Supplementary Data: Multi-Epitope Vaccine Design Targeting E and NS1 Proteins of Spondweni Virus

Supplementary Data: Multi-Epitope Vaccine Design Targeting E and NS1 Proteins of Spondweni Virus This repository contains the supplementary data and computational analysis files supporting the study entitled “Integrated Immunoinformatics and Structural Modelling Approach for Multi-Epitope Vaccine Design Targeting E and NS1 Proteins of Spondweni Virus ”, which describes the in-silico design and immunoinformatics evaluation of a multi-epitope vaccine targeting the envelope (E) and non-structural protein 1 (NS1) of Spondweni virus (SPONV). The deposited materials provide the underlying datasets, sequences, prediction outputs, and computational results used throughout the vaccine-design workflow. The supplementary files include the original SPONV protein sequence dataset used for comparative and phylogenetic analyses; multiple-sequence alignment files; selected B-cell, cytotoxic T-lymphocyte (CTL), and helper T-lymphocyte (HTL) epitope sequences; epitope prediction and screening results; epitope conservation analyses; HLA population-coverage inputs and outputs; the final multi-epitope vaccine amino-acid sequence; the codon-optimised nucleotide sequence; physicochemical, antigenicity, allergenicity, and toxicity assessment results; structural modelling files; molecular docking data; immune simulation outputs; and in-silico cloning data. These materials are provided to promote transparency, reproducibility, and independent evaluation of the computational analyses reported in the manuscript. The repository should be considered a supplementary resource accompanying the published manuscript and should be interpreted together with the methods and limitations described therein. Keywords: Spondweni virus; SPONV; multi-epitope vaccine; envelope protein; NS1 protein; immunoinformatics; epitope prediction; CTL epitopes; HTL epitopes; B-cell epitopes; HLA population coverage; molecular docking; immune simulation; in-silico vaccine design.