. Sarma.

A Putative Prophylactic Solution for COVID-19: Development of Novel Multiepitope Vaccine Candidate against SARS-COV-2 by Comprehensive Immunoinformatic and Molecular Modelling Approach

The outbreak of 2019-novel coronavirus (SARS-CoV-2) that causes severe respiratory infection (COVID-19) has spread in China, and the World Health Organization has declared it a pandemic. However, no approved drug or vaccines are available, and treatment is mainly supportive and through a few repurposed drugs. The urgency of the situation requires the development of SARS-CoV-2-based vaccines. Immunoinformatic and molecular modelling are time-efficient methods that are generally used to accelerate the discovery and design of the candidate peptides for vaccine development. In recent years, the use of multiepitope vaccines has proved to be a promising immunization strategy against viruses and pathogens, thus inducing more comprehensive protective immunity. The current study demonstrated a comprehensive in silico strategy to design stable multiepitope vaccine construct (MVC) from B-cell and T-cell epitopes of essential SARS-CoV-2 proteins with the help of adjuvants and linkers. The integrated molecular dynamics simulations analysis revealed the stability of MVC and its interaction with human Toll-like receptors (TLRs), which trigger an innate and adaptive immune response. Later, the in silico cloning in a known pET28a vector system also estimated the possibility of MVC expression in Escherichia coli. Despite that this study lacks validation of this vaccine construct in terms of its efficacy, the current integrated strategy encompasses the initial multiple epitope vaccine design concepts. After validation, this MVC can be present as a better prophylactic solution against COVID-19.

An immunoinformatics study on the spike protein of SARS-CoV-2 revealing potential epitopes as vaccine candidates

Background

The pandemic situation of SARS-CoV-2 infection has sparked global concern due to the disease COVID-19 caused by it. Since the first cluster of confirmed cases in China in December 2019, the infection has been reported across the continents and inflicted upon a substantial number of populations.

Method

This study is focused on immunoinformatics analyses of the SARS-CoV-2 spike glycoprotein (S protein) which is key for the viral attachment to human host cells. Computational analyses were carried out for the prediction of B-cell and T-cell (MHC class I and II) epitopes of S protein and the analyses were extended further for the prediction of their immunogenic properties. The interaction and binding affinity of T-cell epitopes with HLA-B7 were also investigated by molecular docking.

Result

Three distinct epitopes for vaccine design were predicted from the sequence of S protein. The potential B-cell epitope was KNHTSPDVDLG possessing the highest antigenicity score of 1.4039 among other B-cell epitopes. T-cell epitope for human MHC class I was VVVLSFELL with an antigenicity score of 1.0909 and binding ability to 29 MHC-I alleles. The predicted T-cell epitope for human MHC class II molecule was VVIGIVNNT with a corresponding 1.3063 antigenicity score, less digesting enzymes, and 7 MHC-II alleles binding ability. All these three peptides were predicted to be highly antigenic, non-allergenic, and non-toxic. Analyses of the physiochemical properties of these predicted epitopes indicate their stable nature for plausible vaccine design. Furthermore, molecular docking investigation between the MHC class-I epitopes and human HLA-B7 reflects the stable interaction with high affinity among them.

Conclusion

The present study posits three potential epitopes of S protein of SARS-CoV-2 predicted by immunoinformatic methods based on their immunogenic properties and interactions with the host counterpart that can facilitate the development of vaccine against SARS-CoV-2. This study can act as the springboard for the future development of the COVID-19 vaccine.

Exploring membrane proteins of Leishmania major to design a new multi-epitope vaccine using immunoinformatics approach

Leishmaniasis is one of the major global endemic diseases. Among all the different forms of the disease, cutaneous Leishmaniasis has the highest prevalence worldwide. Treatment with current drugs has not had a significant effect on the improvement of the disease. An attempt to replace an appropriate vaccine that can stimulate host cellular immunity and induce the response of Major histocompatibility complex I (MHCI) and Major histocompatibility complex II (MHCII) against Leishmania is essential. Vaccine production remains a challenge despite the use of different antigens for vaccination against Leishmania major. Hence, we were used the immunoinformatics approach to design a new multi-epitope vaccine against L. major using immunogenic outer membrane proteins. Helper T-lymphocyte (HTL) and Cytotoxic T lymphocyte (CTL) epitopes were predicted and for final confirmation of the selected epitopes, docking analysis, and molecular dynamics simulation was performed. Then, GDGDG linker and profilin adjuvant were added to enhance the immunity of vaccines. The designed vaccine was evaluated in terms of molecular weight, PI, immunogenicity, and allergenicity. Moreover, the secondary and three-dimensional structure of the final construct was identified. In silico cloning approach was carried out to improve expression of the vaccine construct. Finally, molecular docking, followed by molecular dynamic was performed to determine the interaction between multi-epitope vaccine and TLR11. We hope that the designed vaccine can be a good candidate for the development of cutaneous leishmaniasis vaccine. but its effectiveness should be assessed in vivo.

Anti-Flavivirus Vaccines: Review of the Present Situation and Perspectives of Subunit Vaccines Produced in Escherichia coli

This article aims to review the present status of anti-flavivirus subunit vaccines, both those at the experimental stage and those already available for clinical use. Aspects regarding development of vaccines to Yellow Fever virus, (YFV), Dengue virus (DENV), West Nile virus (WNV), Zika virus (ZIKV), and Japanese encephalitis virus (JEV) are highlighted, with particular emphasis on purified recombinant proteins generated in bacterial cells. Currently licensed anti-flavivirus vaccines are based on inactivated, attenuated, or virus-vector vaccines. However, technological advances in the generation of recombinant antigens with preserved structural and immunological determinants reveal new possibilities for the development of recombinant protein-based vaccine formulations for clinical testing. Furthermore, novel proposals for multi-epitope vaccines and the discovery of new adjuvants and delivery systems that enhance and/or modulate immune responses can pave the way for the development of successful subunit vaccines. Nonetheless, advances in this field require high investments that will probably not raise interest from private pharmaceutical companies and, therefore, will require support by international philanthropic organizations and governments of the countries more severely stricken by these viruses.

Immuno-informatics approach for multi-epitope vaccine designing against SARS-CoV-2

The novel Corona Virus Disease 2019 (COVID-19) pandemic has set the fatality rates ablaze across the world. So, to combat this disease, we have designed a multi-epitope vaccine from various proteins of Severe Acute Respiratory Syndrome Corona virus 2 (SARS-CoV-2) with an immuno-informatics approach, validated in silico to be stable, non-allergic and antigenic. Cytotoxic T-cell, helper T-cell, and B-cell epitopes were computationally predicted from six conserved protein sequences among four viral strains isolated across the world. The T-cell epitopes, overlapping with the B-cell epitopes, were included in the vaccine construct to assure the humoral and cell-mediated immune response. The beta-subunit of cholera toxin was added as an adjuvant at the N-terminal of the construct to increase immunogenicity. Interferon-gamma inducing epitopes were even predicted in the vaccine. Molecular docking and binding energetics studies revealed strong interactions of the vaccine with immune-stimulatory toll-like receptors (TLR) −2, 3, 4. Molecular dynamics simulation of the vaccine ensured in vivo stability in the biological system. The immune simulation of vaccine evinced elevated immune response. The efficient translation of the vaccine in an expression vector was assured utilizing in silico cloning approach. Certainly, such a vaccine construct could reliably be effective against COVID-19.

The effects of synonymous codon usages on genotypic formation of open reading frames in hepatitis E virus

Hepatitis E virus (HEV) infection has emerged as an important public health issue. As a zoonotic RNA virus, new strains are continuously discovered from human or various animal species. However, the capability of cross-species infection varies largely among different strains. Because the classical nucleotide-based genotyping system provides little functional insight, this study aimed to comprehensively investigate codon usage of the HEV coding regions for better understanding the evolutional orientation, virus-host interaction and cross-species transmission. We observed significant differences of the four nucleotide usages in the three open reading frames, indicating that the evolutional tendency of HEV caused by mutation pressure is modified by the evolutional dynamic related to positive selection. Furthermore, significant differences of nucleotide usages were found among HEV isolated from different host species, suggesting an important role of natural selection related to the host. Analysis of effective number of codons revealed distinct degrees of biased codon usage caused by mutation pressure or the host. Finally, we have mapped the similarity levels of the overall codon usage between the virus and the host to assess the potential of cross-species infection. Thus, this study has provided a novel aspect for better understanding the HEV genetic orientation and the zoonotic nature.

A candidate multi-epitope vaccine against SARS-CoV-2

In the past two decades, 7 coronaviruses have infected the human population, with two major outbreaks caused by SARS-CoV and MERS-CoV in the year 2002 and 2012, respectively. Currently, the entire world is facing a pandemic of another coronavirus, SARS-CoV-2, with a high fatality rate. The spike glycoprotein of SARS-CoV-2 mediates entry of virus into the host cell and is one of the most important antigenic determinants, making it a potential candidate for a vaccine. In this study, we have computationally designed a multi-epitope vaccine using spike glycoprotein of SARS-CoV-2. The overall quality of the candidate vaccine was validated in silico and Molecular Dynamics Simulation confirmed the stability of the designed vaccine. Docking studies revealed stable interactions of the vaccine with Toll-Like Receptors and MHC Receptors. The in silico cloning and codon optimization supported the proficient expression of the designed vaccine in E. coli expression system. The efficiency of the candidate vaccine to trigger an effective immune response was assessed by an in silico immune simulation. The computational analyses suggest that the designed multi-epitope vaccine is structurally stable which can induce specific immune responses and thus, can be a potential vaccine candidate against SARS-CoV-2.

Designing of a multi-epitope vaccine candidate against Nipah virus by in silico approach: a putative prophylactic solution for the deadly virus

Nipah virus (NPV) is one of the most notorious viruses with a very high fatality rate. Because of the recurrent advent of this virus and its severe neurological implications, often leading to high mortality, the WHO R&D Blueprint, 2018 has listed the Nipah virus as one of the emerging infectious diseases requiring urgent research and development effort. Yet there is a major layback in the development of effective vaccines or drugs against NPV. In this study, we have designed a stable multivalent vaccine combining several T-cell and B-cell epitopes of the essential Nipah viral proteins with the help of different ligands and adjuvants which can effectively induce both humoral and cellular immune responses in human. Different advanced immune-informatic tools confirm the stability, high immunogenicity and least allergenicity of the vaccine candidate. The standard molecular dynamic cascade analysis validates the stable interaction of the vaccine construct with the human Toll-like receptor 3 (TLR3) complex. Later, codon optimization and in silico cloning in a known pET28a vector system shows the possibility for the expression of this vaccine in a simple organism like E.coli. It is believed that with further in vitro and in vivo validation, this vaccine construct can pose to be a better prophylactic solution to the Nipah viral disease. Communicated by Ramaswamy H. Sarma.

Extensive immunoinformatics study for the prediction of novel peptide-based epitope vaccine with docking confirmation against envelope protein of Chikungunya virus: a computational biology approach

Chikungunya virus (CHIKV) instigating Chikungunya fever is a global infective menace resulting in high fever, weakened joint-muscle pain, and brain inflammation. Inaccessibility and unavailability of effective drugs have led us to an uncertain arena when it comes to providing proper medical treatment to the affected people. In this study, authentic encroachment has been made concerning the peptide-based epitope vaccine designing against CHIKV. A Proteome-wide search was performed to locate a conserved portion among the accessible viral outer membrane proteins which showcase a remarkable immune response using specific immunoinformatics and docking simulation tools. Primarily, the most probable immunogenic envelope glycoproteins E1 and E2 were identified from the UniProt database depending on their antigenicity scores. Subsequently, we selected two distinctive sequences "SEDVYANTQLVLQRP" and "IMLLYPDHPTLLSYR" in both E1 and E2 glycoproteins respectively. These two sequences identified as the most potent T and B cell epitope-based peptides as they interacted with 6 and 7 HLA-I and 5 HLA-II molecules with an extremely low IC50 score that was verified by molecular docking. Moreover, the sequences possess no allergenicity and are certainly located outside the transmembrane region. In addition, the sequences exhibited 88.46% and 100.00% Conservancy, covering high population coverage of 89.49% to 94.74% and 60.51% to 88.87% respectively in endemic countries. The identified peptide SEDVYANTQLVLQRP and IMLLYPDHPTLLSYR can be utilized next for the development of peptide-based epitope vaccine contrary to CHIKV, so further documentations and experimentations like Antigen testing, Antigen production, Clinical trials are needed to prove the validity of it. Communicated by Ramaswamy H. Sarma.

Adjacent dimer epitope of envelope protein as an important region for Zika virus serum neutralization: a computational investigation

The recent emergence of Zika virus (ZIKV) has affected many countries, with severe clinical manifestations such as fetal microcephaly and Guillain-Barré syndrome. However, even though it is a major public health concern, there is no approved treatment available. Structural knowledge of the main neutralization regions of the envelope (E) protein of ZIKV and its interactions with neutralizing antibodies (nAbs) are crucial for the rational development of subunit vaccines and establishment of antibody-based interventions. In this study we screened from public data hot spot epitopes in conserved regions of ZIKV E protein that are nAbs targets. The result points to a conserved epitope located at domain II of the ZIKV E protein, namely adjacent dimer epitope, which is the ZIKV-117 and Z20 nAbs target. Although these two nAbs have been isolated from different donors, we have demonstrated, from structural and energetic details obtained by molecular dynamics of native and mutants, that hot spots residues of the epitope are the same for these nAbs, thereby indicating that they may share similar binding and neutralization mechanism. This convergence of information between these nAbs is important because both are potential targets for the development of therapies against ZIKV and only Z20 has its sequence and its complex structure with ZIKV E protein determined. Finally, these findings also contribute to existing knowledge, by fine mapping of the epitope/paratope residue pairs that are important for biotechnological development of therapies such as epitope mimetics for subunit vaccines and the rational design for antibody-based interventions against ZIKV. Communicated by Ramaswamy H. Sarma.