Mapping immune targets in peste des petits ruminants virus hemagglutinin: An integrated computational framework for vaccine candidate prioritization.

BACKGROUND

Peste des petits ruminants virus (PPRV) is a major transboundary viral pathogen of small ruminants and causes substantial economic losses in endemic regions. The hemagglutinin (H) protein mediates receptor recognition and host-cell attachment and is an important target for vaccine development. This study applied an integrated computational framework to identify conserved immunogenic regions within the PPRV H protein.

METHODS

A total of 64 unique PPRV H protein sequences were analyzed using multiple sequence alignment, entropy-based conservation profiling, conservation-aware epitope prediction, comparison with experimentally characterized immune determinants, structural mapping, candidate-region ranking, and exploratory neural-network attribution analysis. Predicted epitopes were compared with reported immune determinants and contextualized using conservation and structural data.

RESULTS

The workflow identified 9 predicted B-cell epitope candidates and 151 predicted T-cell peptide candidates distributed throughout the H protein sequence. The highest-scoring predicted B-cell epitope candidate was localized within residues 399-407 (SGPWSEGRI, Epitope_Score: 1.0000, length: 9 aa), whereas the highest-scoring T-cell peptide candidate corresponded to residues 36-44 (YILLGVLLV; score: 0.889). Conservation analysis identified 412 residues with conservation scores greater than 0.9. Comparison with experimentally characterized immune determinants showed literature-based correspondence with selected predicted regions. Structural mapping provided three-dimensional context for conserved and predicted regions. Exploratory neural-network attribution scores were generated descriptively, without biological interpretation as validated antigenicity measures.

CONCLUSIONS

Integrated computational analysis combining conservation profiling, immune epitope prediction, comparison with experimentally characterized immune determinants, structural interpretation, candidate-region ranking, and exploratory neural-network attribution analysis identified conserved and computationally predicted immune candidate regions within the PPRV H protein. Residues 399-407 (SGPWSEGRI) represented the highest-scoring computationally predicted B-cell epitope region and warrant further investigation and experimental confirmation.