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We leveraged deep learning to mine unexplored sequence space across 246 million proteins, discovering AhPETase, an evolutionarily distinct hydrolase with low homology (&lt;50% sequence identity) to known PET\u2010degrading enzymes. This noncanonical biocatalyst efficiently depolymerizes PET at 37\u00b0C, outperforming all typical PETases and achieving a 7.76\u2010fold enhancement over IsPETase, one of the most representative mesophilic PETases. Additionally, engineered variant AhPETase\n                    <jats:sup>M1<\/jats:sup>\n                    retains functional activity for over 20 days under physiological conditions and can degrade post\u2010consumer PET MPs 34\u2010fold faster than recombinant human\u2010derived enzyme MG8 (rMG8) under equal enzyme loading. Critically, it reversed PET\u2010induced toxicity in human lung and colon cells, establishing the first proof\u2010of\u2010concept for enzymatic MPs detoxification.\n                  <\/jats:p>","DOI":"10.1002\/advs.77163","type":"journal-article","created":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T11:16:22Z","timestamp":1787051782000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Deep Learning\u2010Driven Discovery and Engineering of an Efficient PETase for Depolymerization and Detoxification of PET Microplastics Under Physiological Conditions"],"prefix":"10.1002","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6476-9589","authenticated-orcid":false,"given":"Yuxuan","family":"Wang","sequence":"first","affiliation":[{"name":"College of Environmental and Resource Sciences Zhejiang University  Hangzhou China"},{"name":"School of Engineering Westlake University  Hangzhou Zhejiang China"},{"name":"The 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