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Updated: Sep 20, 2026
A High Throughput MHC II Binding Assay for Quantitative Analysis of Peptide Epitopes
Published on: March 25, 2014
Mapping immune targets in peste des petits ruminants virus hemagglutinin: An integrated computational framework for
1Research and Documentation Unit, Department of Veterinary Services, Ministry of Livestock and Fisheries Development, Sokoto, Nigeria.
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.
