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Bahadori Z, Shafaghi M, Madanchi H, Ranjbar MM, Shabani AA, Mousavi SF. In silico designing of a novel epitope-based candidate vaccine against Streptococcus pneumoniae with introduction of a new domain of PepO as adjuvant. J Transl Med 2022; 20:389. [PMID: 36059030 PMCID: PMC9440865 DOI: 10.1186/s12967-022-03590-6] [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: 02/14/2022] [Accepted: 08/14/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Streptococcus pneumoniae is the leading reason for invasive diseases including pneumonia and meningitis, and also secondary infections following viral respiratory diseases such as flu and COVID-19. Currently, serotype-dependent vaccines, which have several insufficiency and limitations, are the only way to prevent pneumococcal infections. Hence, it is plain to need an alternative effective strategy for prevention of this organism. Protein-based vaccine involving conserved pneumococcal protein antigens with different roles in virulence could provide an eligible alternative to existing vaccines. METHODS In this study, PspC, PhtD and PsaA antigens from pneumococcus were taken to account to predict B-cell and helper T-cell epitopes, and epitope-rich regions were chosen to build the construct. To enhance the immunogenicity of the epitope-based vaccine, a truncated N-terminal fragment of pneumococcal endopeptidase O (PepO) was used as a potential TLR2/4 agonist which was identified by molecular docking studies. The ultimate construct was consisted of the chosen epitope-rich regions, along with the adjuvant role (truncated N-PepO) and suitable linkers. RESULTS The epitope-based vaccine was assessed as regards physicochemical properties, allergenicity, antigenicity, and toxicity. The 3D structure of the engineered construct was modeled, refined, and validated. Molecular docking and simulation of molecular dynamics (MD) indicated the proper and stable interactions between the vaccine and TLR2/4 throughout the simulation periods. CONCLUSIONS For the first time this work presents a novel vaccine consisting of epitopes of PspC, PhtD, and PsaA antigens which is adjuvanted with a new truncated domain of PepO. The computational outcomes revealed that the suggested vaccine could be deemed an efficient therapeutic vaccine for S. pneumoniae; nevertheless, in vitro and in vivo examinations should be performed to prove the potency of the candidate vaccine.
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Affiliation(s)
- Zohreh Bahadori
- Department of Medical Biotechnology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran.,Research Center of Biotechnology, Semnan University of Medical Sciences, Semnan, Iran.,Department of Bacteriology, Pasteur Institute of Iran, Tehran, Iran
| | - Mona Shafaghi
- Department of Medical Biotechnology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran.,Research Center of Biotechnology, Semnan University of Medical Sciences, Semnan, Iran.,Department of Bacteriology, Pasteur Institute of Iran, Tehran, Iran
| | - Hamid Madanchi
- Department of Medical Biotechnology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran.,Research Center of Biotechnology, Semnan University of Medical Sciences, Semnan, Iran.,Drug Design and Bioinformatics Unit, Department of Medical Biotechnology, Biotechnology Research Center, Pasteur Institute of Iran, Tehran, Iran
| | - Mohammad Mehdi Ranjbar
- Agricultural Research, Education, and Extension Organization (AREEO), Razi Vaccine and Serum Research Institute, Karaj, Iran
| | - Ali Akbar Shabani
- Department of Medical Biotechnology, Faculty of Medicine, Semnan University of Medical Sciences, Semnan, Iran. .,Research Center of Biotechnology, Semnan University of Medical Sciences, Semnan, Iran.
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Doytchinova IA, Flower DR. In silico prediction of cancer immunogens: current state of the art. BMC Immunol 2018; 19:11. [PMID: 29544447 PMCID: PMC5856276 DOI: 10.1186/s12865-018-0248-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Accepted: 03/06/2018] [Indexed: 01/22/2023] Open
Abstract
Cancer kills 8 million annually worldwide. Although survival rates in prevalent cancers continue to increase, many cancers have no effective treatment, prompting the search for new and improved protocols. Immunotherapy is a new and exciting addition to the anti-cancer arsenal. The successful and accurate identification of aberrant host proteins acting as antigens for vaccination and immunotherapy is a key aspiration for both experimental and computational research. Here we describe key elements of in silico prediction, including databases of cancer antigens and bleeding-edge methodology for their prediction. We also highlight the role dendritic cell vaccines can play and how they can act as delivery mechanisms for epitope ensemble vaccines. Immunoinformatics can help streamline the discovery and utility of Cancer Immunogens.
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Affiliation(s)
- Irini A. Doytchinova
- Faculty of Pharmacy, Medical University of Sofia, 2 Dunav st, 1000 Sofia, Bulgaria
| | - Darren R. Flower
- School of Life and Health Sciences, Aston University, Aston Triangle, Birmingham, B4 7ET UK
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Tambunan USF, Sipahutar FRP, Parikesit AA, Kerami D. Vaccine Design for H5N1 Based on B- and T-cell Epitope Predictions. Bioinform Biol Insights 2016; 10:27-35. [PMID: 27147821 PMCID: PMC4852757 DOI: 10.4137/bbi.s38378] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2015] [Revised: 03/10/2016] [Accepted: 03/16/2016] [Indexed: 12/11/2022] Open
Abstract
From 2003 to 2013, Indonesia had the highest number of avian influenza A cases in humans, with 192 cases and 160 fatalities. Avian influenza is caused by influenza virus type A, such as subtype H5N1. This virus has two glycoproteins: hemagglutinin and neuraminidase, which will become the primary target to be neutralized by vaccine. Vaccine is the most effective immunologic intervention. In this study, we use the epitope-based vaccine design from hemagglutinin and neuraminidase of H5N1 Indonesian strain virus by using immunoinformatics approach in order to predict the binding of B-cell and T-cell epitopes (class I and class II human leukocyte antigen [HLA]). BCPREDS was used to predict the B-cell epitope. Propred, Propred I, netMHCpan, and netMHCIIpan were used to predict the T-cell epitope. Two B-cell epitopes of hemagglutinin candidates and one B-cell epitope of neuraminidase candidates were obtained to bind T-cell CD4(+) (class II HLA), and also five T-cell epitope hemagglutinin and four T-cell epitope neuraminidase were obtained to bind T-cell CD8(+) (class I HLA). The visualization of epitopes was done using MOE 2008.10. It shows that the binding affinity of epitope-HLA was based on minimum binding free energy (ΔG binding). Based on this result, visualization, and dynamic simulation, four hemagglutinin epitopes (MEKIVLLLA, CPYLGSPSF, KCQTPMGAI, and IGTSTLNQR) and two neuraminidase epitopes (NPNQKIITI and CYPDAGEIT) were computed as having the best binding affinity from HLA ligand. The results mentioned above are from in silico experiments and need to be validated using wet experiment.
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Affiliation(s)
- Usman Sumo Friend Tambunan
- Bioinformatics Group, Department of Chemistry, Faculty of Mathematics and Natural Science, University of Indonesia, Depok, Indonesia
| | - Feimmy Ruth Pratiwi Sipahutar
- Bioinformatics Group, Department of Chemistry, Faculty of Mathematics and Natural Science, University of Indonesia, Depok, Indonesia
| | - Arli Aditya Parikesit
- Bioinformatics Group, Department of Chemistry, Faculty of Mathematics and Natural Science, University of Indonesia, Depok, Indonesia
| | - Djati Kerami
- Mathematics Computation Group, Department of Mathematics, Faculty of Mathematics and Natural Science, University of Indonesia, Depok, Indonesia
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Dimitrov I, Atanasova M, Patronov A, Flower DR, Doytchinova I. A Cohesive and Integrated Platform for Immunogenicity Prediction. Methods Mol Biol 2016; 1404:761-770. [PMID: 27076336 DOI: 10.1007/978-1-4939-3389-1_50] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
In silico methods for immunogenicity prediction mine the enormous quantity of data arising from deciphered genomes and proteomes to identify immunogenic proteins. While high and productive immunogenicity is essential for vaccines, therapeutic proteins and monoclonal antibodies should be minimally immunogenic. Here, we present a cohesive platform for immunogenicity and MHC class I and/or II binding affinity prediction. The platform integrates three quasi-independent modular servers: VaxiJen, EpiJen, and EpiTOP. VaxiJen (http://www.ddg-pharmfac.net/vaxijen) predicts immunogenicity of proteins of different origin; EpiJen (http://www.ddg-pharmfac.net/epijen) predicts peptide binding to MHC class I proteins; and EpiTOP (http://www.ddg-pharmfac.net/epitop) predicts peptide binding to MHC class II proteins. The platform is freely accessible and user-friendly. The protocol for immunogenicity prediction is demonstrated by selecting immunogenic proteins from Mycobacterium tuberculosis and predicting how the peptide epitopes within them bind to MHC class I and class II proteins.
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Affiliation(s)
- Ivan Dimitrov
- School of Pharmacy, Medical University of Sofia, Sofia, 1000, Bulgaria
| | | | - Atanas Patronov
- Center for Integrated Protein Science Munich (CIPSM), Technical University of Munich, Freising-Weihenstephan, 85354, Germany.,Department of Life Sciences, Technical University of Munich, Freising-Weihenstephan, 85354, Germany
| | - Darren R Flower
- School of Life and Health Sciences, Aston University, Birmingham, B4 7ET, UK
| | - Irini Doytchinova
- School of Pharmacy, Medical University of Sofia, Sofia, 1000, Bulgaria.
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Valdivia-Olarte H, Requena D, Ramirez M, Saravia LE, Izquierdo R, Falconi-Agapito F, Zavaleta M, Best I, Fernández-Díaz M, Zimic M. Design of a predicted MHC restricted short peptide immunodiagnostic and vaccine candidate for Fowl adenovirus C in chicken infection. Bioinformation 2015; 11:460-5. [PMID: 26664030 PMCID: PMC4658644 DOI: 10.6026/97320630011460] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/18/2015] [Accepted: 10/18/2015] [Indexed: 11/23/2022] Open
Abstract
Fowl adenoviruses (FAdVs) are the ethiologic agents of multiple pathologies in chicken. There are five different species of FAdVs grouped as FAdV-A, FAdV-B, FAdV-C, FAdV-D, and FAdV-E. It is of interest to develop immunodiagnostics and vaccine candidate for Peruvian FAdV-C in chicken infection using MHC restricted short peptide candidates. We sequenced the complete genome of one FAdV strain isolated from a chicken of a local farm. A total of 44 protein coding genes were identified in each genome. We sequenced twelve Cobb chicken MHC alleles from animals of different farms in the central coast of Peru, and subsequently determined three optimal human MHC-I and four optimal human MHC-II substitute alleles for MHC-peptide prediction. The potential MHC restricted short peptide epitope-like candidates were predicted using human specific (with determined suitable chicken substitutes) NetMHC MHC-peptide prediction model with web server features from all the FAdV genomes available. FAdV specific peptides with calculated binding values to known substituted chicken MHC-I and MHC-II were further filtered for diagnostics and potential vaccine epitopes. Promiscuity to the 3/4 optimal human MHC-I/II alleles and conservation among the available FAdV genomes was considered in this analysis. The localization on the surface of the protein was considered for class II predicted peptides. Thus, a set of class I and class II specific peptides from FAdV were reported in this study. Hence, a multiepitopic protein was built with these peptides, and subsequently tested to confirm the production of specific antibodies in chicken.
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Affiliation(s)
- Hugo Valdivia-Olarte
- Farvet s.A.C. Carretera Panamericana Sur N° 766 Km 198.5, Chincha Alta. Ica – Peru
- Laboratorio de Bioinformática y Biologáa
Molecular, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofáa, Universidad Peruana Cayetano Heredia,
Av. Honorio Delgado 430, San Martin de Porres. Lima – Peru
| | - David Requena
- Farvet s.A.C. Carretera Panamericana Sur N° 766 Km 198.5, Chincha Alta. Ica – Peru
- Laboratorio de Bioinformática y Biologáa
Molecular, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofáa, Universidad Peruana Cayetano Heredia,
Av. Honorio Delgado 430, San Martin de Porres. Lima – Peru
| | - Manuel Ramirez
- Farvet s.A.C. Carretera Panamericana Sur N° 766 Km 198.5, Chincha Alta. Ica – Peru
- Laboratorio de Bioinformática y Biologáa
Molecular, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofáa, Universidad Peruana Cayetano Heredia,
Av. Honorio Delgado 430, San Martin de Porres. Lima – Peru
| | - Luis E Saravia
- Farvet s.A.C. Carretera Panamericana Sur N° 766 Km 198.5, Chincha Alta. Ica – Peru
| | - Ray Izquierdo
- Farvet s.A.C. Carretera Panamericana Sur N° 766 Km 198.5, Chincha Alta. Ica – Peru
| | | | - Milagros Zavaleta
- Farvet s.A.C. Carretera Panamericana Sur N° 766 Km 198.5, Chincha Alta. Ica – Peru
| | - Iván Best
- Farvet s.A.C. Carretera Panamericana Sur N° 766 Km 198.5, Chincha Alta. Ica – Peru
| | | | - Mirko Zimic
- Farvet s.A.C. Carretera Panamericana Sur N° 766 Km 198.5, Chincha Alta. Ica – Peru
- Laboratorio de Bioinformática y Biologáa
Molecular, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias y Filosofáa, Universidad Peruana Cayetano Heredia,
Av. Honorio Delgado 430, San Martin de Porres. Lima – Peru
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Jafarpour S, Ayat H, Ahadi AM. Design and Antigenic Epitopes Prediction of a New Trial Recombinant Multiepitopic Rotaviral Vaccine: In Silico Analyses. Viral Immunol 2015; 28:325-30. [PMID: 25965449 PMCID: PMC4507124 DOI: 10.1089/vim.2014.0152] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Rotavirus is the major etiologic factor of severe diarrheal disease. Natural infection provides protection against subsequent rotavirus infection and diarrhea. This research presents a new vaccine designed based on computational models. In this study, three types of epitopes are considered-linear, conformational, and combinational-in a proposed model protein. Several studies on rotavirus vaccines have shown that VP6 and VP4 proteins are good candidates for vaccine production. In the present study, a fusion protein was designed as a new generation of rotavirus vaccines by bioinformatics analyses. This model-based study using ABCpred, BCPREDS, Bcepred, and Ellipro web servers showed that the peptide presented in this article has the necessary properties to act as a vaccine. Prediction of linear B-cell epitopes of peptides is helpful to investigate whether these peptides are able to activate humoral immunity.
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Affiliation(s)
- Sima Jafarpour
- Department of Genetics, Faculty of Science, Shahrekord University , Shahrekord, Iran
| | - Hoda Ayat
- Department of Genetics, Faculty of Science, Shahrekord University , Shahrekord, Iran
| | - Ali Mohammad Ahadi
- Department of Genetics, Faculty of Science, Shahrekord University , Shahrekord, Iran
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Abstract
Urinary tract infections (UTIs) are among the most common of bacterial infections in humans. Although a number of Gram-negative bacteria can cause UTIs, most cases are due to infection by uropathogenic E. coli (UPEC). Genomic studies have shown that UPEC encode a number of specialized activities that allow the bacteria to initiate and maintain infections in the environment of the urinary tract. Proteomic analyses have complemented the genomic data and have documented differential patterns of protein synthesis for bacteria growing ex vivo in human urine or recovered directly from the urinary tracts of infected mice. These studies provide valuable insights into the molecular basis of UPEC pathogenesis and have aided the identification of putative vaccine targets. Despite the substantial progress that has been achieved, many future challenges remain in the application of proteomics to provide a comprehensive view of bacterial pathogenesis in both acute and chronic UTIs.
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Affiliation(s)
- Phillip Cash
- Division of Applied Medicine, University of Aberdeen, Foresterhill, Aberdeen AB32 6QX, Scotland
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Prabdial-Sing N, Puren AJ, Bowyer SM. Sequence-based in silico analysis of well studied hepatitis C virus epitopes and their variants in other genotypes (particularly genotype 5a) against South African human leukocyte antigen backgrounds. BMC Immunol 2012; 13:67. [PMID: 23227878 PMCID: PMC3552980 DOI: 10.1186/1471-2172-13-67] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2012] [Accepted: 11/30/2012] [Indexed: 02/07/2023] Open
Abstract
Background Host genetics influence the outcome of HCV disease. HCV is also highly mutable and escapes host immunity. HCV genotypes are geographically distributed and HCV subtypes have been shown to have distinct repertoires of HLA-restricted viral epitopes which explains the lack of cross protection across genotypes observed in some studies. Despite this, immune databases and putative epitope vaccines concentrate almost exclusively on HCV genotype 1 class I-epitopes restricted by the HLA-A*02 allele. While both genotype and allele predominate in developed countries, we hypothesise that HCV variation and population genetics will affect the efficacy of proposed epitope vaccines in South Africa. This in silico study investigates HCV viral variability within well-studied epitopes identified in genotype 1 and uses algorithms to predict the immunogenicity of their variants from other less studied genotypes and thus rate the most promising vaccine candidates for the South African population. Six class I- and seven class II- restricted epitope sequences within the core, NS3, NS4B and NS5B regions were compared across the six HCV genotypes using local genotype 5a sequence data together with global data. Common HLA alleles in the South African population are A30:01, A02:01, B58:02, B07:02; DRB1*13:01 and DRB1*03:01. Epitope binding to 13 class I- and 8 class –II alleles were described using web-based prediction servers, Immune Epitope Database, (IEDB) and Propred. Online population coverage tools were used to assess vaccine efficacy. Results Despite the homogeneity of genotype 1 and genotype 5 over the epitopes, there was limited promiscuity to local HLA-alleles.Host differences will make a putative vaccine less effective in South Africa. Of the 6 well-characterized class I- epitopes, only 2 class I- epitopes were promiscuous and 3 of the 7 class-II epitopes were better conserved and promiscuous. By fine tuning the putative vaccine using an optimal cocktail of genotype 1 and 5a epitopes and local HLA data, the coverage was raised from 65.85% to 91.87% in South African Blacks. Conclusion While in vivo and in vitro studies are needed to confirm immunogenic epitopes, in silico HCV epitope vaccine design which takes into account HCV variation and host allele frequency will maximize population coverage in different ethnic groups.
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Affiliation(s)
- Nishi Prabdial-Sing
- Specialized Molecular Diagnostics, Hepatitis Unit, National Institute for Communicable Diseases, National Health Laboratory Services, Johannesburg, South Africa.
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