Designing Lsa46 Based Multi-Epitope Peptide Vaccine Against Leptospirosis: Immunoinformatic Approach

Authors

  • Junaida M. Ibrahim Department of Computational Biology & Bioinformatics, University of Kerala, India https://orcid.org/0000-0003-1981-8489
  • Padikara K. Satheeshkumar Department of Botany, Institute of Science, Banaras Hindu University, India https://orcid.org/0000-0002-2031-9049
  • Achuthsankar S. Nair Department of Computational Biology & Bioinformatics, University of Kerala, India https://orcid.org/0000-0003-0479-0743
  • Oommen V. Oommen Department of Computational Biology & Bioinformatics, University of Kerala, India
  • Perumana R. Sudhakaran Department of Computational Biology & Bioinformatics, University of Kerala, India https://orcid.org/0000-0002-3980-612X

DOI:

https://doi.org/10.47852/bonviewMEDIN42022655

Keywords:

leptospirosis, Lsa46, multi-epitope, peptide vaccine, immune simulation

Abstract

Leptospirosis represents a significant global public health problem due to its epidemiological impact, complex pathogen biology, and diverse clinical manifestations. Effective treatment, management, and preventive measures, including vaccination, are vital for addressing this disease. Lsa46, a surface-exposed outer membrane protein in leptospires, plays a crucial role in pathogenesis. In this study, we utilized multiple epitopes predicted from Lsa46, validated in previous study, to design a potential vaccine candidate construct. The antigenicity, allergenicity, autoimmunity, population coverage, immune simulation, molecular interactions etc. were assessed using various computational tools. 3D structure modeling revealed a stable and high quality model for epitope constructs. Immune simulation confirmed a robust immune response induced by the Designer Epitope construct, including IgG, IgM, MHCI, MHCII, cytokines, and interleukins production. Interaction analysis with immune cells and receptors, such as TCRαβ, TCRγδ, and TLRs, provided insights into the epitope construct's potential immunogenic response. Docking studies with TLR2 and TLR4 indicated their interaction with the epitope, suggesting their involvement in the immune response against leptospirosis. Further experimental validations are required to confirm these prediction results.

 

Received: 21 February 2024 | Revised: 6 May 2024 | Accepted: 20 June 2024

 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.

 

Data Availability Statement

All the data discussed have been included in the manuscript and with its supplementary figures and tables.


Author Biography

Junaida M. Ibrahim, Department of Computational Biology & Bioinformatics, University of Kerala, India

I am a research scholar in the Dept. of Computational Biology and Bioinformatics, University of Kerala. I had my M.Phil in CADD and M.Sc in Biotechnology

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Published

2024-06-27

How to Cite

Ibrahim, J. M. ., Satheeshkumar, P. K. . ., Nair, A. S. ., Oommen, O. V. ., & Sudhakaran, P. R. . (2024). Designing Lsa46 Based Multi-Epitope Peptide Vaccine Against Leptospirosis: Immunoinformatic Approach. Medinformatics. https://doi.org/10.47852/bonviewMEDIN42022655

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Research Articles