{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T17:56:40Z","timestamp":1790791000106,"version":"4.1.0"},"reference-count":50,"publisher":"Wiley","license":[{"start":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T00:00:00Z","timestamp":1790467200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T00:00:00Z","timestamp":1790467200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["advanced.onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Advanced Science"],"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>\n                    Enzyme turnover number () is a central kinetic parameter for biocatalysis, but experimental determination is low\u2010throughput and existing computational methods inadequately model enzyme\u2013reaction interplay. Here, we introduced MCKcat, a deep learning framework that integrates multi\u2010scale convolutional feature extraction and cross\u2010attention to enable deep, reciprocal fusion of enzyme sequence and reaction fingerprint representations for accurate  prediction. We constructed MCKcat\u2010DB, a large\u2010scale dataset comprising 33 396 enzyme\u2010reaction\u2010based  data points, covering both wild\u2010type enzymes and a large number of mutants. MCKcat demonstrated competitive performance across diverse prediction scenarios on two benchmarks. A two\u2010step strategy was developed to engineer\n                    <jats:italic>Bacillus aryabhattai<\/jats:italic>\n                    laccase with synergistically improved thermostability and catalytic activity. Rational design generated 217 candidate thermostable mutants, followed by MCKcat\u2010based screening that identified 20 hits. Validation showed 15 mutants (75% positive rate) exhibited simultaneous enhancements in both thermostability and . A user\u2010friendly web server was provided to facilitate broad adoption. MCKcat establishes a robust, generalizable strategy for data\u2010driven  prediction and artificial intelligence\u2010assisted enzyme\u00a0engineering.\n                  <\/jats:p>","DOI":"10.1002\/advs.77789","type":"journal-article","created":{"date-parts":[[2026,9,27]],"date-time":"2026-09-27T18:00:31Z","timestamp":1790532031000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Predicting Enzyme Turnover Numbers and Enabling Rational Enzyme Evolution"],"prefix":"10.1002","author":[{"given":"Fengya","family":"Ge","sequence":"first","affiliation":[{"name":"College of Artificial Intelligence Tianjin University of Science and Technology Tianjin P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiangyang","family":"Ma","sequence":"additional","affiliation":[{"name":"Key Laboratory of Industrial Fermentation Microbiology, Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, The College of Biotechnology Tianjin University of Science and Technology Tianjin P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jiyan","family":"Li","sequence":"additional","affiliation":[{"name":"Key Laboratory of Industrial Fermentation Microbiology, Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, The College of Biotechnology Tianjin University of Science and Technology Tianjin P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mengxiang","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence Tianjin University of Science and Technology Tianjin P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Fuping","family":"Lu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Industrial Fermentation Microbiology, Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, The College of Biotechnology Tianjin University of Science and Technology Tianjin P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5322-6818","authenticated-orcid":false,"given":"Yihan","family":"Liu","sequence":"additional","affiliation":[{"name":"Key Laboratory of Industrial Fermentation Microbiology, Ministry of Education, Tianjin Key Laboratory of Industrial Microbiology, The College of Biotechnology Tianjin University of Science and Technology Tianjin P. R. China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5025-3880","authenticated-orcid":false,"given":"Lin","family":"Wang","sequence":"additional","affiliation":[{"name":"College of Artificial Intelligence Tianjin University of Science and Technology Tianjin P. R. 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