In Silico Immunoinformatics Design and Evaluation of a Protein Based Vaccine Candidate Against Type 1 Diabetes Mellitus
DOI:
https://doi.org/10.61919/er8vkf50Keywords:
Type 1 diabetes; CTB-GM1; in silico vaccine; epitope prediction; molecular docking; immune simulation.Abstract
Background: Type 1 diabetes mellitus (T1DM) results from autoimmune destruction of pancreatic β-cells, and no licensed vaccine currently prevents or halts this process. Computational immunology offers a rapid approach for identifying tolerogenic antigen combinations that may modulate autoimmune responses. Objective: To design and evaluate an in silico multi-epitope vaccine candidate incorporating the CTB–GM1 system to promote antigen-specific immune tolerance in T1DM. Methods: Protein sequences were retrieved from NCBI and assessed using ProtParam, VaxiJen, AllerTOP, ToxinPred, and SolPro. T- and B-cell epitopes were predicted through IEDB, filtered by antigenicity, allergenicity, toxicity, and population coverage, and assembled using appropriate linkers and an adjuvant. Structural modelling was performed using I-TASSER, with validation by Ramachandran and ERRAT analyses. Molecular docking with GM1 was conducted via ClusPro, and immune responses were simulated using C-IMMSIM. Results: The final construct incorporated five MHC-I, five MHC-II, and four B-cell epitopes and demonstrated favourable predicted antigenicity (VaxiJen score 0.62), non-allergenicity, and non-toxicity. Structural modelling indicated a stable conformation (ERRAT >95%). Docking predicted strong interaction with GM1 (best score –1050.7). Immune simulations suggested a Th2-leaning profile with increased IL-4, IL-5, IL-13 and generation of memory subsets; however, these findings are theoretical. Conclusion: This CTB–GM1 multi-epitope construct shows promising computational characteristics, but all findings are predictive only and require comprehensive in vitro, in vivo, and clinical validation before any therapeutic relevance can be established.
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