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To address this, we developed an integrated strategy combining immunoinformatics with the ProteinMPNN deep learning framework. We constructed a fusion protein utilizing B\u2010cell epitopes from MPB70 and MPB83, where ProteinMPNN was employed to redesign non\u2010epitope scaffolds for optimized thermodynamic stability. The structural integrity was verified via 200\u2010ns molecular dynamics (MD) simulations. MD analysis revealed the redesigned construct transitions into a rigid, compact native state with a stable hydrophobic core. Validating this in silico design, the optimized protein achieved high\u2010yield soluble expression in\n                    <jats:styled-content style=\"fixed-case\">\n                      <jats:italic>Escherichia coli<\/jats:italic>\n                    <\/jats:styled-content>\n                    , eliminating inclusion body formation. The resulting indirect ELISA demonstrated 96.30% sensitivity and 98.61% specificity, showing excellent concordance (Cohen's\n                    <jats:italic>\u03ba<\/jats:italic>\n                    \u2009&gt;\u20090.9) with standard assays. This study demonstrates that deep learning\u2010based sequence redesign effectively resolves solubility bottlenecks in antigen engineering, providing a robust, scalable tool for precision bTB surveillance.\n                  <\/jats:p>","DOI":"10.1111\/1751-7915.70348","type":"journal-article","created":{"date-parts":[[2026,4,16]],"date-time":"2026-04-16T10:07:16Z","timestamp":1776334036000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning\u2010Enabled Engineering of a Hyper\u2010Stable and Soluble\n                    <scp>MPB70<\/scp>\n                    \u201083 Antigen for Sensitive Bovine Tuberculosis Surveillance"],"prefix":"10.1111","volume":"19","author":[{"given":"Wen\u2010Hao","family":"Wang","sequence":"first","affiliation":[{"name":"State Key Laboratory for Animal Disease Control and Prevention, College of Veterinary Medicine Lanzhou Veterinary Research Institute, Chinese Academy of 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