Multi‐Epitope Vaccine Design Against <i>Leishmania donovani</i> : An Immunoinformatic Based In Silico Approach

Leishmaniasis, caused by Leishmania donovani, remains a major neglected tropical disease (NTD) with limited therapeutic options and the absence of a universally effective vaccine. Multi-epitope vaccines offer a promising strategy for combating this intracellular parasite by stimulating a robust and specific immune response. In this study, an immunoinformatics-driven, in silico reverse vaccinology approach was utilized to design a multi-epitope vaccine targeting key surface-exposed proteins of L. donovani, namely C-type lectin, Proteophosphoglycan (PPG4), Hydrophilic Acylated Surface Protein (HASP), Legume-like Lectin (LLL), and Kinetoplastid Membrane Protein (KMP-11). These proteins are implicated in essential processes such as parasite survival, immune modulation, and host-pathogen interactions, making them prime candidates for vaccine development. A comprehensive analysis was conducted to identify and screen B-cell and T-cell (MHC-I and MHC-II) epitopes for immunogenicity, antigenicity, and population coverage. Multi-epitope vaccines, incorporating individual proteins or chimeric constructs, were developed with IFN-gamma as an adjuvant. The vaccine constructs were prioritized based on factors such as IC<sub>50</sub> values and immunogenic potential. Subsequently, the selected epitopes were analyzed for physicochemical properties, and secondary and tertiary structural predictions were made and validated. Molecular docking simulations were employed to examine the interaction of the vaccine constructs with immune receptors, ensuring optimal immune system activation. Based on the molecular docking score, the vaccine candidates were screened and top four constructs (vaccines based on C-type lectin, LLL, PPG and chimeric vaccine; -1048.9, -1025.8, -1291.8, and -852.1 Kcal/mol respectively) were processed through immunogenic simulation. This in silico analysis indicates that lectins are highly effective vaccine candidates. Further, top two constructs, based on the immunogenic simulations, underwent molecular dynamics simulations. In the end, the final constructs were computationally cloned in pET28a vector. This study underscores the potential of multi-epitope vaccines as a cost-effective and efficient strategy for addressing L. donovani infections, providing a foundation for subsequent experimental validation and clinical trial development.

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Journal
Proteins Structure Function and Bioinformatics
Published
2025-12-30
DOI
https://doi.org/10.1002/prot.70102
Primary Topic
vaccines and immunoinformatics approaches
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article
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article

Multi‐Epitope Vaccine Design Against Leishmania donovani : An Immunoinformatic Based In Silico Approach

Manisha Pritam, Sumit Govil, Aviral Kaushik, Radhey Shyam Kaushal
Proteins Structure Function and Bioinformatics
vaccines and immunoinformatics approaches
article

Multi‐Epitope Vaccine Design Against Leishmania donovani : An Immunoinformatic Based In Silico Approach

Manisha Pritam, Sumit Govil, Aviral Kaushik, Radhey Shyam Kaushal
article en

Abstract

Leishmaniasis, caused by Leishmania donovani, remains a major neglected tropical disease (NTD) with limited therapeutic options and the absence of a universally effective vaccine. Multi-epitope vaccines offer a promising strategy for combating this intracellular parasite by stimulating a robust and specific immune response. In this study, an immunoinformatics-driven, in silico reverse vaccinology approach was utilized to design a multi-epitope vaccine targeting key surface-exposed proteins of L. donovani, namely C-type lectin, Proteophosphoglycan (PPG4), Hydrophilic Acylated Surface Protein (HASP), Legume-like Lectin (LLL), and Kinetoplastid Membrane Protein (KMP-11). These proteins are implicated in essential processes such as parasite survival, immune modulation, and host-pathogen interactions, making them prime candidates for vaccine development. A comprehensive analysis was conducted to identify and screen B-cell and T-cell (MHC-I and MHC-II) epitopes for immunogenicity, antigenicity, and population coverage. Multi-epitope vaccines, incorporating individual proteins or chimeric constructs, were developed with IFN-gamma as an adjuvant. The vaccine constructs were prioritized based on factors such as IC<sub>50</sub> values and immunogenic potential. Subsequently, the selected epitopes were analyzed for physicochemical properties, and secondary and tertiary structural predictions were made and validated. Molecular docking simulations were employed to examine the interaction of the vaccine constructs with immune receptors, ensuring optimal immune system activation. Based on the molecular docking score, the vaccine candidates were screened and top four constructs (vaccines based on C-type lectin, LLL, PPG and chimeric vaccine; -1048.9, -1025.8, -1291.8, and -852.1 Kcal/mol respectively) were processed through immunogenic simulation. This in silico analysis indicates that lectins are highly effective vaccine candidates. Further, top two constructs, based on the immunogenic simulations, underwent molecular dynamics simulations. In the end, the final constructs were computationally cloned in pET28a vector. This study underscores the potential of multi-epitope vaccines as a cost-effective and efficient strategy for addressing L. donovani infections, providing a foundation for subsequent experimental validation and clinical trial development.

Proteins Structure Function and Bioinformatics
National Institutes of Health (US), Parul University (IN), Jaipur National University (IN)
Openalex Percentile: Top 35%
vaccines and immunoinformatics approaches
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