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Zhu Y, Shi J, Wang Q, Zhu Y, Li M, Tian T, Shi H, Shang K, Yin Z, Zhang F. Novel dual-pathogen multi-epitope mRNA vaccine development for Brucella melitensis and Mycobacterium tuberculosis in silico approach. PLoS One 2024; 19:e0309560. [PMID: 39466745 PMCID: PMC11515988 DOI: 10.1371/journal.pone.0309560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/05/2024] [Accepted: 08/13/2024] [Indexed: 10/30/2024] Open
Abstract
Brucellosis and Tuberculosis, both of which are contagious diseases, have presented significant challenges to global public health security in recent years. Delayed treatment can exacerbate the conditions, jeopardizing patient lives. Currently, no vaccine has been approved to prevent these two diseases simultaneously. In contrast to traditional vaccines, mRNA vaccines offer advantages such as high efficacy, rapid development, and low cost, and their applications are gradually expanding. This study aims to develop multi-epitope mRNA vaccines argeting Brucella melitensis and Mycobacterium tuberculosis H37Rv (L4 strain) utilizing immunoinformatics approaches. The proteins Omp25, Omp31, MPT70, and MPT83 from the specified bacteria were selected to identify the predominant T- and B-cell epitopes for immunological analysis. Following a comprehensive evaluation, a vaccine was developed using helper T lymphocyte epitopes, cytotoxic T lymphocyte epitopes, linear B-cell epitopes, and conformational B-cell epitopes. It has been demonstrated that multi-epitope mRNA vaccines exhibit increased antigenicity, non-allergenicity, solubility, and high stability. The findings from molecular docking and molecular dynamics simulation revealed a robust and enduring binding affinity between multi-epitope peptides mRNA vaccines and TLR4. Ultimately, Subsequently, following the optimization of the nucleotide sequence, the codon adaptation index was calculated to be 1.0, along with an average GC content of 54.01%. This indicates that the multi-epitope mRNA vaccines exhibit potential for efficient expression within the Escherichia coli(E. coli) host. Analysis through immune modeling indicates that following administration of the vaccine, there may be variation in immunecell populations associated with both innate and adaptive immune reactions. These types encompass helper T lymphocytes (HTL), cytotoxic T lymphocytes (CTL), regulatory T lymphocytes, natural killer cells, dendritic cells and various immune cell subsets. In summary, the results suggest that the newly created multi-epitope mRNA vaccine exhibits favorable attributes, offering novel insights and a conceptual foundation for potential progress in vaccine development.
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Affiliation(s)
- Yuejie Zhu
- Department of Reproductive Assistance, Center for Reproductive Medicine, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Juan Shi
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Quan Wang
- The Eighth Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Yun Zhu
- Xinjiang Uygur Autonomous Region Disease Prevention Control Center, Urumqi, Xinjiang, China
| | - Min Li
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Tingting Tian
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Huidong Shi
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Kaiyu Shang
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Zhengwei Yin
- The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
| | - Fengbo Zhang
- Department of Clinical Laboratory, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
- State Key Laboratory of Pathogenesis, Prevention, Treatment of Central Asian High Incidence Diseases, The First Affiliated Hospital of Xinjiang Medical University, Urumqi, Xinjiang, China
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Jiang D, Ma Z, Zhang J, Sun Y, Bai T, Liu R, Wang Y, Guan L, Fu S, Sun Y, Li Y, Zhou B, Yang Y, Yang S, Chang Y, Sun B, Yang K. Immunoreactivity Analysis of MHC-I Epitopes Derived from the Nucleocapsid Protein of SARS-CoV-2 via Computation and Vaccination. Vaccines (Basel) 2024; 12:1214. [PMID: 39591116 PMCID: PMC11598499 DOI: 10.3390/vaccines12111214] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2024] [Revised: 10/19/2024] [Accepted: 10/22/2024] [Indexed: 11/28/2024] Open
Abstract
Background: Since 2019, the SARS-CoV-2 virus has been responsible for the global spread of respiratory illness. As of 1 September 2024, the cumulative number of infections worldwide exceeded 776 million. There are many structural proteins of the virus, among which the SARS-CoV-2 nucleocapsid (N) protein plays a pivotal role in the viral life cycle, participating in a multitude of essential activities following viral invasion. An important antiviral immune response is the major histocompatibility complex (MHC)-restricted differentiation cluster 8 (CD8+) T cell cytotoxicity. Therefore, understanding the immunogenicity of SARS-CoV-2 NP-specific MHC-I-restricted epitopes is highly important. Methods: MHC-I molecules from 11 human leukocyte antigen I (HLA-I) superfamilies with 98% population coverage and 6 mouse H2 alleles were selected. The affinity were screened by IEDB, NetMHCpan, SYFPEITHI, SMMPMBEC and Rankpep. Further immunogenicity and conservative analyses were performed using VaxiJen and BLASTp, respectively. EpiDock was used to simulate molecular docking. Cluster analysis was performed. Selective epitopes were validated by enzyme-linked immunospot (ELISpot) assay and flow cytometry in the mice with pVAX-NPSARS-CoV-2 immunization. Enzyme-Linked Immunosorbent Assay (ELISA) was used to detect whether the preferred epitope induced humoral immunity. Results: There were 64 dominant epitopes for the H-2 haplotype and 238 dominant epitopes for the HLA-I haplotype. Further analysis of immunogenicity and conservation yielded 8 preferred epitopes, and docking simulations were conducted with corresponding MHC-I alleles. The relationships between the NP peptides and MHC-I haplotypes were then determined via two-way hierarchical clustering. ELISA, ELISpot assay, and flow cytometry revealed that the preferred epitope stimulated both humoral and cellular immunity and enhanced cytokine secretion in mice. Conclusions: our study revealed the general patterns among multiple haplotypes within the humans and mice superfamily, providing a comprehensive assessment of the pan-MHC-I immunoreactivity of SARS-CoV-2 NP. Our findings would render prospects for the development and application of epitope-based immunotherapy in lasting viral epidemics.
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Affiliation(s)
- Dongbo Jiang
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Zilu Ma
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Junqi Zhang
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Yubo Sun
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Tianyuan Bai
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Ruibo Liu
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Yongkai Wang
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Liang Guan
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Shuaishuai Fu
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Yuanjie Sun
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Yuanzhe Li
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Bingquan Zhou
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Yulin Yang
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Shuya Yang
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Yuanhang Chang
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
| | - Baozeng Sun
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
- Yingtan Detachment, Jiangxi General Hospital, Chinese People’s Armed Police Force, Nanchang 330001, China
- General Practice Medicine Base of Shanghai Changzheng Hospital, Shanghai 200041, China
| | - Kun Yang
- Department of Immunology, The Key Laboratory of Bio-Hazard Damage and Prevention Medicine, Basic Medicine School, Air Force Medical University (In Former The Fourth Military Medical University), Xi’an 710032, China; (D.J.); (Z.M.); (J.Z.); (Y.S.); (T.B.); (R.L.); (Y.W.); (L.G.); (S.F.); (Y.S.); (Y.L.); (B.Z.); (Y.Y.); (S.Y.); (Y.C.)
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Kant R, Khan MS, Chopra M, Saluja D. Artificial intelligence-driven reverse vaccinology for Neisseria gonorrhoeae vaccine: Prioritizing epitope-based candidates. Front Mol Biosci 2024; 11:1442158. [PMID: 39193221 PMCID: PMC11347834 DOI: 10.3389/fmolb.2024.1442158] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2024] [Accepted: 07/04/2024] [Indexed: 08/29/2024] Open
Abstract
Neisseria gonorrhoeae is the causative agent of the sexually transmitted disease gonorrhea. The increasing prevalence of this disease worldwide, the rise of antibiotic-resistant strains, and the difficulties in treatment necessitate the development of a vaccine, highlighting the significance of preventative measures to control and eradicate the infection. Currently, there is no widely available vaccine, partly due to the bacterium's ability to evade natural immunity and the limited research investment in gonorrhea compared to other diseases. To identify distinct vaccine candidates, we chose to focus on the uncharacterized, hypothetical proteins (HPs) as our initial approach. Using the in silico method, we first carried out a comprehensive assessment of hypothetical proteins of Neisseria gonorrhoeae, encompassing assessments of physicochemical properties, cellular localization, secretary pathways, transmembrane regions, antigenicity, toxicity, and prediction of B-cell and T-cell epitopes, among other analyses. Detailed analysis of all HPs resulted in the functional annotation of twenty proteins with a great degree of confidence. Further, using the immuno-informatics approach, the prediction pipeline identified one CD8+ restricted T-cell epitope, seven linear B-cell epitopes, and seven conformational B-cell epitopes as putative epitope-based peptide vaccine candidates which certainly require further validation in laboratory settings. The study accentuates the promise of functional annotation and immuno-informatics in the systematic design of epitope-based peptide vaccines targeting Neisseria gonorrhoeae.
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Affiliation(s)
- Ravi Kant
- Medical Biotechnology Laboratory, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
- Delhi School of Public Health, Institute of Eminence (IoE), University of Delhi, Delhi, India
| | - Mohd. Shoaib Khan
- Laboratory of Molecular Modeling and Anticancer Drug Development, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Madhu Chopra
- Laboratory of Molecular Modeling and Anticancer Drug Development, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
| | - Daman Saluja
- Medical Biotechnology Laboratory, Dr. B. R. Ambedkar Center for Biomedical Research, University of Delhi, Delhi, India
- Delhi School of Public Health, Institute of Eminence (IoE), University of Delhi, Delhi, India
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Khalid S, Guo J, Muhammad SA, Bai B. Designing, cloning and simulation studies of cancer/testis antigens based multi-epitope vaccine candidates against cutaneous melanoma: An immunoinformatics approach. Biochem Biophys Rep 2024; 37:101651. [PMID: 38371523 PMCID: PMC10873875 DOI: 10.1016/j.bbrep.2024.101651] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Revised: 01/18/2024] [Accepted: 01/18/2024] [Indexed: 02/20/2024] Open
Abstract
Background Melanoma is the most fatal kind of skin cancer. Among its various types, cutaneous melanoma is the most prevalent one. Melanoma cells are thought to be highly immunogenic due to the presence of distinct tumor-associated antigens (TAAs), which includes carcinoembryonic antigen (CEA), cancer/testis antigens (CTAs) and neo-antigens. The CTA family is a group of antigens that are only expressed in malignancies and testicular germ cells. Methods We used integrative framework and systems-level analysis to predict potential vaccine candidates for cutaneous melanoma involving epitopes prediction, molecular modeling and molecular docking to cross-validate the binding affinity and interaction between potential vaccine agents and major histocompatibility molecules (MHCs) followed by molecular dynamics simulation, immune simulation and in silico cloning. Results In this study, three cancer/testis antigens were targeted for immunotherapy of cutaneous melanoma. Among many CTAs that were studied for their expression in primary and malignant melanoma, NY-ESO-1, MAGE1 and SSX2 antigens are most prevalent in cutaneous melanoma. Cytotoxic and Helper epitopes were predicted, and the finest epitopes were shortlisted based on binding score. The vaccine construct was composed of the four epitope-rich domains of antigenic proteins, an appropriate adjuvant, His tag and linkers. This potential multi-epitope vaccine was further evaluated in terms of antigenicity, allergencity, toxicity and other physicochemical properties. Molecular interaction estimated through protein-protein docking unveiled good interactions characterized by favorable binding energies. Molecular dynamics simulation ensured the stability of docked complex and the predicted immune response through immune simulation revealed elevated levels of antibodies titer, cytokines, interleukins and immune cells (NK, DC and MA) population. Conclusion The findings indicate that the potential vaccine candidates could be effective immunotherapeutic agents that modify the treatment strategies of cutaneous melanoma.
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Affiliation(s)
- Sana Khalid
- Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya University Multan, Pakistan
| | - Jinlei Guo
- School of Intelligent Medical Engineering, Sanquan College of Xinxiang Medical University, Xinxiang, China
| | - Syed Aun Muhammad
- Institute of Molecular Biology and Biotechnology, Bahauddin Zakariya University Multan, Pakistan
| | - Baogang Bai
- School of Information and Technology, Wenzhou Business College, Wenzhou, China
- Zhejiang Province Engineering Research Center of Intelligent Medicine, Wenzhou, China
- The 1st School of Medical, School of Information and Engineering, The 1st Affiliated Hospital of Wenzhou Medical University, Wenzhou, China
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Salod Z, Mahomed O. Mapping Potential Vaccine Candidates Predicted by VaxiJen for Different Viral Pathogens between 2017-2021-A Scoping Review. Vaccines (Basel) 2022; 10:1785. [PMID: 36366294 PMCID: PMC9695814 DOI: 10.3390/vaccines10111785] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Revised: 10/16/2022] [Accepted: 10/18/2022] [Indexed: 09/29/2023] Open
Abstract
Reverse vaccinology (RV) is a promising alternative to traditional vaccinology. RV focuses on in silico methods to identify antigens or potential vaccine candidates (PVCs) from a pathogen's proteome. Researchers use VaxiJen, the most well-known RV tool, to predict PVCs for various pathogens. The purpose of this scoping review is to provide an overview of PVCs predicted by VaxiJen for different viruses between 2017 and 2021 using Arksey and O'Malley's framework and the Preferred Reporting Items for Systematic Reviews extension for Scoping Reviews (PRISMA-ScR) guidelines. We used the term 'vaxijen' to search PubMed, Scopus, Web of Science, EBSCOhost, and ProQuest One Academic. The protocol was registered at the Open Science Framework (OSF). We identified articles on this topic, charted them, and discussed the key findings. The database searches yielded 1033 articles, of which 275 were eligible. Most studies focused on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), published between 2020 and 2021. Only a few articles (8/275; 2.9%) conducted experimental validations to confirm the predictions as vaccine candidates, with 2.2% (6/275) articles mentioning recombinant protein expression. Researchers commonly targeted parts of the SARS-CoV-2 spike (S) protein, with the frequently predicted epitopes as PVCs being major histocompatibility complex (MHC) class I T cell epitopes WTAGAAAYY, RQIAPGQTG, IAIVMVTIM, and B cell epitope IAPGQTGKIADY, among others. The findings of this review are promising for the development of novel vaccines. We recommend that vaccinologists use these findings as a guide to performing experimental validation for various viruses, with SARS-CoV-2 as a priority, because better vaccines are needed, especially to stay ahead of the emergence of new variants. If successful, these vaccines could provide broader protection than traditional vaccines.
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Affiliation(s)
- Zakia Salod
- Discipline of Public Health Medicine, University of KwaZulu-Natal, Durban 4051, South Africa
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Kaushal N, Jain S, Baranwal M. Computational design of immunogenic peptide constructs comprising multiple HLA restricted Dengue virus envelope epitopes. J Mol Recognit 2022; 35:e2961. [PMID: 35514257 DOI: 10.1002/jmr.2961] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 02/01/2022] [Accepted: 05/02/2022] [Indexed: 11/09/2022]
Abstract
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.
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Affiliation(s)
- Neha Kaushal
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala, Punjab, India
| | - Sahil Jain
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala, Punjab, India.,University Institute of Biotechnology, Chandigarh University, Mohali, India
| | - Manoj Baranwal
- Department of Biotechnology, Thapar Institute of Engineering and Technology, Patiala, Punjab, India
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Gong W, Pan C, Cheng P, Wang J, Zhao G, Wu X. Peptide-Based Vaccines for Tuberculosis. Front Immunol 2022; 13:830497. [PMID: 35173740 PMCID: PMC8841753 DOI: 10.3389/fimmu.2022.830497] [Citation(s) in RCA: 34] [Impact Index Per Article: 11.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 01/10/2022] [Indexed: 12/12/2022] Open
Abstract
Tuberculosis (TB) is an infectious disease caused by Mycobacterium tuberculosis. As a result of the coronavirus disease 2019 (COVID-19) pandemic, the global TB mortality rate in 2020 is rising, making TB prevention and control more challenging. Vaccination has been considered the best approach to reduce the TB burden. Unfortunately, BCG, the only TB vaccine currently approved for use, offers some protection against childhood TB but is less effective in adults. Therefore, it is urgent to develop new TB vaccines that are more effective than BCG. Accumulating data indicated that peptides or epitopes play essential roles in bridging innate and adaptive immunity and triggering adaptive immunity. Furthermore, innovations in bioinformatics, immunoinformatics, synthetic technologies, new materials, and transgenic animal models have put wings on the research of peptide-based vaccines for TB. Hence, this review seeks to give an overview of current tools that can be used to design a peptide-based vaccine, the research status of peptide-based vaccines for TB, protein-based bacterial vaccine delivery systems, and animal models for the peptide-based vaccines. These explorations will provide approaches and strategies for developing safer and more effective peptide-based vaccines and contribute to achieving the WHO's End TB Strategy.
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Affiliation(s)
- Wenping Gong
- Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, The 8th Medical Center of PLA General Hospital, Beijing, China
| | - Chao Pan
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Biotechnology, Beijing, China
| | - Peng Cheng
- Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, The 8th Medical Center of PLA General Hospital, Beijing, China
- Hebei North University, Zhangjiakou City, China
| | - Jie Wang
- Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, The 8th Medical Center of PLA General Hospital, Beijing, China
| | - Guangyu Zhao
- State Key Laboratory of Pathogen and Biosecurity, Beijing Institute of Microbiology and Epidemiology, Beijing, China
| | - Xueqiong Wu
- Tuberculosis Prevention and Control Key Laboratory/Beijing Key Laboratory of New Techniques of Tuberculosis Diagnosis and Treatment, Senior Department of Tuberculosis, The 8th Medical Center of PLA General Hospital, Beijing, China
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Montes-Grajales D, Olivero-Verbel J. Bioinformatics Prediction of SARS-CoV-2 Epitopes as Vaccine Candidates for the Colombian Population. Vaccines (Basel) 2021; 9:vaccines9070797. [PMID: 34358213 PMCID: PMC8310250 DOI: 10.3390/vaccines9070797] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2021] [Revised: 07/10/2021] [Accepted: 07/13/2021] [Indexed: 12/23/2022] Open
Abstract
Coronavirus disease (COVID-19) pandemic caused by the coronavirus SARS-CoV-2 represents an enormous challenge to global public health, with thousands of infections and deaths in over 200 countries worldwide. The purpose of this study was to identify SARS-CoV-2 epitopes with potential to interact in silico with the alleles of the human leukocyte antigen class I (HLA I) and class II (HLA II) commonly found in the Colombian population to promote both CD4 and CD8 immune responses against this virus. The generation and evaluation of the peptides in terms of HLA I and HLA II binding, immune response, toxicity and allergenicity were performed by using computer-aided tools, such as NetMHCpan 4.1, NetMHCIIpan 4.0, VaxiJem, ToxinPred and AllerTop. Furthermore, the interaction between the predicted epitopes with HLA I and HLA II proteins frequently found in the Colombian population was studied through molecular docking simulations in AutoDock Vina and interaction analysis in LigPlot+. One of the promising peptides proposed in this study is the HLA I epitope YQPYRVVVL, which displayed an estimated coverage of over 82% and 96% for the Colombian and worldwide population, respectively. These findings could be useful for the design of new epitope-vaccines that include Colombia among their population target.
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Hwang W, Lei W, Katritsis NM, MacMahon M, Chapman K, Han N. Current and prospective computational approaches and challenges for developing COVID-19 vaccines. Adv Drug Deliv Rev 2021; 172:249-274. [PMID: 33561453 PMCID: PMC7871111 DOI: 10.1016/j.addr.2021.02.004] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Revised: 02/01/2021] [Accepted: 02/03/2021] [Indexed: 12/23/2022]
Abstract
SARS-CoV-2, which causes COVID-19, was first identified in humans in late 2019 and is a coronavirus which is zoonotic in origin. As it spread around the world there has been an unprecedented effort in developing effective vaccines. Computational methods can be used to speed up the long and costly process of vaccine development. Antigen selection, epitope prediction, and toxicity and allergenicity prediction are areas in which computational tools have already been applied as part of reverse vaccinology for SARS-CoV-2 vaccine development. However, there is potential for computational methods to assist further. We review approaches which have been used and highlight additional bioinformatic approaches and PK modelling as in silico methods which may be useful for SARS-CoV-2 vaccine design but remain currently unexplored. As more novel viruses with pandemic potential are expected to arise in future, these techniques are not limited to application to SARS-CoV-2 but also useful to rapidly respond to novel emerging viruses.
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Affiliation(s)
- Woochang Hwang
- Milner Therapeutics Institute, University of Cambridge, Cambridge, UK
| | - Winnie Lei
- Milner Therapeutics Institute, University of Cambridge, Cambridge, UK; Department of Surgery, University of Cambridge, Cambridge, UK
| | - Nicholas M Katritsis
- Milner Therapeutics Institute, University of Cambridge, Cambridge, UK; Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge, UK
| | - Méabh MacMahon
- Milner Therapeutics Institute, University of Cambridge, Cambridge, UK; Centre for Therapeutics Discovery, LifeArc, Stevenage, UK
| | - Kathryn Chapman
- Milner Therapeutics Institute, University of Cambridge, Cambridge, UK
| | - Namshik Han
- Milner Therapeutics Institute, University of Cambridge, Cambridge, UK.
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