Epitope-Based Peptide Vaccine Construction Against Nipah Virus Using Comprehensive Immunoinformatics Approaches

Nipah virus (NiV) outbreaks continue to pose a serious public health threat in South Asia, particularly in India, with no approved vaccines currently available for human use. To address this challenge, we employed an integrated reverse vaccinology and immunoinformatics approach to design a multiepitope vaccine targeting the NiV G glycoprotein, a key viral surface protein responsible for host-cell attachment. Computational pipelines were utilized to predict antigenic B-cell and T-cell epitopes, evaluate their immunogenicity, and assess their binding affinity with common human HLA alleles through molecular docking. A promising epitope, AVGFLVRTEFKYNDS, was identified and its three-dimensional structure modeled and validated. Unlike previous NiV vaccine design studies that focused on conserved peptide prediction alone, this work integrates a comprehensive workflow combining antigenicity screening, structural modeling, and molecular interaction analysis to enhance vaccine precision. Overall, the findings demonstrate the potential of computational vaccinology to accelerate rational NiV vaccine development and lay the groundwork for future experimental validation.