Cytotoxic T Lymphocytes Epitopes Research Articles

Designing a multi-epitope construct using immuno-informatic tools to prepare a messenger RNA vaccine against Rhipicephalus microplus ticks

Background and Aim: Ticks are blood-feeding ectoparasites that transmit pathogens to animals and humans. One of the most important hard ticks in animals is Rhipicephalus microplus, which transmits Babesia and Anaplasma spp. Although many potential tick vaccine candidates have been identified, no effective vaccine that can provide sterile immunity against R. microplus tick infestations has been developed. This study aimed to design a construct using different computational tools to identify and predict immunogenic epitopes within protein sequences and to prepare a messenger RNA (mRNA) vaccine against R. microplus based on lipid nanoparticles (LNPs). Materials and Methods: The R. microplus proteins (Bm86, Subolesin, and ATAQ) were selected and their consensus sequence was obtained from the National Center for Biotechnology Information in FASTA format. The Immune Epitope Database and Analysis Resource (IEBD) server was used for the prediction of helper T-cell epitopes, the NetCTL 1.2 server was used to predict cytotoxic T-cell epitopes, and the ABCpred server was used for B-cell epitope prediction. Antigenicity testing, allergenicity assessment, and toxicity screening were immuno-informatic techniques used to identify potent epitopes within protein sequences. The multi-epitope construct was prepared and cloned into the pVAX1 plasmid. Plasmids were transformed in compatible competent cells, and restriction analysis was performed. After restriction analysis of the transformed plasmid, in vitro transcription was performed to prepare mRNA. The mRNA was purified, quantified, and converted into complementary DNA, and gene-specific primers were used to confirm the in vitro transcription of mRNA. A mixture of four lipids containing 1,2-dioleoyl-3-dimethylammonium-propane (DODAP), Distearoylphosphatidylcholine (DSPC, cholesterol, and 1,2-Dimyristoyl-sn-glycero-3-methoxypolyethylene glycol-2000 (DMG PEG-2000 was used to prepare LNPs. LNPs were characterized using a scanning electron microscope, Zeta potential, and Zeta Sizer tests. Results: More than 1000 epitopes were predicted, from which only nine helper T-lymphocytes, 18 cytotoxic T-lymphocytes, and nine B-cell epitopes of all three proteins were selected with high antigenic scores of 0.958 for Bm86, 0.752 for Subolesin, and 0.964 for ATAQ, respectively. An adjuvant was used to enhance immune responses, all of which were linked to one another using GPGPG, AAY, and KK linkers, respectively. The physiochemical properties predicted that the instability index of the construct would be <40%, indicating that the construct is stable. Plasmids were transformed in compatible competent cells, and white-transformed colonies were observed. Restriction analysis was performed, DNA was transcribed into mRNA, and LNPs were prepared and characterized. Conclusion: More than 1000 epitopes were predicted using immune informatic tools, and only high-scoring epitopes were selected. A multi-epitope construct was designed using bio-informatic tools, and its physicochemical properties were predicted. The design construct was inserted into the pVAX1 plasmid, and in vitro transcription was performed to prepare the mRNA. LNPs of mRNA were prepared and characterized to be used as vaccines. It was found that LNPs were stable and nanometer-sized. Keywords: immuno-informatic tools, lipid nanoparticles, multiepitope construct, Rhipicephalus microplus.

Targeting Polyprotein to Design Potential Multiepitope Vaccine against Omsk Hemorrhagic Fever Virus (OHFV) by Evaluating Allergenicity, Antigenicity, and Toxicity Using Immunoinformatic Approaches.

Omsk Hemorrhagic Fever Virus (OHFV) is an RNA virus with a single-stranded, positive-sense genome. It is classified under the Flaviviridae family. The genome of this virus is 98% similar to the Alkhurma hemorrhagic fever virus (AHFV), which belongs to the same family. Cases of the virus have been reported in various regions of Saudi Arabia. Both OHFV and AHFV have similarities in pathogenic polyprotein targets. No effective and licensed vaccines are available to manage OHFV infections. Therefore, an effective and safe vaccine is required that can activate protective immunity against OHFV. The current study aimed to design a multiepitope subunit vaccine against the OHFV utilizing several immunoinformatic tools. The polyprotein of OHFV was selected and potent antigenic, non-allergenic, and nontoxic cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and linear B-lymphocyte (LBL) epitopes were chosen. After screening, eight (8) CTL, five (5) HTL, and six (6) B cell epitopes were joined with each other using different linkers. Adjuvant human beta defensin-2 was also linked to the epitopes to increase vaccine antigenic and immunogenic efficiency. The designed vaccine was docked with Toll-like receptor 4 (TLR4) as it activates and induces primary and secondary immune responses against OHFV. Codon optimization was carried out, which resulted in a CAI value of 0.99 and 53.4% GC contents. In addition, the construct was blindly docked to the TLR4 immune receptor and subjected to conformational dynamics simulation analysis to interpret the intricate affinity and comprehend the time-dependent behavior. Moreover, it was predicted that immune responses to the developed vaccine construct reported formation of strong humoral and cellular immune cells. Therefore, the proposed vaccine may be considered in experimental assays to combat OHFV infections. Laboratory experiments for the above predictions are essential in order to evaluate the effectiveness, safety, and protective properties of the subject in question.

Comprehensive bioinformatics assessments of the ROP34 of Toxoplasma gondii to approach vaccine candidates

IntroductionRhoptries proteins (ROPs) are crucial throughout different stages of the Toxoplasma gondii (T. gondii) lifecycle, playing key roles in both the invasion of host cells and their subsequent survival. ROP34 is particularly noteworthy as it significantly influences host gene expression and aids in the transition from the tachyzoite to the bradyzoite form.Materials and methodsThis research utilized various bioinformatics tools to assess physico-chemical properties, allergenic and antigenic characteristics, sites for post-translational modifications (PTMs) and protein's secondary and three-dimensional structures of the ROP34 protein. Furthermore, the study identified potential B-cell, MHC-binding, and cytotoxic T-lymphocyte (CTL) epitopes within the ROP34 sequence.ResultsThe ROP34 peptide comprised 553 amino acid residues, with a calculated average molecular weight (MW) of 61.60149 kDa, an aliphatic index of 73.98, and a GRAVY score of − 0.554. The antigenicity of the multi-epitope peptide was estimated to be 0.526563 and 0.6025 by the ANTIGENpro and VaxiJen servers, respectively, suggesting ROP34 as an immunogenic protein with no allergenic potential. Secondary structure analysis revealed a composition of 52.80% random coil, 36.17% alpha helix, and 11.03% extended strand. The Ramachandran plot for the refined model depicted that 97.46% of the residues were situated in the favored region.ConclusionThis in silico research serves as a foundation for designing effective immunization tactics to target toxoplasmosis. The present article lays the groundwork for future studies and offers perspectives for the advancement of an appropriate toxoplasmosis vaccine.Graphical

Targeting Yezo Virus Structural Proteins for Multi-Epitope Vaccine Design Using Immunoinformatics Approach.

A novel tick-borne orthonairovirus called the Yezo virus (YEZV), primarily transmitted by the Ixodes persulcatus tick, has been recently discovered and poses significant threats to human health. The YEZV is considered endemic in Japan and China. Clinical symptoms associated with this virus include thrombocytopenia, fatigue, headache, leukopenia, fever, depression, and neurological complications ranging from mild febrile illness to severe outcomes like meningitis and encephalitis. At present, there is no treatment or vaccine readily accessible for this pathogenic virus. Therefore, this research employed an immunoinformatics approach to pinpoint potential vaccine targets within the YEZV through an extensive examination of its structural proteins. Three structural proteins were chosen using specific criteria to pinpoint T-cell and B-cell epitopes, which were subsequently validated through interferon-gamma induction. Six overlapping epitopes for cytotoxic T-lymphocytes (CTL), helper T-lymphocytes (HTL), and linear B-lymphocytes (LBL) were selected to construct a multi-epitope vaccine, achieving a 92.29% coverage of the global population. These epitopes were then fused with the 50S ribosomal protein L7/L12 adjuvant to improve protection against international strains. The three-dimensional structure of the designed vaccine construct underwent an extensive evaluation through structural analysis. Following molecular docking studies, the YEZV vaccine construct emerged as a candidate for further investigation, showing the lowest binding energy (-78.7 kcal/mol) along with favorable physiochemical and immunological properties. Immune simulation and molecular dynamics studies demonstrated its stability and potential to induce a strong immune response within the host cells. This comprehensive analysis indicates that the designed vaccine construct could offer protection against the YEZV. It is crucial to conduct additional in vitro and in vivo experiments to verify its safety and effectiveness.

Immunoinformatic Analysis of Leishmania Major gp46 Protein and Potential Targets for Vaccination against Leishmaniasis.

Cutaneous leishmaniasis (CL) is a parasitic disease with a significant burden in the Old World countries. In the current study, some of the primary biochemical properties and IFN-γ inducing epitopes with specific binding capacity to human and mouse MHC alleles were predicted for Leishmania major gp46 antigenic protein. Several online servers were used to predict physico-chemical traits, allergenicity, antigenicity, transmembrane domain and signal peptide, subcellular localization, post-translational modifications (PTMs), secondary and tertiary structures, tertiary model refining with validations. Also, IEDB web server was used to predict mouse/human cytotoxic T-lymphocyte (CTL) and helper T-lymphocyte (HTL) epitopes. The 33.25 kDa protein was stable, hydrophilic, antigenic, while non-allergenic, with enhanced thermotolerance and 45 PTM sites. The secondary structure encompassed a random coil, followed by extended strands and helices. Ramachandran-based analysis of the refined model showed 73.1%, 21.6%, 3.4% and 1.9% of residues in the most favored, additional allowed, generously-allowed and disallowed regions, respectively. Epitope screening demonstrated 4 HTL epitopes against seemingly protective HLA alleles, 5 HTL epitopes against the HLA reference set, 3 human CTL epitopes and a number of mouse MHC-restricted epitopes. This paper provides insights into the bioinformatics characteristics of the L. major gp46 protein as a promising vaccine candidate.

In silico Identification of MHC Displayed Tumor Associated Peptides in Ovarian Cancer for Multi-Epitope Vaccine Construct.

Recognizing the potential of the immune system, immunotherapies have brought about a revolution in the treatment of cancer. Low tumour mutational burden and strong immunosuppression in the peritoneal tumor microenvironment (TME) lead to poor outcomes of immune checkpoint inhibition (ICI) and CART cell therapy in ovarian cancer. Alternative immunotherapeutic strategies are of utmost importance to achieve sound clinical success. The development of peptide vaccines based on tumor-associated antigens (TAAs) for ovarian cancer cells can be a potential target to provoke an anti-tumor immune response and subsequent clearance of tumour cells. The purpose of this in silico study was to find potential epitopes for a multi-epitope vaccine construct using the immunopeptidomics landscape of ovarian carcinoma. The four TAAs (MUC16, IDO1, FOLR1, and DDX5) were selected for potential epitopes prediction. The epitopes for B-cells, helper T-lymphocytes (HTL), and Cytotoxic Tlymphocytes (CTL) were predicted on the basis of antigenic, allergenic, and toxic properties. These epitopes were combined with suitable linkers and an adjuvant to form a multi-epitope construct. Four HTLs, 13 CTLs, and 6 potential B-cell epitopes were selected from the predicted epitope. The designed multi-epitope construct was potentially immunogenic, non-toxic, and non-allergenic. Physicochemical properties and higher-order structural analyses of the final construct revealed a potential vaccine candidate. The designed vaccine construct has the potential to trigger both humoral and cellular immune responses and may be employed as a therapeutic immunization candidate for ovarian malignancies. However, further in vitro and animal experimentation is required to establish the efficacy of the vaccine candidate.

Design a novel of Brucellosis preventive vaccine based on IgV_CTLA-4 and multiple epitopes via immunoinformatics approach

Brucellosis is a zoonotic disease caused by Brucella, which is difficult to eliminate by conventional drugs. Therefore, a novel multi-epitope vaccine (MEV) was designed to prevent human Brucella infection. Based on the method of “reverse vaccinology”, cytotoxic T lymphocyte epitopes (CTLEs), helper T lymphocyte epitopes (HTLEs), linear B-cell epitopes (LBEs) and conformational B-cell epitopes (CBEs) of four Brucella proteins (VirB9, VirB10, Omp 19 and Omp 25) were obtained. In order to keep the correct protein folding, the multiple epitopes was constructed by connecting epitopes through linkers. In view of the significant connection between human leukocyte antigen CTLA-4 and B7 molecules found on antigen presenting cells (APCs), a new vaccine (V_C4MEV) for preventing brucellosis was created by combining CTLA-4 immunoglobulin variable region (IgV_CTLA-4) with MEV protein. Immunoinformatics analysis showed that V_C4MEV has a good secondary and tertiary structure. Additionally, molecular docking and molecular dynamics simulation (MD) revealed a robust binding affinity between IgV_ CTLA-4 and the B7 molecule. Notably, the vaccine V_C4MEV was demonstrated favorable immunogenicity and antigenicity in both in vitro and in vivo experiments. V_C4MEV had the potential to activate defensive cells and immune responses, offering a hopeful approach for developing vaccines against Brucella in the upcoming years.

An immunoinformatic investigation on Rift Valley fever virus protein reveals possible epitopes for vaccines.

This immunoinformatic study identified potential epitopes from the envelopment polyprotein (Gn/Gc) of Rift Valley fever virus (RVFV), a pathogenic virus causing severe fever in humans and livestock. Effective vaccination is crucial for controlling RVFV outbreaks. The identification of suitable epitopes is crucial for the development of safe and effective vaccines. Protein sequences were obtained from the UniProt database, and evaluated through VaxiJen v2.0 to predict the B and T-cell epitopes within the RVFV glycoprotein. Gn/Gc protein sequences were analyzed with bioinformatics tools and algorithms. The predicted T-cell and B-cell epitopes were evaluated for antigenicity, allergenicity, and toxicity by the VaxiJen v2.0 system, AllerTop v2.0, and ToxinPred server, respectively. We employed computational methods to screen the RVFV envelopment polyprotein encompassing N-terminal and C-terminal glycoprotein segments, to discover antigenic T- and B-cell epitopes. Our analysis unveiled multiple potential epitopes within the RVFV glycoprotein, specifically within the Gn/Gc protein sequences. Subsequently, we selected eleven cytotoxic T-lymphocytes (CTL) and four helper T-lymphocytes (HTL) for population coverage analysis, which collectively extended to cover 97.04% of the world's population, representing diverse ethnicities and regions. Notably, the CTL epitope VQADLTLMF exhibited binding affinity to numerous human leukocyte antigen (HLA) alleles. The identification of glycoprotein (Gn/Gc) epitopes through this immunoinformatic study bears significant implications for advancing the development of an effective RVFV vaccine. These findings provide valuable insights into the immunological aspects of the disease and may contribute towards the development of broad-spectrum antiviral therapies targeting other RNA viruses with similar polymerase enzymes.

A Multi-epitope Subunit Vaccine Identification and Development Against Scrub Typhus (Orientia tsutsugamushi) Using Immunoinformatics Approaches.

Background The pathogen Orientia tsutsugamushi, which causes scrub typhus, is rapidlyspreading throughout the tropics. As a measure to improve public health, the development of a vaccine for human use is essential. Scrub typhus is listed as one of the underdiagnosed and underreported febrile infections. This vector-borne zoonotic infection appears as eschar on the patient's skin. Methods Immunoinformaticswas employed to predict the multi-epitope subunit vaccine that will activate both B and T cells. The final vaccine includes lipoprotein LprA as an adjuvant at the N-terminus along with B-cell, helperTlymphocyte (HTL), and cytotoxic T lymphocyte (CTL)-binding epitopes to boost immunogenicity. Assessing the vaccine's physiochemistry demonstrates that it is both antigenic and non-allergic. The vaccine structure was developed, enhanced, confirmed, and disulfide-engineered to provide the best possible model. Using molecular docking, the interaction of the produced vaccine with toll-like receptor 2 (TLR2) was analyzed, and the vaccine-receptor complex was stabilized by molecular dynamics (MD) simulation. According to in silico cloning, Escherichia coli can efficiently produce the recommended vaccine. Additionally, the efficacy of the in silico-developed vaccine must be evaluated in an in vitro and in vivo experiment. Results The developed vaccine successfully stimulates cellular and humoral immune responses. The vaccine, which has three B-cell epitopes, three HCL epitopes, and nine CTL epitopes, can bind firmly to immunological receptors. Dynamic investigations of the vaccine-receptor complex show a strong interaction and stable conformation. Conclusion In this study, the vaccine candidate demonstrated strong antigenicity, stability, and solubility while also being non-allergenic to host cells. The vaccine candidate's stability with the TLR2 immune receptor is established by binding studies, and in silico cloning verifies efficient and stable expression in the bacterial system.

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\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\beta$$\\end{document}-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.

Subtractive proteomics-guided vaccine targets identification and designing of multi-epitopes vaccine for immune response instigation against Burkholderia pseudomallei

In this study, a methodical workflow using subtractive proteomics, vaccine designing, molecular simulation, and agent-based modeling approaches were used to annotate the whole proteome of Burkholderia pseudomallei (strain K96243) for vaccine designing. Among the total 5717 proteins in the whole proteome, 505 were observed to be essential for the pathogen's survival and pathogenesis predicted by the Database of Essential Genes. Among these, 23 vaccine targets were identified, of which fimbrial assembly chaperone (Q63UH5), Outer membrane protein (Q63UH1), and Hemolysin-like protein (Q63UE4) were selected for the subsequent analysis based on the systematic approaches. Using immunoinformatic approaches CTL (cytotoxic T lymphocytes), HTL (helper T lymphocytes), IFN-positive, and B cell epitopes were predicted for these targets. A total of 9 CTL epitopes were added using the GSS linker, 6 HTL epitopes using the GPGPG linker, and 6 B cell epitopes using the KK linker. An adjuvant was added for enhanced antigenicity, an HIV-TAT peptide for improved delivery, and a PADRE sequence was added to form a 466 amino acids long vaccine construct. The construct was classified as non-allergenic, highly antigenic, and experimentally feasible. Molecular docking results validated the robust interaction of MEVC with immune receptors such as TLR2/4. Furthermore, molecular simulation revealed stable dynamics and compact nature of the complexes. The binding free energy results further validated the robust binding. In silico cloning, results revealed GC contents of 50.73 % and a CIA value of 0.978 which shows proper downstream processing. Immune simulation results reported that after the three injections of the vaccine a robust secondary immune response, improved antigen clearance, and effective immune memory generation were observed highlighting its potential for effective and sustained immunity. Future directions should encompass experimental validations, animal model studies, and clinical trials to substantiate the vaccine's efficacy, safety, and immunogenicity.

Immunoinformatics Design and In Vivo Immunogenicity Evaluation of a Conserved CTL Multi-Epitope Vaccine Targeting HPV16 E5, E6, and E7 Proteins.

Human papillomavirus type 16 (HPV16) infection is responsible for more than 50% of global cervical cancer cases. The development of a vaccine based on cytotoxic T-lymphocyte (CTL) epitopes is a promising strategy for eliminating pre-existing HPV infections and treating patients with cervical cancer. In this study, an immunoinformatics approach was used to predict HLA-I-restricted CTL epitopes in HPV16 E5, E6, and E7 proteins, and a set of conserved CTL epitopes co-restricted by human/murine MHCs was screened and characterized, with the set containing three E5, four E6, and four E7 epitopes. Subsequently, the immunogenicity of the epitope combination was assessed in mice, and the anti-tumor effects of the multi-epitope peptide vaccine E5E6E7pep11 and the recombinant protein vaccine CTB-Epi11E567 were evaluated in the TC-1 mouse tumor model. The results demonstrated that mixed epitope peptides could induce antigen-specific IFN-γ secretion in mice. Prophylactic immunization with E5E6E7pep11 and CTB-Epi11E567 was found to provide 100% protection against tumor growth in mice. Moreover, both types of the multi-epitope vaccine significantly inhibited tumor growth and prolonged mouse survival. In conclusion, in this study, a multi-epitope vaccine targeting HPV16 E5, E6, and E7 proteins was successfully designed and evaluated, demonstrating potential immunogenicity and anti-tumor effects and providing a promising strategy for immunotherapy against HPV-associated tumors.

Designing a Novel Multiepitope Vaccine from the Human Papilloma Virus E1 and E2 Proteins for Indonesia with Immunoinformatics and Molecular Dynamics Approaches.

One of the deadliest malignant cancer in women globally is cervical cancer. Specifically, cervical cancer is the second most common type of cancer in Indonesia. The main infectious agent of cervical cancer is the human papilloma virus (HPV). Although licensed prophylactic vaccines are available, cervical cancer cases are on the rise. Therapy using multiepitope-based vaccines is a very promising therapy for cervical cancer. This study aimed to develop a multiepitope vaccine based on the E1 and E2 proteins of HPV 16, 18, 45, and 52 using in silico. In this study, we develop a novel multiepitope vaccine candidate using an immunoinformatic approach. We predicted the epitopes of the cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) and evaluated their immunogenic properties. Population coverage analysis of qualified epitopes was conducted to determine the successful use of the vaccine worldwide. The epitopes were constructed into a multiepitope vaccine by using AAY linkers between the CTL epitopes and GPGPG linkers between the HTL epitopes. The tertiary structure of the multiepitope vaccine was modeled with AlphaFold and was evaluated by Prosa-web. The results of vaccine construction were analyzed for B-cell epitope prediction, molecular docking with Toll like receptor-4 (TLR4), and molecular dynamics simulation. The results of epitope prediction obtained 4 CTL epitopes and 7 HTL epitopes that are eligible for construction of multiepitope vaccines. Prediction of the physicochemical properties of multiepitope vaccines obtained good results for recombinant protein production. The interaction showed that the interaction of the multiepitope vaccine-TLR4 complex is stable based on the binding free energy value -106.5 kcal/mol. The results of the immune response simulation show that multiepitope vaccine candidates could activate the adaptive and humoral immune systems and generate long-term B-cell memory. According to these results, the development of a multiepitope vaccine with a reverse vaccinology approach is a breakthrough to develop potential cervical cancer therapeutic vaccines.

Identification of a new HLA-A*0201-restricted cytotoxic T lymphocyte epitope from TC2N.

Identification of cytotoxic T lymphocyte (CTL) epitopes from tumor related antigens is a promising approach for malignant tumor immunotherapy. TC2N, a recently identified tumor associated antigen from human glioblastoma, is regarded as a promising target of tumor-specific immunotherapy. As one of the most widely used histocompatibility molecules in Chinese is HLA-A*0201, we were able to identify the TC2N peptides that are provided by this molecular type. A panel of antigenic peptides produced from TC2N were predicted by using a computer tool. The binding affinities of three peptides with the highest predicted score to the HLA-A*0201 molecule were evaluated after synthesis. In vitro and in vivo stimulation of the main T-cell response against the predicted peptides. The results demonstrated that TC2N (152-160) was able to release IFN-γ and lyse U251 cells in vitro as well as in vivo by eliciting peptide-specific CTLs. Our results indicated that peptide TC2N (152-160) (RLYGSVCDL) was a novel HLA-A2.1-restricted CTL epitope capable of inducing TC2N specific CTLs in vitro. As TC2N might qualify as a viable target for immunotherapeutic approaches for patients with GBM, we speculated that the newly identified epitope RLYGSVCDL would be of potential use in peptide-based, cancer-specific immunotherapy against GBM.

Development of a novel multi‑epitope vaccine against the pathogenic human polyomavirus V6/7 using reverse vaccinology.

Human polyomaviruses contribute to human oncogenesis through persistent infections, but currently there is no effective preventive measure against the malignancies caused by this virus. Therefore, the development of a safe and effective vaccine against HPyV is of high priority. First, the proteomes of 2 polyomavirus species (HPyV6 and HPyV7) were downloaded from the NCBI database for the selection of the target proteins. The epitope identification process focused on selecting proteins that were crucial, associated with virulence, present on the surface, antigenic, non-toxic, and non-homologous with the human proteome. Then, the immunoinformatic methods were used to identify cytotoxic T-lymphocyte (CTL), helper T-lymphocyte (HTL), and B-cell epitopes from the target antigens, which could be used to create epitope-based vaccine. The physicochemical features of the designed vaccine were predicted through various online servers. The binding pattern and stability between the vaccine candidate and Toll-like receptors were analyzed through molecular docking and molecular dynamics (MD) simulation, while the immunogenicity of the designed vaccines was assessed using immune simulation. Online tools were utilized to forecast the most optimal epitope from the immunogenic targets, including LTAg, VP1, and VP1 antigens of HPyV6 and HPyV7. A multi-epitope vaccine was developed by combining 10 CTL, 7 HTL, and 6 LBL epitopes with suitable linkers and adjuvant. The vaccine displayed 98.35% of the world's population coverage. The 3D model of the vaccine structure revealed that the majority of residues (87.7%) were located in favored regions of the Ramachandran plot. The evaluation of molecular docking and MD simulation revealed that the constructed vaccine exhibits a strong binding (-1414.0 kcal/mol) towards the host's TLR4. Moreover, the vaccine-TLR complexes remained stable throughout the dynamic conditions present in the natural environment. The immune simulation results demonstrated that the vaccine design had the capacity to elicit robust immune responses in the host. The multi-parametric analysis revealed that the designed vaccine is capable of inducing sustained immunity against the selected polyomaviruses, although further in-vivo investigations are needed to verify its effectiveness.

Designing of a Novel Candidate Multi-epitope Vaccine to boost Immune Responses against SARS‐COV‐2 using Immunoinformatics and Machine Learning based Approach

Background: The fast development of an effective vaccine is the major demand for protection against the SARS-COV-2 virus outbreak. With the vast volume of data and the requirement for automatic abstract property learning, machine learning (ML) as a branch of artificial intelligence (AI) has a significant contribution in areas of vaccine discovery. The rise of ML has greatly accelerated the often lengthy vaccine approval process. ML models for COVID-19 vaccine development focus on the prediction of potential epitopes by using a variety of techniques, such as artificial neural networks, gradient boosting decision trees and deep neural networks. : In this regard, immuno-informatics tools are time-saving and cost-effective methods to hasten the design and establishment of a proficient multi-peptide candidate vaccine. The utilization of multi-epitope-based vaccines has been demonstrated to be a promising immunization approach against viruses due to the induction of long-term protective immunity. Methods: In the present study, a comprehensive computational and machine learning based approach was conducted to design a multi-epitope-based potential candidate vaccine composed of cytotoxic T lymphocyte (CTL) and helper T lymphocyte (HTL) epitopes of conserved regions of Spike and Nucleocapsid proteins. The potential viral peptides as the candidate vaccine were screened regarding convenient features like hydrophilicity, flexibility, antigenicity, and charging properties. In the next step, the vaccine efficacy needs to be improved by an immune adjuvant. For this purpose, the C-terminal domain of the heat shock protein gp96 (CT-GP96) was applied as a potent adjuvant for enhancing immunity. The five assembled constructs with different peptide orders were generated and fused with the assistance of suitable linkers. All five assembled candidate vaccine constructs were modeled and their 3D structures were assessed in terms of strong immune responses stimulation and their structural stability and immune processing for response induction. Finally, the best refined model was docked to toll-like receptor 4 (TLR4). Furthermore, Molecular Dynamics (MD) simulation of the vaccine-receptor complex was done to assess the stability and related physical movements of the vaccine-TLR4 docking complex. The final candidate vaccine was computationally cloned in E. coli expression host to guarantee its high level of production. Results: Following a comprehensive immune-informatics and machine learning-based approach, the best conserved CTL and HTL immune stimulant epitopes were selected and assembled in different orders to build five different constructs. The final validated candidate vaccine construct was selected according to its efficacy, stability, and exposure ability, molecular docking analysis with TLR4. The molecular simulations by iMODS software also confirmed the stability of the binding interface. Additionally, the computational cloning of the final assembled candidate vaccine with pET28a plasmid showed the possibility of high level production of the vaccine construct post transformation in an E. coli host. Conclusion: The computational analysis indicated that this construct can be proposed as a potent prophylactic and therapeutic candidate multi-epitope vaccine against SARS-COV-2 once its effectiveness is verified by experimental and animal studies.

Potential SLA Hp-4.0 haplotype-restricted CTL epitopes identified from the membrane protein of PRRSV induce cell immune responses.

Swine leukocyte antigen (SLA) class I molecule-restricted T-cell epitopes, which induce cytotoxic T lymphocyte (CTL) responses, play a critical role in the clearance of porcine reproductive and respiratory syndrome virus (PRRSV) and the development of efficient protective vaccines. The SLA-1*04:01:01, SLA-2*04:01, and SLA-3*04:01 alleles, assigned the Hp-4.0 haplotype, are highly prevalent and usually present in all pig breeds. However, the SLA Hp-4.0 haplotype-restricted CTL epitopes in the structural membrane (M) protein of PRRSV are still unknown. In this study, we predicted 27 possible 9-mer epitope peptides in M protein with high binding scores for SLA-1*04:01:01 using CTL epitope prediction tools. In total, 45 SLA class I complexes, comprising the predicted peptide, extracellular region of the SLA-I molecules, and β2-microglobulin, were constructed in vitro to detect the specific binding of these peptides to SLA-1*04:01:01 (27 complexes), SLA-2*04:01 (9 complexes), and SLA-3*04:01 (9 complexes), respectively. Our results showed that the M27 (T91WKFITSRC), M39 (N130HAFVVRRP), and M49 (G158RKAVKQGV) peptides bind specifically to SLA-1*04:01:01, SLA-2*04:01, and SLA-3*04:01, respectively. Subsequently, using peripheral blood mononuclear cells (PBMCs) isolated from the homozygous Hp-4.0 and Hp-26.0 haplotype piglets vaccinated with commercial PRRSV HuN4-F112 strain, we determined the capacities of these 27 potential peptides to stimulate their proliferation with a Cell Counting Kit-8 and their secretion and expression of interferon gamma (IFN-γ) with an ELISpot assay and real-time qPCR, respectively. The immunological activities of M27, M39, and M49 were therefore confirmed when they efficiently induced PBMC proliferation and IFN-γ secretion in PBMCs from piglets with the prevalent SLA Hp-4.0 haplotype. The amino acid sequence alignment revealed that M27, M39, and M49 are highly conserved among 248 genotype II PRRSV strains collected between 1998 and 2019. These findings contribute to the understanding of the mechanisms of cell-mediated immune responses to PRRSV. Our study also provides a novel strategy for identifying and confirming potential SLA haplotype-restricted CTL epitopes that could be used to develop novel peptide-based vaccines against swine diseases.

Harnessing bioinformatics for the development of a promising multi-epitope vaccine against tuberculosis: The ZL9810L vaccine

BackgroundTuberculosis (TB) is a global infectious disease posing a serious threat to human health, caused by Mycobacterium tuberculosis (MTB) infection. Although vaccination is the most effective way to prevent and control TB, the existing Bacillus Calmette–Guérin (BCG) vaccine exhibits limited protective efficacy in adult pulmonary TB. Therefore, developing a novel TB vaccine is an urgent need. MethodsThis study designed a novel multi-epitope vaccine (MEV) to combat MTB infection, utilizing bioinformatics and immunoinformatics approaches. Dominant epitopes of helper T lymphocytes (HTL), cytotoxic T lymphocytes (CTL), and B lymphocytes were selected from antigens of MTB to construct the MEV. To enhance the targeting and immunogenicity of the vaccine, toll like receptor (TLR) agonists and PADRE helper peptides were incorporated into the design. In addition, comprehensive predictions have been made on the physicochemical properties, three-dimensional structure, spatial conformation, and molecular interactions with TLRs of MEVs. These evaluations also extend to the exploration of their immunological characteristics. ResultsA novel MEV named ZL9810L was successfully constructed, based on 8 HTL epitopes, 9 CTL epitopes, 10 B lymphocyte epitopes, Toll-like receptor agonists, and auxiliary peptides. Bioinformatics analysis demonstrated that the ZL9810L vaccine has excellent immunogenicity and antigenicity, non-toxicity, and non-sensitization capability, capable of significantly inducing a strong immune response and solubility, with scores of 2.21451, 0.8913, and 0.455 respectively. Moreover, the global population coverage of HLA class I and II allele genes by the ZL9810L vaccine reached 72.89 % and 81.49 %, respectively. Molecular docking analysis indicated good binding capacities of the ZL9810L vaccine to TLR2 and TLR4 receptors, with binding energies of −1028.5 kcal/mol and −1018.8 kcal/mol respectively. Immune simulation predicted that the vaccine could effectively activate innate and adaptive immune cells, including NK cells, macrophages, B lymphocytes, and T lymphocytes. ConclusionAs a candidate for a novel TB vaccine, the ZL9810L vaccine exhibits significant immunogenicity and antigenicity, with no toxicity or allergenicity. The ZL9810L vaccine designed in this study provides a new vaccine candidate for TB control and prevention.

Enzyme-Linked Immunosorbent Assay for Antibodies Against the Tumor-Associated Antigen-Derived Cytotoxic T-Lymphocyte Epitope.

Antibodies serve as crucial indicators of the immune system in clinical tests. In therapeutic cancer vaccines, IgG antibodies against target antigens are vital for immune monitoring. Additionally, assessing baseline antigen-specific immune responses before cancer vaccine administration is possible by measuring IgM and IgG antibodies against the target antigen. To this end, we have developed an enzyme-linked immunosorbent assay (ELISA) system that detects and quantifies serum levels of IgG and IgM antibodies against the WT1 cytotoxic T-lymphocyte epitope peptide. The assay immobilizes the epitope peptide in a microplate to capture antigen-specific antibodies. Here, this article presents the details of our ELISA system to detect and measure antibodies against a tumor-associated antigen-derived cytotoxic T-lymphocyte epitope with high reproducibility. Detecting these antibodies has novel significance in the context of emerging critical roles of B lineage-cells in tumor immunity.

Epitope-based therapeutic targets in HCV genotype 1 non-structural proteins: a novel strategy to combat emerging drug resistance.

The hepatitis C virus (HCV) poses a major global health challenge, with its non-structural proteins being essential for viral replication and pathogenesis. Mutations in these proteins significantly contribute to drug resistance, necessitating innovative therapeutic strategies. This study aims to identify epitope-based therapeutic targets in the non-structural proteins of HCV genotype 1, employing in-depth in silico tools to counteract emerging drug resistance. We retrieved approximately 250 sequences of each non-structural protein from the NCBI database, capturing a broad spectrum of variability and sequence alignments, variability analysis and physicochemical property analysis were conducted. We utilized the TEPITOOL server by IEDB to predict cytotoxic T lymphocyte (CTL) epitopes. Following this, we assessed the efficiency of TAP transport and proteasomal cleavage using IEDB's combined predictor tool. The epitopes were selected based on conservancy analysis, immunogenicity, allergenicity, and presence in non-glycosylated regions, ensuring high predictive scores and suitability as vaccine candidates. Epitopes were docked with the HLA-A*02:01 allele and Toll-like receptor-3 using the ClusPro server. The immune response potential of the epitopes was evaluated through in-silico immune stimulation. The study identified 27 potential CTL epitopes from the non-structural proteins, including NS3, NS4a, NS4b, NS5a, and NS5b. Out of these, three lead epitopes demonstrated high conservation (>90%), strong binding affinities to HLA-A*02:01 and TLR-3, and robust immune response potential. These epitopes also showed favorable characteristics such as being non-allergenic and non-glycosylated. This comprehensive in-silico analysis provides a promising foundation for developing an epitope-based vaccine targeting HCV non-structural proteins, offering a novel approach to overcoming drug resistance in HCV treatment.