In-silico design of Multi-Epitope Vaccine Against Glioblastoma Using Tumor-Associated Antigens and TLR Agonist Adjuvants

Abstract Glioblastoma multiforme (GBM) is the most severe and chemo-resistant primary brain tumor in adult patients, which is accompanied by high molecular heterogeneity, immunosuppressive microenvironment of the tumor, and ultimately poor prognosis. Traditional treatment plans have shown to be only marginally effective, so we introduced this in-silico approach for developing highly efficient vaccine candidate. An HSPA1A that has high antigenic cross reactivity, extracellular localization, and have no reported allergic reactions was chosen as a chaperone protein. Powerful B-cell, MHC class I and MHC class II epitopes were identified and optimally combined into a single construct using proper linkers and adjuvant sequences thus ensuring high immunogenicity, stability and dual innate receptor stimulation. Physicochemical evaluations also indicated desirable solubility, thermal, and expression outlook aspects. A 3D conformation was obtained via structural modeling on AlphaFold 3 and rigorous validation to obtain a compact and stereochemically robust structure. Docking done with TLR-4 showed good docking activity, and after that, a molecular dynamics simulation was done for 500 ns, which further showed stable protein-ligand conjugates and negligible distortion. Simulated immune responses were predicted to be high at the humoral and T cell levels with the anticipation of memory T cell and B cell formation and high IFN- Y and IL 2. Taken together all these results, the multi-epitope vaccine proposed shows excellent potential to be a risk-free, targeted, and broadly effective immunotherapy tool against glioblastoma and, therefore, must be pursued into limiting preclinical and experimental testing.