Designing and immuno-informatics evaluation of a multi-epitope vaccine targeting lipoprotein A-4'-phosphatase (LpxF) for infection control.
1/5 보강
[INTRODUCTION] The WHO has classified as a category 1 carcinogen and a major causative agent of gastrointestinal ulcers, gastric adenocarcinoma, and gastric lymphoma.
APA
Gollapalli P, Gnanasekaran TS (2026). Designing and immuno-informatics evaluation of a multi-epitope vaccine targeting lipoprotein A-4'-phosphatase (LpxF) for infection control.. Frontiers in bioinformatics, 6, 1779654. https://doi.org/10.3389/fbinf.2026.1779654
MLA
Gollapalli P, et al.. "Designing and immuno-informatics evaluation of a multi-epitope vaccine targeting lipoprotein A-4'-phosphatase (LpxF) for infection control.." Frontiers in bioinformatics, vol. 6, 2026, pp. 1779654.
PMID
41929239
Abstract
[INTRODUCTION] The WHO has classified as a category 1 carcinogen and a major causative agent of gastrointestinal ulcers, gastric adenocarcinoma, and gastric lymphoma. While antibiotics and proton pump inhibitors are effective treatments, they are associated with risks of reinfection, patient dissatisfaction, and increasing antibiotic resistance. Due to the bacterium's extremophile nature, designing potent drugs remains challenging. Therefore, an effective vaccine represents the most suitable prophylactic option for mass administration.
[METHODS] A subtractive proteomics pipeline was employed to identify appropriate antigenic proteins for the development of a multi-epitope vaccine (MEV). Lipid A-4'phosphatase (LpxF) was selected as a potential target. Various bioinformatics and immunoinformatics databases were used to predict T and B cell epitopes. A 757 amino acid MEV was then constructed by combining eight cytotoxic T cell (CTL), nineteen helper T cell (HTL), and fourteen linear B cell (LBL) epitopes using appropriate adjuvants and linkers. The vaccine's interaction with human immunological receptors (TLR2, TLR4, and TLR5) was evaluated via molecular docking and molecular dynamics (MD) simulations. Finally, the pET-28a(+) plasmid vector from Escherichia coli was used to assess expression capabilities.
[RESULTS] The proposed MEV was found to be non-allergic, stable, and highly antigenic for human use. Computational simulations, including molecular docking and MD, demonstrated strong binding affinity and stable molecular interactions between the MEV and target immune receptors. In silico cloning results further confirmed the expression potential of the vaccine within the system.
[DISCUSSION] Based on these computational findings, the designed MEV shows significant promise for establishing protective immunity against . The multi-epitope approach addresses the challenges posed by the bacterium's resilient nature. However, while the in silico results are encouraging, further and investigations are required to fully comprehend and validate its immune-protective efficacy in biological systems.
[METHODS] A subtractive proteomics pipeline was employed to identify appropriate antigenic proteins for the development of a multi-epitope vaccine (MEV). Lipid A-4'phosphatase (LpxF) was selected as a potential target. Various bioinformatics and immunoinformatics databases were used to predict T and B cell epitopes. A 757 amino acid MEV was then constructed by combining eight cytotoxic T cell (CTL), nineteen helper T cell (HTL), and fourteen linear B cell (LBL) epitopes using appropriate adjuvants and linkers. The vaccine's interaction with human immunological receptors (TLR2, TLR4, and TLR5) was evaluated via molecular docking and molecular dynamics (MD) simulations. Finally, the pET-28a(+) plasmid vector from Escherichia coli was used to assess expression capabilities.
[RESULTS] The proposed MEV was found to be non-allergic, stable, and highly antigenic for human use. Computational simulations, including molecular docking and MD, demonstrated strong binding affinity and stable molecular interactions between the MEV and target immune receptors. In silico cloning results further confirmed the expression potential of the vaccine within the system.
[DISCUSSION] Based on these computational findings, the designed MEV shows significant promise for establishing protective immunity against . The multi-epitope approach addresses the challenges posed by the bacterium's resilient nature. However, while the in silico results are encouraging, further and investigations are required to fully comprehend and validate its immune-protective efficacy in biological systems.