{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T05:58:28Z","timestamp":1790747908765,"version":"4.1.0"},"reference-count":21,"publisher":"SAGE Publications","issue":"3","license":[{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2026,7,1]],"date-time":"2026-07-01T00:00:00Z","timestamp":1782864000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/journals.sagepub.com\/page\/policies\/text-and-data-mining-license"}],"funder":[{"name":"Fundamental Research Funds for the Central Universities of China"}],"content-domain":{"domain":["journals.sagepub.com"],"crossmark-restriction":true},"short-container-title":["Science Progress"],"published-print":{"date-parts":[[2026,7]]},"abstract":"<jats:sec>\n                    <jats:title>Objective<\/jats:title>\n                    <jats:p>Prediction of mutation-induced enzyme activity changes is important for protein engineering, drug response analysis, and precision medicine. Existing methods often depend on structural information or complex external pipelines, limiting reproducibility and practical use.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>We developed EnzyDiff, a lightweight diffusion-based framework that encodes mutation-induced activity perturbations from enzyme sequences before and after mutation, together with mutation identity and position. The model was evaluated on the P450 deep mutational scanning dataset using five-fold cross-validation, with additional analyses of robustness, representation visualization, and case-based occlusion sensitivity. After preprocessing, 3,289 labeled mutation entries were retained, including 240 Increased samples and 3,049 Decreased samples.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>In five-fold cross-validation, EnzyDiff achieved an accuracy of 0.933, F1-score of 0.497, AUROC of 0.803, and PR-AUC of 0.495 on the P450 dataset. It remained stable under reversed mutation settings, showed clear class separation in learned representations, and highlighted mutation-relevant positions in interpretability analyses. However, the moderate F1-score also indicates that minority-class prediction remains challenging under strong class imbalance.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>EnzyDiff is a lightweight, reproducible, and interpretable framework for enzyme activity direction classification. It offers a practical sequence-based solution for functional mutation assessment and downstream biological analysis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1177\/00368504261489697","type":"journal-article","created":{"date-parts":[[2026,9,11]],"date-time":"2026-09-11T14:38:45Z","timestamp":1789137525000},"update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":0,"title":["EnzyDiff: Sequence-based classification of mutation-induced enzyme activity direction using latent diffusion denoising"],"prefix":"10.1177","volume":"109","author":[{"given":"Hui","family":"Jin","sequence":"first","affiliation":[{"name":"The First Affiliated hospital of Xi\u2019an Medical University"},{"name":"Shanghai Mental Health Center"},{"name":"Shanghai Jiao Tong University"},{"name":"Shanghai Jiao Tong University"},{"name":"Shanghai Gener Arfysica Intelligent Healthcare &amp; Brain Science Research Institute, Shanghai, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7685-5457","authenticated-orcid":false,"given":"Zhe","family":"Liu","sequence":"additional","affiliation":[{"name":"East China University of Science and Technology"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhuopeng","family":"Jia","sequence":"additional","affiliation":[{"name":"The First Affiliated hospital of Xi\u2019an Medical University"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"179","published-online":{"date-parts":[[2026,9,11]]},"reference":[{"key":"e_1_3_6_2_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jctc.5c01912"},{"key":"e_1_3_6_3_2","doi-asserted-by":"publisher","DOI":"10.3390\/molecules31010045"},{"key":"e_1_3_6_4_2","doi-asserted-by":"publisher","DOI":"10.1085\/jgp.202012662"},{"key":"e_1_3_6_5_2","first-page":"32","article-title":"A collection of bioinformatics tools to protein engineering","volume":"3","author":"Arab SS","year":"2014","unstructured":"Arab SS, Shirvanizadeh N, Khoshnejat M. A collection of bioinformatics tools to protein engineering. MOLECULAR BIOLOGY RESEARCH COMMUNICATIONS 2014; 3: 32, [online].","journal-title":"MOLECULAR BIOLOGY RESEARCH COMMUNICATIONS"},{"key":"e_1_3_6_6_2","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa0901281"},{"key":"e_1_3_6_7_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.molmed.2016.12.003"},{"key":"e_1_3_6_8_2","doi-asserted-by":"publisher","DOI":"10.15252\/emmm.201606210"},{"key":"e_1_3_6_9_2","doi-asserted-by":"publisher","DOI":"10.1002\/wcms.1502"},{"key":"e_1_3_6_10_2","doi-asserted-by":"publisher","DOI":"10.1002\/pro.70081"},{"key":"e_1_3_6_11_2","doi-asserted-by":"publisher","DOI":"10.3390\/catal11020286"},{"key":"e_1_3_6_12_2","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pcbi.1006658"},{"key":"e_1_3_6_13_2","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbag081"},{"key":"e_1_3_6_14_2","doi-asserted-by":"publisher","DOI":"10.1021\/acssynbio.6c00037"},{"key":"e_1_3_6_15_2","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btaf511"},{"key":"e_1_3_6_16_2","doi-asserted-by":"publisher","DOI":"10.1093\/bib\/bbaf120"},{"key":"e_1_3_6_17_2","doi-asserted-by":"publisher","DOI":"10.3390\/biom15060843"},{"key":"e_1_3_6_18_2","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.4c00920"},{"key":"e_1_3_6_19_2","doi-asserted-by":"publisher","DOI":"10.3390\/molecules30020214"},{"key":"e_1_3_6_20_2","first-page":"1","article-title":"Exploration of Computational Approaches in Enzyme Classification: Problems and Recent Development\u2014A Critical Review","volume":"33","author":"Singh P","year":"2025","unstructured":"Singh P, Tripathi S, Bihari A. Exploration of Computational Approaches in Enzyme Classification: Problems and Recent Development\u2014A Critical Review. Archives of Computational Methods in Engineering 2025; 33: 1\u201341. https:\/\/doi.org\/10.1007\/s11831-025-10377-7","journal-title":"Archives of Computational Methods in Engineering"},{"key":"e_1_3_6_21_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ajhg.2021.07.001"},{"key":"e_1_3_6_22_2","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2023.3261988"}],"container-title":["Science Progress"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/00368504261489697","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/full-xml\/10.1177\/00368504261489697","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/journals.sagepub.com\/doi\/pdf\/10.1177\/00368504261489697","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T05:17:47Z","timestamp":1790745467000},"score":1,"resource":{"primary":{"URL":"https:\/\/journals.sagepub.com\/doi\/10.1177\/00368504261489697"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,7]]},"references-count":21,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2026,7]]}},"alternative-id":["10.1177\/00368504261489697"],"URL":"https:\/\/doi.org\/10.1177\/00368504261489697","relation":{},"ISSN":["0036-8504","2047-7163"],"issn-type":[{"value":"0036-8504","type":"print"},{"value":"2047-7163","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,7]]},"article-number":"00368504261489697"}}