SEARCHOTHERinfectious disease, immunology

other·infectious disease, immunology, biomedical research, preclinical research·PMC10540849

Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach

Frontiers in Immunology · 10 authors, 6 centres

AI SUMMARY

FIDELITY 100%

This summary was generated by AI from a single paper. It has not been reviewed by a clinician and is not clinical advice. Verify against the source before acting on it.

AGENT 01 · STRUCTURED SUMMARY

TRACE TO SOURCE

“

TL;DR

The top-ranked vaccine model (V1) showed stable binding to human TLR4 and was predicted to elicit both humoral and cell-mediated immune responses.

Full summary

689 CHARS

Five extracellular parasite proteins were prioritized, and overlapping MHC-I, MHC-II, and linear B-cell epitopes were predicted based on antigenicity, non-allergenicity, and non-toxicity. Four multi-epitope constructs incorporating adjuvant sequences were designed. The vaccine model V1 demonstrated the strongest predicted binding affinity to human TLR4 via molecular docking and molecular dynamics simulations, suggesting stable interaction. In silico immune simulations predicted that V1 could stimulate helper T cells, memory B and T cells, and strong Ig production. The work provides a theoretical framework for future preclinical development but does not report experimental testing.

STUDY TYPE

other

SPECIALTY

infectious disease

SUMMARISED BY

AI pipeline

FIDELITY CHECK

100% · A

ORIGINAL PAPER

PMC10540849

Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach

Frontiers in Immunology

READ THE FULL PAPER

ABSTRACT

Leishmania tropica is a vector-borne parasitic protozoa that is the leading cause of leishmaniasis throughout the global tropics and subtropics. L. tropica is a multidrug-resistant parasite with a diverse set of serological, biochemical, and genomic features. There are currently no particular vaccines available to combat leishmaniasis. The present study prioritized potential vaccine candidate proteins of L. tropica using subtractive proteomics and vaccinomics approaches. These vaccine candidate proteins were downstream analyzed to predict B- and T-cell epitopes based on high antigenicity, non-allergenic, and non-toxic characteristics. The top-ranked overlapping MHC-I, MHC-II, and linear B-cell epitopes were prioritized for model vaccine designing. The lead epitopes were linked together by suitable linker sequences to design multi-epitope constructs. Immunogenic adjuvant sequences were incorporated at the N-terminus of the model vaccine constructs to enhance their immunological potential. Among different combinations of constructs, four vaccine designs were selected based on their physicochemical and immunological features. The tertiary structure models of the designed vaccine constructs were predicted and verified. The molecular docking and molecular dynamic (MD) simulation analyses indicated that the vaccine design V1 demonstrated robust and stable molecular interactions with toll-like receptor 4 (TLR4). The top-ranked vaccine construct model-IV demonstrated significant expressive capability in the E. coli expression system during in-silico restriction cloning analysis. The results of the present study are intriguing; nevertheless, experimental bioassays are required to validate the efficacy of the predicted model chimeric vaccine.

CITATION EXPORT

Sara Aiman, Abbas Ahmad, Azmat Ali Khan et al.. Vaccinomics-based next-generation multi-epitope chimeric vaccine models prediction against Leishmania tropica - a hierarchical subtractive proteomics and immunoinformatics approach. Frontiers in Immunology. (2023). https://doi.org/10.3389/fimmu.2023.1259612

AUTHORS

10 · 6 CENTRES

Sara Aiman, Abbas Ahmad, Azmat Ali Khan, Amer M. Alanazi, Abdus Samad, Syed Luqman Ali, Chunhua Li, Zhiguang Ren, Asifullah Khan, Saadullah Khattak

1 Faculty of Environmental and Life Sciences, Beijing University of Technology, Beijing, China
2 Department of Biotechnology, Abdul Wali Khan University Mardan, Mardan, Pakistan
3 Pharmaceutical Biotechnology Laboratory, Department of Pharmaceutical Chemistry, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
4 Department of Biochemistry, Abdul Wali Khan University Mardan (AWKUM), Mardan, Pakistan
5 The First Affiliated Hospital, Henan University, Kaifeng, China
6 Henan International Joint Laboratory for Nuclear Protein Regulation, School of Basic Medical Sciences, Henan University, Kaifeng, Henan, China