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This study addresses these challenges by computationally designing a novel CTL-based multi-epitope vaccine using experimentally validated epitopes from cancer-testis antigens (NY-ESO-1 and MAGE-A family), which are overexpressed in esophageal squamous cell carcinoma. To the best of our knowledge, this represents one of the most comprehensive in silico investigations for esophageal cancer, uniquely integrating experimentally validated epitopes with advanced immunoinformatics, high-resolution structural modeling, molecular dynamics, and immune simulation strategies. Nine experimentally validated CTL epitopes were retrieved from IEDB and rigorously evaluated for antigenicity (VaxiJen), toxicity (ToxinPred), allergenicity (AllerTOP), and IFN-\u03b3 induction (IFNepitope). A 253-amino-acid multi-epitope construct was assembled with AAY\/EAAAK linkers, PADRE adjuvant, and 5\u00a0S rRNA-derived TLR4 agonist. Physicochemical properties were assessed (ProtParam, SOLpro); secondary\/tertiary structures predicted (SOPMA, trRosetta); and validated (ProSA, Ramachandran). B-cell epitopes were predicted with ElliPro. Molecular docking (ClusPro) with TLR4, 100-ns MD simulations (GROMACS), and MM\/GBSA binding free energy calculations were performed. Immune responses were simulated using C-ImmSim, and population coverage was analyzed via IEDB. The vaccine construct demonstrated excellent stability (instability index 31.16), solubility (0.577), and antigenicity (VaxiJen 0.5734; non-allergenic). It exhibited a predominantly \u03b1-helical structure (64.43%) with high model quality (ProSA Z-score: \u2212\u20096.33). Strong TLR4 binding was confirmed (\u2013910.7\u00a0kJ\/mol, stable RMSD\u2009~\u20090.29\u00a0nm, MM\/GBSA \u2212\u2009110.76\u00a0kcal\/mol). Immune simulations predicted robust IgG\/IgM responses, memory cell formation, and elevated IFN-\u03b3 (&gt;\u20094\u2009\u00d7\u200910\u2075 ng\/mL). Global population coverage reached 50.02%. This novel CTL-based multi-epitope vaccine candidate is stable, immunogenic, and capable of eliciting strong anti-tumor immunity. It provides a promising computational platform for esophageal cancer immunotherapy, warranting experimental validation and clinical translation.<\/jats:p>","DOI":"10.1038\/s41598-026-60801-6","type":"journal-article","created":{"date-parts":[[2026,7,9]],"date-time":"2026-07-09T11:33:09Z","timestamp":1783596789000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["In silico design of novel CTL based multi epitope vaccine for esophageal cancer using immunoinformatics and molecular docking"],"prefix":"10.1038","volume":"16","author":[{"given":"Mingjun","family":"Hu","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoyan","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Deyong","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Juan","family":"Chen","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hai","family":"Zeng","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2026,7,9]]},"reference":[{"issue":"4","key":"60801_CR1","first-page":"e4084","volume":"23","author":"H Cao","year":"2025","unstructured":"Cao, H. & Ding, F. 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