Systems-level design of a multi-epitope immunotherapeutic vaccine targeting EBV-associated oncogenesis.
TL;DR
An integrated immunoinformatics and structure-guided framework for the design and prioritization of therapeutic multi-epitope vaccine candidates targeting both structural glycoproteins and latency-associated proteins and identifies prioritized vaccine candidates for experimental validation is developed.
Abstract
Epstein-Barr virus (EBV) is an oncogenic herpesvirus associated with multiple lymphoid and epithelial malignancies. Despite extensive investigation of EBV vaccine strategies, effective therapeutic approaches capable of targeting established EBV-associated cancers remain limited. In this study, we developed an integrated immunoinformatics and structure-guided framework for the design and prioritization of therapeutic multi-epitope vaccine candidates targeting both structural glycoproteins (gp350, gB, gH/gL, and gp42) and latency-associated proteins (EBNA1, LMP1, LMP2, and BZLF1). Sixteen multi-epitope vaccine constructs were generated and evaluated through sequence validation, structural refinement, reverse vaccinology assessment, immune-response simulation, receptor interaction analysis, molecular dynamics simulations, and expression-readiness profiling. The prioritized epitope repertoire achieved projected global population coverage exceeding 98% for both MHC class I and II pathways. Structural refinement improved model quality across vaccine constructs, while immunological and safety assessments supported favorable predicted antigenicity, non-allergenic potential, non-toxicity, and developability properties. Immune simulations predicted coordinated innate, humoral, and cellular responses, with several constructs demonstrating strong predicted immunogenic profiles. Molecular docking and molecular dynamics analyses further supported predicted structural compatibility and interaction stability with immune-associated receptors under simulated conditions. Integrated multi-parameter evaluation identified Constructs 4, 7, 10, 8, and 12 as the most promising candidates, with Construct 4 exhibiting the most balanced profile across immunological, structural, safety, and expression-related properties. Collectively, this study provides a comprehensive computational framework for therapeutic EBV vaccine development and identifies prioritized vaccine candidates for experimental validation. The proposed strategy offers a scalable approach for accelerating the development of multi-epitope vaccines targeting persistent viral infections and virus-associated malignancies.