Identification of Conserved Peptides Comprising Multiple T Cell Epitopes of Matrix 1 Protein in H1N1 Influenza Virus

Computational identification of a multi-peptide vaccine candidate in E2 glycoprotein against diverse Hepatitis C virus genotypes

Hepatitis C Virus (HCV) is estimated to affect nearly 180 million people worldwide, culminating in ∼0.7 million yearly casualties. However, a safe vaccine against HCV is not yet available. This study endeavored to identify a multi-genotypic, multi-epitopic, safe, and globally competent HCV vaccine candidate. We employed a consensus epitope prediction strategy to identify multi-epitopic peptides in all known envelope glycoprotein (E2) sequences, belonging to diverse HCV genotypes. The obtained peptides were screened for toxicity, allergenicity, autoimmunity and antigenicity, resulting in two favorable peptides viz., P2 (VYCFTPSPVVVG) and P3 (YRLWHYPCTV). Evolutionary conservation analysis indicated that P2 and P3 are highly conserved, supporting their use as part of a designed multi-genotypic vaccine. Population coverage analysis revealed that P2 and P3 are likely to be presented by >89% Human Leukocyte Antigen (HLA) molecules from six geographical regions. Indeed, molecular docking predicted the physical binding of P2 and P3 to various representative HLAs. We designed a vaccine construct using these peptides and assessed its binding to toll-like receptor 4 (TLR-4) by molecular docking and simulation. Subsequent analysis by energy-based and machine learning tools predicted high binding affinity and pinpointed the key binding residues (i.e. hotspots) in P2 and P3. Also, a favorable immunogenic profile of the construct was predicted by immune simulations. We encourage the scientific community to validate our vaccine construct in vitro and in vivo.Communicated by Ramaswamy H. Sarma.

Designing ferritin nanocage based vaccine candidates for SARS-CoV-2 by in silico engineering of its HLA I and HLA II epitope peptides

New variants of SARS-CoV-2 are continuously being reported. To curtail the spread of this virus, it is essential to find an efficient and potent vaccine. Here, we report in silico designing of a protein (ferritin: FR) nanocage fused with multiple epitopes identified using the immuno-informatics approach and high-throughput screening. Employing computational approaches, we identified potential epitopes from membrane, nucleocapsid, and envelope proteins of SARS-CoV-2 and docked them on the selected human leukocyte antigen Class I and II receptors, then the stability of the complexes was assessed using molecular dynamics simulation studies. We have engineered chimeric ferritin nanocage, chm66FR, with the nested peptide of 10 epitopes by replacing the loop region at the 66^th position of the nanocage, then its stability was confirmed using metadynamics simulation. Further, we used the homotrimeric '6-helical bundle' of the spike protein to engineer the chimeric 6HB (chm6HB). The chm6HB is, engineered with three epitope peptides, mounted on the N-terminal trimeric interface of the chm66FR to generate the chm6HB-chm66FR, which contains 15 epitope peptides. Chimeric FR nanocages and the chm6HB could be potential vaccine candidates against strains of SARS-CoV-2. These multivalent and multiple epitopes protein nanocages and scaffolds could mount both humoral and T-cell mediated immune responses against SARS-CoV-2.Communicated by Ramaswamy H. Sarma.

In silico epitope-based vaccine design against influenza a neuraminidase protein: Computational analysis established on B- and T-cell epitope predictions

Objective

Influenza A virus belongs to the most studied virus and its mutant initiates epidemic and pandemics outbreaks. Inoculation is the significant foundation to diminish the risk of infection. To prevent an incidence of influenza from the transmission, various practical approaches require more advancement and progress. More efforts and research must take in front to enhance vaccine efficacy.

Methods

The present research emphasizes the development and expansion of a universal vaccine for the influenza virus. Research focuses on vaccine design with high efficacy. In this study, numerous computational approaches were used, covering a wide range of elements and ideas in bioinformatics methodology. Various B and T-cell epitopic peptides derived from the Neuraminidase protein N1 are recognized by these approaches. With the implementation of numerous obtained databases and bioinformatics tools, the different immune framework methods of the conserved sequences of N1 neuraminidase were analyzed. NCBI databases were employed to retrieve amino acid sequences. The antigenic nature of the neuraminidase sequence was achieved by the VaxiJen server and Kolaskar and Tongaonkar method. After screening of various B and T cell epitopes, one efficient peptide each from B cell epitope and T cell epitopes was assessed for their antigenic determinant vaccine efficacy. Identical two B cell epitopes were recognized from the N1 protein when analyzed using B-cell epitope prediction servers. The detailed examination of amino acid sequences for interpretation of B and T cell epitopes was achieved with the help of the ABCPred and Immune Epitope Database.

Results

Computational immunology via immunoinformatic study exhibited RPNDKTG as having its high conservancy efficiency and demonstrated as a good antigenic, accessible surface hydrophilic B-cell epitope. Among T cell epitope analysis, YVNISNTNF was selected for being a conserved epitope. T cell epitope was also analyzed for its allergenicity and cytotoxicity evaluation. YVNISNTNF epitope was found to be a non-allergen and not toxic for cells as well. This T-cell epitope with maximum world populace coverages was scrutinized for its association with the HLA-DRB1*0401 molecule. Results from docking simulation analyses showed YVNISNTNF having lower binding energy, the radius of gyration (Rg), RMSD values, and RMSE values which make the protein structure more stable and increase its ability to become an epitopic peptide for influenza virus vaccination.

Conclusions

We propose that this epitope analysis may be successfully used as a measurement tool for the robustness of an antigen-antibody reaction between mutant strains in the annual design of the influenza vaccine.

Computational design of immunogenic peptide constructs comprising multiple HLA restricted Dengue virus envelope epitopes

Dengue virus (DENV) is endemic in 100 countries with ability to impact nearly 50% of world population. DENV envelope (E) protein is responsible for viral attachment to host cells and has been target of various countermeasure development efforts. The current study focuses on a consensus computational approach to identify cross-reactive, immunogenic DENV-2 E peptides displaying promiscuity with a wide array of HLA molecules. Four conserved peptides (FP-1, FP-2, FP-3 and FP-4) containing multiple CD8⁺ and CD4⁺ T cell epitopes were identified by employment of various immunoinformatics tools. FP-1, FP-2, FP-3 and FP-4 were estimated to bind with 227, 1787, 1008 and 834 HLA alleles respectively. RMSD values obtained by Molecular docking (CABS-Dock) with 20 HLA alleles (10 each of HLA class I and II) resulted into comparable RMSD values of identified epitopes with native peptides which represents the natural presentation of epitopes to HLA molecules. These peptides were also found to be part of previous experimentally validated immunogenic peptides. Further, a dengue immunogenic peptide construct was generated by linking the four peptides, an adjuvant and a 6x histidine tag. The construct showed strong binding and stability with Toll-like receptor (TLR4). Collectively, these results provide strong evidence in the support of the immunogenic potential of the dengue immunogenic peptide construct. This article is protected by copyright. All rights reserved.

In silico design of a multi-epitope peptide construct as a potential vaccine candidate for Influenza A based on neuraminidase protein

Designing an effective vaccine against different subtypes of Influenza A virus is a critical issue in the field of medical biotechnology. At the current study, a novel potential multi-epitope vaccine candidate based on the neuraminidase proteins for seven subtypes of Influenza virus was designed, using the in silico approach. Potential linear B-cell and T-cell binding epitopes from each neuraminidase protein (N1, N2, N3, N4, N6, N7, N8) were predicted by in silico tools of epitope prediction. The selected epitopes were joined by three different linkers, and physicochemical properties, toxicity, and allergenecity were investigated. The final multi-epitope construct was modeled using GalaxyWEB server, and the molecular interactions with immune receptors were investigated and the immune response simulation assay was performed. A multi-epitope construct with GPGPGPG linker with the lowest allergenicity and highest stability was selected. The molecular docking assay indicated the interactions with immune system receptors, including HLA1, HLA2, and TLR-3. Immune response simulation detected both humoral and cellular response, including the elevated count of B-cells, T-cell, and Nk-cells.

Identification of a universal antigen epitope of influenza A virus using peptide microarray

Background

Hemagglutinin is a major surface protein in influenza A virus (IAV), and HA2 is relative conserved among different IAVs. It will be meaningful to identify broad-spectrum epitopes based on the HA2 protein.

Results

Overlapping peptides of the HA2 protein of the H5N1 IAV A/Mallard/Huadong/S/2005 were synthesized and loaded on modified silica gel film to form a microarray, and antisera against different subtypes of IAVs were used to screen universal epitopes. The selected epitope was further confirmed by western blotting using anti-peptide immune serum and viruses rescued with amino acid substitution. The results showed that 485-FYHKCDNECME-495 of the H5 14th peptide in HA2 had broad-spectrum binding activity with antisera against H1, H3, H4, H5, H6, H7, H8, H9, and H10 subtype IAV. Substitution of amino acids (K or D) in rescued viruses resulted in decreased serum binding, indicating that they were critical residues for serum binding activity. In Immune Epitope Database, some epitopes containing 14–4 peptide were confirmed as MHC-II-restricted CD4 T cell epitope and had effects on releasing IL-2 or IFN.

Conclusion

The identified epitope should be a novel universal target for detection and vaccine design and its ability to generate immune protection needs further exploration.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12917-020-02725-5.

An Immunoinformatics Approach in Design of Synthetic Peptide Vaccine Against Influenza Virus

Peptide-based vaccines are an appealing strategy which involves usage of short synthetic peptides to engineer a highly targeted immune response. These short synthetic peptides contain potential T- and B-cell epitopes. Experimental approaches in identifying these epitopes are time-consuming and expensive; hence immunoinformatics approach came into picture. Immuninformatics approach involves epitope prediction tools, molecular docking, and population coverage analysis in design of desired immunogenic peptides. In order to overcome the antigenic variation of viruses, conserved regions are targeted to find the potential epitopes. The present chapter demonstrates the use of immunoinformatics approach to select potential peptide containing multiple T- (CD8+ and CD4+) and B-cell epitopes from Avian H3N2 M1 Protein. Further, molecular docking (to analyse HLA-peptide interaction) and population coverage analysis have been used to verify the potential of peptide to be presented by polymorphic HLA molecules. In silico approach of epitope prediction has proven to be successful methodology in screening the putative epitopes among numerous possible vaccine targets in a given protein.

In silico rational design of a novel tetra-epitope tetanus vaccine with complete population coverage using developed immunoinformatics and surface epitope mapping approaches

Presentation of many unwanted epitopes within tetanus toxoid vaccine to lymphocyte clones may lead to production of many unwanted antibodies. Moreover an ideal vaccine must cover all individuals in a population that is dependent to the kinds of human leukocyte antigen alleles. Concerning these issues, our study was aimed to in silico design of a multi-epitope tetanus vaccine (METV) in order to improve population coverage and protectivity of tetanus vaccine as well as reduction of complications. Concerning these issues, a novel rational filtration was implemented to design a novel METV using immunoinformatics and surface epitope mapping approaches. Prediction of epitopes for tetanus toxin was performed in the candidate country in which the frequency had been gathered from almost all geographical distributions. The most strong binder epitopes for major histocompatibility complex class II were selected and among them the surface epitopes of native toxin were selected. The population coverage of the selected epitopes was estimated. The final candidate epitopes had highly population coverage. Molecular docking was performed to prediction of binding affinity of our candidate epitopes to the HLA-DRB1 alleles. At first, 680 strong binder epitopes were predicted. Among them 11 epitopes were selected. Finally, 4 epitopes had the most population coverage and suggested as a tetra-epitope tetanus vaccine. 99.41% of inessential strong binders were deleted using our tree steps filtration. HLA-DP had the most roles in epitope presentation. Molecular docking analysis proved the strong binding affinity of candidate epitopes to the HLA-DRB1 alleles. In conclusion, we theoretically reduced 99.41% of unwanted antibodies using our novel filtration strategies. Our tetra-epitope tetanus vaccine showed 100% population coverage in the candidate country. Furthermore, it was demonstrated that HLA-DP and HLA-DQ had more potential in epitope presentation in comparison to HLA-DRB1.

Reverse vaccinology approach to design a novel multi-epitope subunit vaccine against avian influenza A (H7N9) virus

H7N9, a novel strain of avian origin influenza was the first recorded incidence where a human was transited by a N9 type influenza virus. Effective vaccination against influenza A (H7N9) is a major concern, since it has emerged as a life threatening viral pathogen. Here, an in silico reverse vaccinology strategy was adopted to design a unique chimeric subunit vaccine against avian influenza A (H7N9). Induction of humoral and cell-mediated immunity is the prime concerned characteristics for a peptide vaccine candidate, hence both T cell and B cell immunity of viral proteins were screened. Antigenicity testing, transmembrane topology screening, allergenicity and toxicity assessment, population coverage analysis and molecular docking approach were adopted to generate the most antigenic epitopes of avian influenza A (H7N9) proteome. Further, a novel subunit vaccine was designed by the combination of highly immunogenic epitopes along with suitable adjuvant and linkers. Physicochemical properties and secondary structure of the designed vaccine were assessed to ensure its thermostability, h ydrophilicity, theoretical PI and structural behavior. Homology modeling, refinement and validation of the designed vaccine allowed to construct a three dimensional structure of the predicted vaccine, further employed to molecular docking analysis with different MHC molecules and human immune TLR8 receptor present on lymphocyte cells. Moreover, disulfide engineering was employed to lessen the high mobility region of the designed vaccine in order to extend its stability. Furthermore, we investigated the molecular dynamic simulation of the modeled subunit vaccine and TLR8 complexed molecule to strengthen our prediction. Finally, the suggested vaccine was reverse transcribed and adapted for E. coli strain K12 prior to insertion within pET28a(+) vector for checking translational potency and microbial expression.

Highly conserved hemagglutinin peptides of H1N1 influenza virus elicit immune response

In the current study, two highly conserved (> 90%) H1N1 hemagglutinin peptides STDTVDTVLEKNVTVTHSVNL (H1) and KVNSVIEKMNTQFTAVGKEF (H2) containing multiple T-cell epitopes have been assessed for their immunogenic potential in vitro, subjecting peripheral blood mononuclear cells from healthy volunteers to repetitive stimulation of chemically synthesised H1 and H2 peptides, and measuring their interferon (IFN)-γ level (ELISA) and proliferation (MTT assay). Further, these peptides were analysed for their binding affinity with 18 different human leukocyte antigen (HLA) class I and II by means of molecular docking. All seven samples tested for H1- and H2-induced IFN-γ secretion were found to have enhanced IFN-γ production. Six (H1) and five (H2) samples have shown proliferative response compared to unstimulated cells. Peptide-induced IFN-γ secretion and proliferation in healthy samples represent the immunogenic potential of these peptides. Further, molecular docking results reveal that the peptides have comparable binding energy to that of native bound peptide for both HLA classes which indicates that these peptides have the capability to be presented by different HLA molecules required for T-cell response. Hence, these conserved immunogenic hemagglutinin peptides are potential candidates for influenza vaccine development.

Overlapping CD8+ and CD4+ T-cell epitopes identification for the progression of epitope-based peptide vaccine from nucleocapsid and glycoprotein of emerging Rift Valley fever virus using immunoinformatics approach

Rift Valley fever virus (RVFV) is an emergent arthropod-borne zoonotic infectious viral pathogen which causes fatal diseases in the humans and ruminants. Currently, no effective and licensed vaccine is available for the prevention of RVFV infection in endemic as well as in non-endemic regions. So, an immunoinformatics-driven genome-wide screening approach was performed for the identification of overlapping CD8+ and CD4+ T-cell epitopes and also linear B-cell epitopes from the conserved sequences of the nucleocapsid (N) and glycoprotein (G) of RVFV. We identified overlapping 99.39% conserved 1 CD8+ T-cell epitope (MMHPSFAGM) from N protein and 100% conserved 7 epitopes (AVFALAPVV, LAVFALAPV, FALAPVVFA, VFALAPVVF, IAMTVLPAL, FFDWFSGLM, and FLLIYLGRT) from G protein and also identified IL-4 and IFN-γ induced (99.39% conserved) 1 N protein CD4+ T-cell epitope (HMMHPSFAGMVDPSL) and 100% conserved 5 G protein CD4+ T-cell epitopes (LPALAVFALAPVVFA, PALAVFALAPVVFAE, GIAMTVLPALAVFAL, GSWNFFDWFSGLMSW, and FFLLIYLGRTGLSKM). The overlapping CD8+ and CD4+ T-cell epitopes were bound with most conserved HLA-C*12:03 and HLA-DRB1*01:01, respectively with the high binding affinity (kcal/mol). The combined population coverage analysis revealed that the allele frequencies of these epitopes are high in endemic and non-endemic regions. Besides, we found 100% conserved and non-allergenic 2 decamer B-cell epitopes, GVCEVGVQAL and RVFNCIDWVH of G protein had the sequence similarity with the nonamer CD8+ T-cell epitopes, VCEVGVQAL and RVFNCIDWV, respectively. Consequently, these epitopes may be used for the development of epitope-based peptide vaccine against emerging RVFV. However, in vivo and in vitro experiments are required for their efficient use as a vaccine.

Immune responses to highly conserved influenza A virus matrix 1 peptides

Influenza vaccine development is considered to be complicated and challenging. Constantly evolving influenza viruses require continuous global monitoring and reformulation of the vaccine strains. Peptides that are conserved among different strains and subtypes of influenza A virus are strongly considered to be attractive targets for development of cross protective influenza vaccines that stimulate cellular responses. In this study, three highly conserved (>90%) matrix 1 peptides that contain multiple T cell epitopes, ILGFVFTLTVPSERGLQRRRF (P_M 1), LIRHENRMVLASTTAKA (P_M 2) and LQAYQKRMGVQMQR (P_M 3), were assessed for their immunogenic potential in vitro by subjecting peripheral blood mononuclear cells from healthy volunteers to repetitive stimulation with these chemically synthesised peptides and measuring their IFN-γ concentrations, proliferation by ELISA, and 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, respectively. Seven samples were screened for immunogenicity of P_M 1 and P_M 2, and six for that of P_M 3. All six samples had positive responses (IFN-γ secretion) to P_M 3 stimulation, as did five and three for P_M 2 and P_M 1 respectively. In contrast, seven (P_M 1 and P_M 2) and four (P_M 3) samples showed proliferative response as compared with unstimulated cells. The encouraging immunogenic response generated by these highly conserved matrix 1 peptides indicates they are prospective candidates for development of broadly reactive influenza vaccines.

Identification of putative unique immunogenic ZIKV and DENV1-4 peptides for diagnostic cellular based tests

Since the re-emergence of Zika virus in 2014 and subsequent association with microcephaly, much work has focused on the development of a vaccine to halt its spread throughout the world. The mosquito vector that transmits this virus is widespread and responsible for the spread of other arboviridae including Dengue. Current diagnostic methods rely on serologic testing that are complicated by cross reactivity and therefore unable to distinguish Zika from Dengue infection in the absence of virus isolation. We performed an in silico analysis to identify potential epitopes that may stimulate a unique T-lymphocyte response to distinguish prior infection with Zika or Dengue. From this analysis, we not only identified epitopes unique to Zika and Dengue, but also identified epitopes unique to each Dengue serotype. These peptides contribute to a pool of peptides identified for vaccine development that can be tested in vitro to confirm immunogenicity, absence of homology and global population coverage. The current lack of accurate diagnostic testing hampers our ability to understand the scope of the epidemic, implications for vaccine implementation and complications related to monoinfection and co-infection with these two closely related viruses.

Metadherin peptides containing CD4(+) and CD8(+) T cell epitopes as a therapeutic vaccine candidate against cancer

The concept of peptide-based vaccines against cancer has made noteworthy progress. Metadherin (MTDH) overexpression and its role in the development of diverse cancers make it an attractive target for cancer immunotherapy. In the current study, six different T cell epitope prediction tools were run to identify MTDH peptides with multiple immunogenic regions. Further, molecular docking was performed to assess HLA-peptide binding interactions. Nine and eleven peptides fragments containing multiple CD8 (+) and CD4 (+) T-cell epitopes, ranging from 9 to 20 amino acids, respectively, were obtained using a consensus immunoinformatics approach. The three peptides that were finally identified as having overlapping CD4 (+) and CD8 (+) T- cell epitopes are ARLREMLSVGLGFLRTELG, FLLGYGWAAACAGAR, YIDDEWSGLNGLSSADP. These peptides were found to not only have multiple T cell epitopes but also to have binding affinity with wide HLA molecules. A molecular docking study revealed that the predicted immunogenic peptides (with single or multiple T cell epitopes) of MTDH have comparable binding energies with naturally bound peptides for both HLA classes I and II. Thus, these peptides have the potential to induce immune responses that could be considered for developing synthetic peptide vaccines against multiple cancers.