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Immunoinformatics approaches to explore Helicobacter Pylori proteome (Virulence Factors) to design B and T cell multi-epitope subunit vaccine

مناهج المعلوماتية المناعية لاستكشاف بروتيوم الملوية البوابية (عوامل الفوعة) لتصميم لقاح الوحدة الفرعية متعدد الخلايا البائية والتائية
Authors: Mazhar Khan; Shahzeb Khan; Asim Ali; Hameed Akbar; Abrar Mohammad Sayaf; Abbas Khan; Dong‐Qing Wei;

Immunoinformatics approaches to explore Helicobacter Pylori proteome (Virulence Factors) to design B and T cell multi-epitope subunit vaccine

Abstract

AbstractHelicobacter Pyloriis a known causal agent of gastric malignancies and peptic ulcers. The extremophile nature of this bacterium is protecting it from designing a potent drug against it. Therefore, the use of computational approaches to design antigenic, stable and safe vaccine against this pathogen could help to control the infections associated with it. Therefore, in this study, we used multiple immunoinformatics approaches along with other computational approaches to design a multi-epitopes subunit vaccine againstH.Pylori. A total of 7 CTL and 12 HTL antigenic epitopes based on c-terminal cleavage and MHC binding scores were predicted from the four selected proteins (CagA, OipA, GroEL and cagA). The predicted epitopes were joined by AYY and GPGPG linkers. Β-defensins adjuvant was added to the N-terminus of the vaccine. For validation, immunogenicity, allergenicity and physiochemical analysis were conducted. The designed vaccine is likely antigenic in nature and produced robust and substantial interactions with Toll-like receptors (TLR-2, 4, 5, and 9). The vaccine developed was also subjected to anin silicocloning and immune response prediction model, which verified its efficiency of expression and the immune system provoking response. These analyses indicate that the suggested vaccine may produce particular immune responses againstH. pylori, but laboratory validation is needed to verify the safety and immunogenicity status of the suggested vaccine design.

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United States
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Keywords

Models, Molecular, FOS: Computer and information sciences, Radiology, Nuclear Medicine and Imaging, Proteome, Epitopes, T-Lymphocyte, Prediction of Peptide-MHC Binding Affinity, Gene, Computational biology, Epitopes, Models, Adjuvant, Vaccines, Virulence, B-Lymphocyte, Life Sciences, Immunoinformatics, Bioinformatics Tools, Immunogenicity, CagA, Oncology, Antigen, Bacterial Vaccines, Vaccines, Subunit, Epitopes, B-Lymphocyte, Medicine, Epitope, Subunit, 570, Therapeutic Antibodies: Development, Engineering, and Applications, Virulence Factors, Bioinformatics, Immunology, Microbiology, Article, Role of Fibroblast Activation in Cancer Progression, Biochemistry, Genetics and Molecular Biology, Virology, Health Sciences, Genetics, Humans, Computer Simulation, Amino Acid Sequence, Molecular Biology, Biology, Helicobacter pylori, FOS: Clinical medicine, In silico, Molecular, Computational Biology, Immune system, T-Lymphocyte, Drug Design, FOS: Biological sciences, Reverse vaccinology

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
136
Top 1%
Top 10%
Top 1%
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gold
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