In silico design of recombinant multi-epitope vaccine against influenza A virus

Design of a peptide-based vaccine against human respiratory syncytial virus using a reverse vaccinology approach: evaluation of immunogenicity, antigenicity, allergenicity, and toxicity

Background

Attempts to develop an hRSV vaccine have faced safety and efficacy challenges, with only three FDA-approved vaccines (Moderna's Mresvia, Pfizer's Abrysvo, and GSK's Arexvy) available. These vaccines are limited to individuals over 60 years, require boosters, and only reduce disease severity without clearing the infection. Therefore, we employed a reverse vaccinology approach in this study to identify the most promising antigenic epitopes capable of eliciting a robust and protective immune response.

Methodology

This study employed computational techniques to design a novel multi-epitope vaccine targeting hRSV. Using bioinformatics tools, candidate epitopes were identified from conserved viral proteins (F and G glycoproteins), assessing their immunogenicity, antigenicity, and allergenicity. Key tools included ExPASy, ProtParam, VaxiJen v2.0, AllergenFP v1.0, AllerTOP v2.0, NetCTL v1.2, IEDB, and Toxin-Pred. The vaccine construct was assessed for stability and toxicity through in silico analyses. We then characterized its kinetic properties, evaluated its structural integrity, and analyzed its interactions with Toll-like receptors (TLRs) using molecular docking, modeling, and refinement with AlphaFold3 and ClusPro.

Results

The designed constructs showed strong antigenicity (0.5996 for F-based and 0.6048 for G-based vaccine), non-allergenicity, and stability (instability index <40). Among these, most amino acids were in the extracellular domain of the construct. Molecular docking and dynamics simulations indicated strong binding interactions with TLR1 and TLR4 and minimal RMSF fluctuations, which ensured structural stability. Strong humoral and cellular responses were suggested by in silico immune simulation demonstrating robust immune activation, with high levels of IgG, IgM, IL-2, and IFN-γ. The physical and chemical analyses revealed that the majority of amino acids from the F and G proteins were located in the extracellular domain of the construct. The presence of signal peptide cleavage sites in both glycoprotein components further facilitates antigen presentation to the immune system.

Conclusions

This study presents a promising peptide-based vaccine candidate against hRSV that can effectively engage the immune system, showing strong immunogenicity and antigenicity. Future in vitro and in vivo studies are essential to evaluate the ability of the multi-epitope vaccine candidate to stimulate both humoral and cell-mediated immune responses and to assess its efficacy and safety profile.

One Health Approach to the Computational Design of a Lipoprotein-Based Multi-Epitope Vaccine Against Human and Livestock Tuberculosis

Tuberculosis (TB) remains a major cause of ill health and one of the leading causes of death worldwide, with about 1.25 million deaths estimated in 2023. Control measures have focused principally on early diagnosis, the treatment of active TB, and vaccination. However, the widespread emergence of anti-tuberculosis drug resistance remains the major public health threat to progress made in global TB care and control. Moreover, the Bacillus Calmette-Guérin (BCG) vaccine, the only licensed vaccine against TB in children, has been in use for over a century, and there have been considerable debates concerning its effectiveness in TB control. A multi-epitope vaccine against TB would be an invaluable tool to attain the Global Plan to End TB 2023-2030 target. A rational approach that combines several B-cell and T-cell epitopes from key lipoproteins was adopted to design a novel multi-epitope vaccine candidate. In addition, interactions with TLR4 were implemented to assess its ability to elicit an innate immune response. The conservation of the selected proteins suggests the possibility of cross-protection in line with the One Health approach to disease control. The vaccine candidate was predicted to be both antigenic and immunogenic, and immune simulation analyses demonstrated its ability to elicit both humoral and cellular immune responses. Protein-protein docking and normal-mode analyses of the vaccine candidate with TLR4 predicted efficient binding and stable interaction. This study provides a promising One Health approach for the design of multi-epitope vaccines against human and livestock tuberculosis. Overall, the designed vaccine candidate demonstrated immunogenicity and safety features that warrant further experimental validation in vitro and in vivo.

In silico design of a trivalent multi-epitope global-coverage vaccine-candidate protein against influenza viruses: evaluation by molecular dynamics and immune system simulation

Hemagglutinin (HA), a variable viral surface protein, is essential for influenza vaccine development. Annually, traditional trivalent vaccines containing influenza A/H1N1, A/H3N2 and B viruses are administered globally, which are not very effective for the mutations in HA protein. The aim of this study was to design a multi-epitope vaccine containing epitopes of the HA protein of H1N1, H3N2 and B viruses using immunoinformatics methods. The HA protein epitope prediction was performed using Immune Epitope Database. Toxicity, antigenicity and conservancy of the epitopes were evaluated using ToxinPred, VaxiJen and Epitope Conservancy Analysis tools, respectively. Then, nontoxic, antigenic and high conserved epitopes with high prediction scores were selected. Their binding affinity was evaluated against human and mouse MHC class I and II molecules using the HPEPDOCK tool. Physicochemical properties and post-translational modifications were evaluated using ProtParam, SOLpro and MusiteDeep tools, respectively. Top selected epitopes were joined using linkers to produce the best effective recombinant trivalent vaccine candidate to elicit cellular and humoral immune responses in mouse and human host models. These sequences were modeled and verified. By evaluating the results of various analyses of all models and the most similarity to the native HA protein, model 5 was selected as the best model. Finally, in silico cloning of this model as vaccine candidate was performed in pET21. This study was a computer-aided analysis for a multi-epitope trivalent recombinant vaccine candidate against influenza viruses. The efficiency of our best model of vaccine candidates should be validated using in vitro and in vivo studies. Communicated by Ramaswamy H. Sarma.

Computational design, expression, and characterization of a Plasmodium falciparum multi-epitope, multi-stage vaccine candidate (PfCTMAG)

Malaria, a tropical disease, claims the lives of thousands of people annually and the development of resistance to insecticides and antimalarial drugs poses a great challenge to current prevention and control strategies. Current malaria vaccines are limited in efficacy, duration of protection, and safety, due to the high antigenic diversity and complex life cycle of the Plasmodium parasite. This study sought to design and assess a more effective multi-stage, multi-epitope vaccine candidate for the control of malaria. A multi-epitope malaria vaccine candidate was designed in silico using multiple antigens from both the pre-erythrocytic and erythrocytic stages, expressed in bacteria, and its sero-reactivity to antibodies in plasma from malaria-positive (cases) and negative individuals (controls) was assessed using enzyme-linked immunosorbent assay (ELISA). Immunization experiments were equally conducted with BALB/c mice. In-silico analysis revealed that the designed antigen, PfCTMAG (Plasmodium falciparum Circumsporozoite, Thrombospondin-related adhesion protein, Merozoite surface protein 2, Apical asparagine (Asn)-rich protein and Glutamate-Rich Protein), effectively bound to Toll-like receptor 4 (TLR-4) and triggered a strong immune response. In sero-reactivity studies, malaria-positives (cases) had higher anti-PfCTMAG IgG ( p  = 0.024) and IgM ( p < 0.001) levels compared to malaria negatives (controls). The mice immunized with PfCTMAG did not show adverse reactions and had higher levels of IgG antibodies (p = 0.002) compared to controls, thereby validating the safety and immunogenicity of PfCTMAG as a promising vaccine candidate.

Negative Association of Gulf War Illness Symptomatology with Predicted Binding Affinity of Anthrax Vaccine Antigen to Human Leukocyte (HLA) Class II Molecules

BACKGROUND

Anthrax is a serious disease caused by Bacillus anthracis (B. anthracis) with a very high mortality when the spores of B. anthracis are inhaled (inhalational anthrax). Aerosolized B. anthracis spores can be used as a deadly bioweapon. Vaccination against anthrax is the only effective preventive measure and, hence, the anthrax vaccine was administered to United States (and other) troops during the 1990-91 Gulf War. However, the anthrax vaccine is not harmless, and the anthrax vaccination has been linked to the occurrence and severity of Gulf War Illness (GWI), a debilitating Chronic Multisymptom Illness (CMI). We hypothesized that this is partly due to the combination of two factors, namely (a) the cytotoxicity of the antigen (anthrax Protective Antigen, PA) contained in the vaccine, and (b) the Human Leukocyte Antigen (HLA) genotype of susceptible vaccinees, reducing their ability to make antibodies against the cytotoxic PA.

METHOD

Here, we tested this hypothesis by determining the association between severity of GWI symptoms in 458 GW veterans and the overall strength of the binding affinity of the PA epitopes to the specific six Human Leukocyte Antigen (HLA) Class II alleles carried by each individual (two of each of the HLA-II genes: DPB1, DQB1, DRB1), responsible for initiating the process of antibody production in otherwise immunocompetent individuals, estimated in silico.

RESULTS

We found that the severity of GWI symptomatology was negatively and significantly correlated with the strength of the predicted binding affinity of PA peptides to HLA-II molecules (r=-0.356, p<0.001); the stronger the overall binding affinity, the weaker the symptoms. Since the binding of a peptide to an HLA-II molecule is the first and necessary step in initiating the production of antibodies, the findings above support our hypothesis that the severity of GWI symptomatology is partly due to a lack of HLA-II protection.

CONCLUSIONS

Reduced HLA protection against the toxic anthrax vaccine may underlie GWI.

An Immunoinformatic Approach for Identifying and Designing Conserved Multi-Epitope Vaccines for Coronaviruses

BACKGROUND/OBJECTIVES

The COVID-19 pandemic caused by the novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has exposed the vulnerabilities and unpreparedness of the global healthcare system in dealing with emerging zoonoses. In the past two decades, coronaviruses (CoV) have been responsible for three major viral outbreaks, and the likelihood of future outbreaks caused by these viruses is high and nearly inevitable. Therefore, effective prophylactic universal vaccines targeting multiple circulating and emerging coronavirus strains are warranted.

METHODS

This study utilized an immunoinformatic approach to identify evolutionarily conserved CD4+ (HTL) and CD8+ (CTL) T cells, and B-cell epitopes in the coronaviral spike (S) glycoprotein.

RESULTS

A total of 132 epitopes were identified, with the majority of them found to be conserved across the bat CoVs, pangolin CoVs, endemic coronaviruses, SARS-CoV-2, and Middle East respiratory syndrome coronavirus (MERS-CoV). Their peptide sequences were then aligned and assembled to identify the overlapping regions. Eventually, two major peptide assemblies were derived based on their promising immune-stimulating properties.

CONCLUSIONS

In this light, they can serve as lead candidates for universal coronavirus vaccine development, particularly in the search for pan-coronavirus multi-epitope universal vaccines that can confer protection against current and novel coronaviruses.

In silico and immunoinformatics based multiepitope subunit vaccine design for protection against visceral leishmaniasis

Visceral leishmaniasis (VL) is a vector-borne neglected tropical protozoan disease with high fatality and no certified vaccine. Conventional vaccine preparation is challenging and tedious. Here in this work, we created a global multiepitope subunit vaccination against VL utilizing innovative immunoinformatics technique based on the extensively conserved epitopic regions of the PrimPol protein of Leishmania donovani consisting of four subunits which were analyzed and studied, out of which DNA primase large subunit and DNA polymerase α subunit B were evaluated as antigens by Vaxijen 2.0. The multiepitope vaccine design includes a single adjuvant β-defensins, eight CTL epitopes, eight HTL epitopes, seven linear BCL epitopes and one discontinuous BCL epitope to induce innate, cellular and humoral immune responses against VL. The Expasy ProtParam tool characterized the physiochemical parameters of the vaccine. At the same time, SOLpro evaluated our vaccine constructs to be soluble upon expression. We also modeled the stable tertiary structure of our vaccine construct through Robetta modeling for molecular docking studies with toll-like receptor proteins through HADDOCK 2.4. Simulations based on molecular dynamics revealed an intact vaccine and TLR8 complex, supporting our vaccine design's immunogenicity. Also, the immune simulation of our vaccine by the C-ImmSim server demonstrated the potency of the multiepitope vaccine construct to induce proper immune response for host defense. Codon optimization and in silico cloning of our vaccine further assured high expression. The outcomes of our study on multiepitope vaccine design significantly produced a potential candidate against VL and can potentially eradicate the disease in the future after clinical investigations.Communicated by Ramaswamy H. Sarma.

Designing a multi-epitope influenza vaccine: an immunoinformatics approach

Influenza continues to be one of the top public health problems since it creates annual epidemics and can start a worldwide pandemic. The virus's rapid evolution allows the virus to evade the host defense, and then seasonal vaccines need to be reformulated nearly annually. However, it takes almost half a year for the influenza vaccine to become accessible. This delay is especially concerning in the event of a pandemic breakout. By producing the vaccine through reverse vaccinology and phage display vaccines, this time can be reduced. In this study, epitopes of B lymphocytes, cytotoxic T lymphocytes, and helper T lymphocytes of HA, NA, NP, and M2 proteins from two strains of Influenza A were anticipated. We found two proper epitopes (ASFIYNGRL and LHLILWITDRLFFKC) in Influenza virus proteins for CTL and HTL cells, respectively. Optimal epitopes and linkers in silico were cloned into the N-terminal end of M13 protein III (pIII) to create a multi-epitope-pIII construct, i.e., phage display vaccine. Also, prediction of tertiary structure, molecular docking, molecular dynamics simulation, and immune simulation were performed and showed that the designed multi-epitope vaccine can bind to the receptors and stimulate the immune system response.

Design of an Epitope-Based Vaccine Against MERS-CoV

Background and Objectives: Middle East Respiratory Syndrome (MERS) is a viral respiratory illness caused by a coronavirus called Middle East respiratory syndrome. In the current study, immunoinformatics studies were applied to design an epitope-based vaccine construct against Middle East Respiratory Syndrome. Materials and Methods: In this study, epitopes base vaccine construct was designed against MERS using immunoinformatics approach. Results: In this approach, the targeted proteins were screened, and probable antigenic, non-allergenic, and good water-soluble epitopes were selected for vaccine construction. In vaccine construction, the selected epitopes were joined by GPGPG linkers, and a linear multi-epitope vaccine was constructed. The vaccine construct underwent a physiochemical property analysis. The 3D structure of the vaccine construct was predicted and subjected to refinement. After the refinement, the 3D model was subjected to a molecular docking analysis, TLRs (TLR-3 and TLR-9) were selected as receptors for vaccine construct, and the molecular docking analysis study determined that the vaccine construct has binding ability with the targeted receptor. Conclusions: The docking analysis also unveils that the vaccine construct can properly activate immune system against the target virus however experimental validation is needed to confirm the in silico findings further.

Design of an epitope-based peptide vaccine against Cryptococcus neoformans

Cryptococcus neoformans is the highest-ranked fungal pathogen in the Fungal Priority Pathogens List (FPPL) released by the World Health Organization (WHO). In this study, through in silico simulations, a multi-epitope vaccine against Cryptococcus neoformans was developed using the mannoprotein antigen (MP88) as a vaccine candidate. Following the retrieval of the MP88 protein sequences, these were used to predict antigenic B-cell and T-cell epitopes via the bepipred tool and the artificial neural network, respectively. Conserved B-cell epitopes AYSTPA, AYSTPAS, PASSNCK, and DSAYPP were identified as the most promising B-cell epitopes. While YMAADQFCL, VSYEEWMNY, and FQQRYTGTF were identified as the best candidates for CD8+ T-cell epitopes; and YARLLSLNA, ISYGTAMAV, and INQTSYARL were identified as the most promising CD4+ T-cell epitopes. The vaccine construct was modeled along with adjuvant and peptide linkers and the expasy protparam tool was used to predict the physiochemical properties. According to this, the construct vaccine was predicted to be antigenic, nontoxic, nonallergenic, soluble, stable, hydrophilic, and thermostable. Furthermore, the three-dimensional structure was also used in docking analyses with Toll-like receptor (TLR4). Finally, the cDNA of vaccine was successfully cloned into the E. coli pET-28a (+) expression vector. The results presented here could contribute towards the design of an effective vaccine against Cryptococcus neoformans.

In silico design of a novel multi-epitope vaccine against HCV infection through immunoinformatics approaches

Infection with the hepatitis C virus (HCV) is one of the causes of liver cancer, which is the world's sixth most prevalent and third most lethal cancer. The current treatments do not prevent reinfection; because they are expensive, their usage is limited to developed nations. Therefore, a prophylactic vaccine is essential to control this virus. Hence, in this study, an immunoinformatics method was applied to design a multi-epitope vaccine against HCV. The best B- and T-cell epitopes from conserved regions of the E2 protein of seven HCV genotypes were joined with the appropriate linkers to design a multi-epitope vaccine. In addition, cholera enterotoxin subunit B (CtxB) was included as an adjuvant in the vaccine construct. This study is the first to present this epitopes-adjuvant combination. The vaccine had acceptable physicochemical characteristics. The vaccine's 3D structure was predicted and validated. The vaccine's binding stability with Toll-like receptor 2 (TLR2) and TLR4 was confirmed using molecular docking and molecular dynamics (MD) simulation. The immune simulation revealed the vaccine's efficacy by increasing the population of B and T cells in response to vaccination. In silico expression in Escherichia coli (E. coli) was also successful.

Lactobacilli-derived adjuvants combined with immunoinformatics-driven multi-epitope antigens based approach protects against Clostridium perfringens in a mouse model

Clostridium perfringens is ubiquitously distributed and capable of secreting toxins, posing a significant threat to animal health. Infections caused by Clostridium perfringens, such as Necrotic Enteritis (NE), result in substantial economic losses to the livestock industry annually. However, there is no effective commercial vaccine available. Hence, we set out to propose an effective approach for multi-epitope subunit vaccine construction utilizing biomolecules. We utilized immunoinformatics to design a novel multi-epitope antigen against C. perfringens (CPMEA). Furthermore, we innovated novel bacterium-like particles (BLPs) through thermal acid treatment of various Lactobacillus strains and selected BLP23017 among them. Then, we detailed the structure of CPMEA and BLPs and utilized them to prepare a multi-epitope vaccine. Here, we showed that our vaccine provided full protection against C. perfringens infection after a single dose in a mouse model. Additionally, BLP23017 notably augmented the secretion of secretory immunoglobulin A (sIgA) and enhanced antibody production. We conclude that our vaccine possess safety and high efficacy, making it an excellent candidate for preventing C. perfringens infection. Moreover, we demonstrate our approach to vaccine construction and the preparation of BLP23017 with distinct advantages may contribute to the prevention of a wider array of diseases and the novel vaccine development.

Designing a conjugate vaccine targeting Klebsiella pneumoniae ST258 and ST11

Klebsiella pneumoniae (K. pneumoniae) is a common bacterium that can cause iatrogenic infection. Recently, the rise of antibiotic resistance among K. pneumoniae strains is one key factor associated with antibiotic treatment failure. Hencefore, there is an urgent need for effective K. pneumoniae vaccines. This study aimed to design a multi-epitope vaccine (MEV) candidate against K. pneumonia by utilizing an immunoinformatics method. In this study, we obtained 15 cytotoxic T lymphocyte epitopes, 10 helper T lymphocyte epitopes, 6 linear B-cell epitopes, and 2 conformational B-cell epitopes for further research. Then, we designed a multi-epitope vaccine composed of a total of 743 amino acids, containing the epitopes linked by GPGPG flexible links and an EAAAK linker to the Cholera Toxin Subunit B coadjuvant. The observed properties of the MEV, including non-allergenicity, high antigenicity, and hydrophilicity, are noteworthy. The improvements in the tertiary structure through structural refinement and disulfide bonding, coupled with promising molecular interactions revealed by molecular dynamics simulations with TLR4, position the MEV as a strong candidate for further investigation against K. pneumoniae.

Toward a SARS-CoV-2 VLP Vaccine: HBc/G as a Carrier for SARS-CoV-2 Spike RBM and Nucleocapsid Protein-Derived Peptides

Virus-like particles (VLPs) offer an attractive possibility for the development of vaccines. Recombinant core antigen (HBc) of Hepatitis B virus (HBV) was expressed in different systems, and the E. coli expression system was shown to be effective for the production of HBc VLPs. Here, we used HBc of the HBV genotype G (HBc/G) as a technologically promising VLP carrier for the presentation of spike RBM and nucleocapsid protein-derived peptides of the SARS-CoV-2 Delta variant for subsequent immunological evaluations of obtained fusion proteins. The major immunodominant region (MIR) of the HBc/G protein was modified through the insertion of a receptor binding motif (RBM) from the S protein or B-cell epitope-containing peptide from the N protein. The C-terminus of the two truncated HBc/G proteins was used for the insertion of a group of five cytotoxic T lymphocyte (CTL) epitopes from the N protein. After expression in E. coli, the MIR-derived proteins were found to be insoluble and were recovered through step-wise solubilization with urea, followed by refolding. Despite the lack of correct VLPs, the chimeric proteins induced high levels of antibodies in BALB/c mice. These antibodies specifically recognized either eukaryotically expressed hRBD or bacterially expressed N protein (2-220) of SARS-CoV-2. CTL-epitope-containing proteins were purified as VLPs. The production of cytokines was analyzed through flow cytometry after stimulation of T-cells with target CTL peptides. Only a protein with a deleted polyarginine (PA) domain was able to induce the specific activation of T-cells. At the same time, the T-cell response against the carrier HBc/G protein was detected for both proteins. The neutralization of SARS-CoV-2 pseudotyped murine retrovirus with anti-HBc/G-RBM sera was found to be low.

A novel therapeutic multiepitope vaccine based on oncoprotein E6 and E7 of HPV 16 and 18: An in silico approach

Introduction

The current vaccine strategies to prevent cervical cancer are effective only for individuals unexposed to HPV, lacking therapeutic effects against pre-existing infections. Multiepitope vaccines, using an immunoinformatic approach, are promising against tumors and viral infections because of their high specificity, safety, and stability, as well as the cheap cost of development.

Methods

This study employed computer-based immunoinformatic analysis to design therapeutic multiepitope vaccines against cervical cancer using oncoproteins E6 and E7 of HPV 16 and 18. Several immunoinformatic tools were applied to analyze potential vaccine constructs capable of stimulating immune responses against both oncoproteins.

Results

The constructed vaccine exhibited antigenic, immunogenic, nonallergenic, nontoxic, stable, and soluble characteristics. Additionally, it effectively interacted with TLR2 and TLR4, showing high binding capacity. Computational analysis indicated the vaccine could induce immune responses through the elevation of cytokine levels after the third injection, antibody production, activation of memory B and T cells, and promotion of increased dendritic cell counts.

Conclusion

The novel multiepitope vaccine based on E6 and E7 presented as a promising candidate for combating HPV infections and associated cervical cancer. Further in vitro and in vivo studies were essential to validate the efficacy and safety of the vaccine.

Immunoinformatics-guided approach for designing a pan-proteome multi-epitope subunit vaccine against African swine fever virus

Despite being identified over a hundred years ago, there is still no commercially available vaccine for the highly contagious and deadly African swine fever virus (ASFV). This study used immunoinformatics for the rapid and inexpensive designing of a safe and effective multi-epitope subunit vaccine for ASFV. A total of 18,858 proteins from 100 well-annotated ASFV proteomes were screened using various computational tools to identify potential epitopes, or peptides capable of triggering an immune response in swine. Proteins from genotypes I and II were prioritized for their involvement in the recent global ASFV outbreaks. The screened epitopes exhibited promising qualities that positioned them as effective components of the ASFV vaccine. They demonstrated antigenicity, immunogenicity, and cytokine-inducing properties indicating their ability to induce potent immune responses. They have strong binding affinities to multiple swine allele receptors suggesting a high likelihood of yielding more amplified responses. Moreover, they were non-allergenic and non-toxic, a crucial prerequisite for ensuring safety and minimizing any potential adverse effects when the vaccine is processed within the host. Integrated with an immunogenic 50S ribosomal protein adjuvant and linkers, the epitopes formed a 364-amino acid multi-epitope subunit vaccine. The ASFV vaccine construct exhibited notable immunogenicity in immune simulation and molecular docking analyses, and stable profiles in secondary and tertiary structure assessments. Moreover, this study designed an optimized codon for efficient translation of the ASFV vaccine construct into the Escherichia coli K-12 expression system using the pET28a(+) vector. Overall, both sequence and structural evaluations suggested the potential of the ASFV vaccine construct as a candidate for controlling and eradicating outbreaks caused by the pathogen.

Computational design and evaluation of mRNA- and protein-based conjugate vaccines for influenza A and SARS-CoV-2 viruses

BACKGROUND

Israel confirmed the first case of "flurona"-a co-infection of seasonal flu (IAV) and SARS-CoV-2 in an unvaccinated pregnant woman. This twindemic has been confirmed in multiple countries and underscores the importance of managing respiratory viral illnesses.

RESULTS

The novel conjugate vaccine was designed by joining four hemagglutinin, three neuraminidase, and four S protein of B-cell epitopes, two hemagglutinin, three neuraminidase, and four S proteins of MHC-I epitopes, and three hemagglutinin, nine neuraminidase, and five S proteins of MHC-II epitopes with linkers and adjuvants. The constructed conjugate vaccine was found stable, non-toxic, non-allergic, and antigenic with 0.6466 scores. The vaccine contained 14.87% alpha helix, 29.85% extended strand, 9.64% beta-turn, and 45.64% random coil, which was modeled to a 3D structure with 94.7% residues in the most favored region of the Ramachandran plot and Z-score of -3.33. The molecular docking of the vaccine with TLR3 represented -1513.9 kcal/mol of binding energy with 39 hydrogen bonds and 514 non-bonded contacts, and 1.582925e-07 of eigenvalue complex. Immune stimulation prediction showed the conjugate vaccine could activate T and B lymphocytes to produce high levels of Th1 cytokines and antibodies.

CONCLUSION

The in silico-designed vaccine against IAV and SARS-CoV-2 showed good population coverage and immune response with predicted T- and B-cell epitopes, favorable molecular docking, Ramachandran plot results, and good protein expression. It fulfilled safety criteria, indicating potential for preclinical studies and experimental clinical trials.

Identification and In Silico Characterization of a Conserved Peptide on Influenza Hemagglutinin Protein: A New Potential Antigen for Universal Influenza Vaccine Development

Antigenic changes in surface proteins of the influenza virus may cause the emergence of new variants that necessitate the reformulation of influenza vaccines every year. Universal influenza vaccine that relies on conserved regions can potentially be effective against all strains regardless of any antigenic changes and as a result, it can bring enormous public health impact and economic benefit worldwide. Here, a conserved peptide (HA288-107) on the stalk domain of hemagglutinin glycoprotein is identified among highly pathogenic influenza viruses. Five top-ranked B-cell and twelve T-cell epitopes were recognized by epitope mapping approaches and the corresponding Human Leukocyte Antigen alleles to T-cell epitopes showed high population coverage (>99%) worldwide. Moreover, molecular docking analysis indicated that VLMENERTL and WTYNAELLV epitopes have high binding affinity to the antigen-binding groove of the HLA-A*02:01 and HLA-A*68:02 molecules, respectively. Theoretical physicochemical properties of the peptide were assessed to ensure its thermostability and hydrophilicity. The results suggest that the HA288-107 peptide can be a promising antigen for universal influenza vaccine design. However, in vitro and in vivo analyses are needed to support and evaluate the effectiveness of the peptide as an immunogen for vaccine development.

Computational formulation of a multiepitope vaccine unveils an exceptional prophylactic candidate against Merkel cell polyomavirus

Merkel cell carcinoma (MCC) is a rare neuroendocrine skin malignancy caused by human Merkel cell polyomavirus (MCV), leading to the most aggressive skin cancer in humans. MCV has been identified in approximately 43%-100% of MCC cases, contributing to the highly aggressive nature of primary cutaneous carcinoma and leading to a notable mortality rate. Currently, no existing vaccines or drug candidates have shown efficacy in addressing the ailment caused by this specific pathogen. Therefore, this study aimed to design a novel multiepitope vaccine candidate against the virus using integrated immunoinformatics and vaccinomics approaches. Initially, the highest antigenic, immunogenic, and non-allergenic epitopes of cytotoxic T lymphocytes, helper T lymphocytes, and linear B lymphocytes corresponding to the virus whole protein sequences were identified and retrieved for vaccine construction. Subsequently, the selected epitopes were linked with appropriate linkers and added an adjuvant in front of the construct to enhance the immunogenicity of the vaccine candidates. Additionally, molecular docking and dynamics simulations identified strong and stable binding interactions between vaccine candidates and human Toll-like receptor 4. Furthermore, computer-aided immune simulation found the real-life-like immune response of vaccine candidates upon administration to the human body. Finally, codon optimization was conducted on the vaccine candidates to facilitate the in silico cloning of the vaccine into the pET28+(a) cloning vector. In conclusion, the vaccine candidate developed in this study is anticipated to augment the immune response in humans and effectively combat the virus. Nevertheless, it is imperative to conduct in vitro and in vivo assays to evaluate the efficacy of these vaccine candidates thoroughly. These evaluations will provide critical insights into the vaccine's effectiveness and potential for further development.

In silico design and immunoinformatics analysis of a universal multi-epitope vaccine against monkeypox virus

Monkeypox virus (MPXV) outbreaks have been reported in various countries worldwide; however, there is no specific vaccine against MPXV. In this study, therefore, we employed computational approaches to design a multi-epitope vaccine against MPXV. Initially, cytotoxic T lymphocyte (CTL), helper T lymphocyte (HTL), linear B lymphocytes (LBL) epitopes were predicted from the cell surface-binding protein and envelope protein A28 homolog, both of which play essential roles in MPXV pathogenesis. All of the predicted epitopes were evaluated using key parameters. A total of 7 CTL, 4 HTL, and 5 LBL epitopes were chosen and combined with appropriate linkers and adjuvant to construct a multi-epitope vaccine. The CTL and HTL epitopes of the vaccine construct cover 95.57% of the worldwide population. The designed vaccine construct was found to be highly antigenic, non-allergenic, soluble, and to have acceptable physicochemical properties. The 3D structure of the vaccine and its potential interaction with Toll-Like receptor-4 (TLR4) were predicted. Molecular dynamics (MD) simulation confirmed the vaccine's high stability in complex with TLR4. Finally, codon adaptation and in silico cloning confirmed the high expression rate of the vaccine constructs in strain K12 of Escherichia coli (E. coli). These findings are very encouraging; however, in vitro and animal studies are needed to ensure the potency and safety of this vaccine candidate.

In Silico Studies to Support Vaccine Development

The progress that has been made in computer science positioned in silico studies as an important and well-recognized methodology in the drug discovery and development process. It has numerous advantages in terms of costs and also plays a huge impact on the way the research is conducted since it can limit the use of animal models leading to more sustainable research. Currently, human trials are already being partly replaced by in silico trials. EMA and FDA are both endorsing these studies and have been providing webinars and guidance to support them. For instance, PBPK modeling studies are being used to gather data on drug interactions with other drugs and are also being used to support clinical and regulatory requirements for the pediatric population, pregnant women, and personalized medicine. This trend evokes the need to understand the role of in silico studies in vaccines, considering the importance that these products achieved during the pandemic and their promising hope in oncology. Vaccines are safer than other current oncology treatments. There is a huge variety of strategies for developing a cancer vaccine, and some of the points that should be considered when designing the vaccine technology are the following: delivery platforms (peptides, lipid-based carriers, polymers, dendritic cells, viral vectors, etc.), adjuvants (to boost and promote inflammation at the delivery site, facilitating immune cell recruitment and activation), choice of the targeted antigen, the timing of vaccination, the manipulation of the tumor environment, and the combination with other treatments that might cause additive or even synergistic anti-tumor effects. These and many other points should be put together to outline the best vaccine design. The aim of this article is to perform a review and comprehensive analysis of the role of in silico studies to support the development of and design of vaccines in the field of oncology and infectious diseases. The authors intend to perform a literature review of all the studies that have been conducted so far in preparing in silico models and methods to support the development of vaccines. From this point, it was possible to conclude that there are few in silico studies on vaccines. Despite this, an overview of how the existing work could support the design of vaccines is described.

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.

In silico clinical trials for relapsing-remitting multiple sclerosis with MS TreatSim

BACKGROUND

The last few decades have seen the approval of many new treatment options for Relapsing-Remitting Multiple Sclerosis (RRMS), as well as advances in diagnostic methodology and criteria. These developments have greatly improved the available treatment options for today's Relapsing-Remitting Multiple Sclerosis patients. This increased availability of disease modifying treatments, however, has implications for clinical trial design in this therapeutic area. The availability of better diagnostics and more treatment options have not only contributed to progressively decreasing relapse rates in clinical trial populations but have also resulted in the evolution of control arms, as it is often no longer sufficient to show improvement from placebo. As a result, not only have clinical trials become longer and more expensive but comparing the results to those of "historical" trials has also become more difficult.

METHODS

In order to aid design of clinical trials in RRMS, we have developed a simulator called MS TreatSim which can simulate the response of customizable, heterogeneous groups of patients to four common Relapsing-Remitting Multiple Sclerosis treatment options. MS TreatSim combines a mechanistic, agent-based model of the immune-based etiology of RRMS with a simulation framework for the generation and virtual trial simulation of populations of digital patients.

RESULTS

In this study, the product was first applied to generate diverse populations of digital patients. Then we applied it to reproduce a phase III trial of natalizumab as published 15 years ago as a use case. Within the limitations of synthetic data availability, the results showed the potential of applying MS TreatSim to recreate the relapse rates of this historical trial of natalizumab.

CONCLUSIONS

MS TreatSim's synergistic combination of a mechanistic model with a clinical trial simulation framework is a tool that may advance model-based clinical trial design.