{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T15:25:36Z","timestamp":1787153136016,"version":"build-2736575974"},"reference-count":52,"publisher":"American Chemical Society (ACS)","issue":"32","license":[{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2026,8,4]],"date-time":"2026-08-04T00:00:00Z","timestamp":1785801600000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"funder":[{"DOI":"10.13039\/501100003725","name":"National Research Foundation of Korea","doi-asserted-by":"publisher","award":["RS-2026-25472936"],"award-info":[{"award-number":["RS-2026-25472936"]}],"id":[{"id":"10.13039\/501100003725","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2026,8,19]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Enzymatic transglycosylation by Deinococcus geothermalis amylosucrase (DgAS) offers a cost-effective route for enhancing the physicochemical properties of bioactive flavonoids. However, predicting DgAS acceptor specificity remains challenging due to complex structure\u2013activity relationships. Here, we developed a data-driven \u201cdigital twin\u201d using deep learning-based Molecular Embeddings (MolE) and L1-regularized logistic regression to decode these structural determinants. Training on experimentally validated substrates and physicochemical decoys, the MolE-based classifier achieved a 98.4% F1-score and 97.6% accuracy, outperforming traditional molecular fingerprints. SHAP analysis revealed a push\u2013pull recognition mechanism, rewarding planar aglycone cores while penalizing steric constraints. Predictive power was validated through in vitro screening, identifying novel active acceptors (e.g., morin, 65.56% yield) and filtering out nonbinders like pinocembrin. Though constrained by substrate chemical stability, this acceptor-centric framework reduces trial-and-error, providing a promising ligand-based virtual screening approach for identifying novel acceptors in enzymatic transglycosylation.<\/jats:p>","DOI":"10.1021\/acs.jafc.6c05432","type":"journal-article","created":{"date-parts":[[2026,8,5]],"date-time":"2026-08-05T03:02:09Z","timestamp":1785898929000},"page":"25452-25462","source":"Crossref","is-referenced-by-count":0,"title":["Data-Driven Digital Twin for Amylosucrase from\n                    <i>Deinococcus geothermalis<\/i>\n                    : Accelerating Acceptor Discovery\nin Transglycosylation Reactions"],"prefix":"10.1021","volume":"74","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0423-5686","authenticated-orcid":true,"given":"Dong-Ho","family":"Seo","sequence":"first","affiliation":[{"name":"Sejong University , , ,","place":["Seoul, Republic of Korea, 05006"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0009-0007-6301-1910","authenticated-orcid":true,"given":"Yun-Sang","family":"So","sequence":"additional","affiliation":[{"name":"Sejong University , , ,","place":["Seoul, Republic of Korea, 05006"]}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7258-5090","authenticated-orcid":true,"given":"Sang-Ho","family":"Yoo","sequence":"additional","affiliation":[{"name":"Sejong University , , ,","place":["Seoul, Republic of Korea, 05006"]}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"316","published-online":{"date-parts":[[2026,8,4]]},"reference":[{"key":"2026081910175596100_cit1","doi-asserted-by":"publisher","first-page":"105296","DOI":"10.1016\/j.tifs.2025.105296","article-title":"Advances in flavonoid glycosylation: Chemical and biological basis,\nmechanisms, physicochemical properties, and applications in the food\nindustry","volume":"165","author":"Lai","year":"2025","journal-title":"Trends Food Sci. Technol."},{"issue":"11","key":"2026081910175596100_cit2","doi-asserted-by":"publisher","first-page":"449","DOI":"10.1016\/S0167-7799(01)01765-6","article-title":"Altering the glycosylation pattern\nof bioactive compounds","volume":"19","author":"Me\u0301ndez","year":"2001","journal-title":"Trends Biotechnol."},{"key":"2026081910175596100_cit3","doi-asserted-by":"publisher","first-page":"125916","DOI":"10.1016\/j.ijbiomac.2023.125916","article-title":"Utilization of glycosyltransferases\nas a seamless tool for synthesis\nand modification of the oligosaccharides-A review","volume":"249","author":"Ali","year":"2023","journal-title":"Int. J. Biol. Macromol."},{"issue":"1","key":"2026081910175596100_cit4","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10068-019-00686-6","article-title":"Versatile\nbiotechnological applications of amylosucrase, a novel glucosyltransferase","volume":"29","author":"Seo","year":"2020","journal-title":"Food Sci. Biotechnol."},{"issue":"11","key":"2026081910175596100_cit5","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0207466","article-title":"Enzymatic synthesis\nof \u03b1-flavone glucoside via\nregioselective transglucosylation by amylosucrase from Deinococcus geothermalis","volume":"13","author":"Jang","year":"2018","journal-title":"PLoS One"},{"issue":"1","key":"2026081910175596100_cit6","doi-asserted-by":"publisher","first-page":"148","DOI":"10.1002\/cmdc.200900314","article-title":"Comparison of Structure-\nand Ligand-Based Virtual Screening Protocols\nConsidering Hit List Complementarity and Enrichment Factors","volume":"5","author":"Kru\u0308ger","year":"2010","journal-title":"ChemMedChem."},{"issue":"7019","key":"2026081910175596100_cit7","doi-asserted-by":"publisher","first-page":"862","DOI":"10.1038\/nature03197","article-title":"Virtual\nscreening of chemical libraries","volume":"432","author":"Shoichet","year":"2004","journal-title":"Nature"},{"key":"2026081910175596100_cit8","doi-asserted-by":"publisher","first-page":"26","DOI":"10.1016\/j.ymeth.2014.07.007","article-title":"Hierarchical\nvirtual screening approaches in small\nmolecule drug discovery","volume":"71","author":"Kumar","year":"2015","journal-title":"Methods"},{"key":"2026081910175596100_cit9","doi-asserted-by":"publisher","first-page":"1682","DOI":"10.1038\/s41401-025-01732-2","article-title":"VsNsbench: evaluating AlphaFold3-embed induced-fit\nmechanism for enhanced virtual screening","volume":"47","author":"Gu","year":"2026","journal-title":"Acta\nPharmacol. Sin."},{"key":"2026081910175596100_cit10","doi-asserted-by":"publisher","first-page":"343","DOI":"10.3389\/fchem.2020.00343","article-title":"Structure-Based\nVirtual Screening: From Classical to Artificial Intelligence","volume":"8","author":"Maia","year":"2020","journal-title":"Frontiers in Chemistry"},{"issue":"1","key":"2026081910175596100_cit11","doi-asserted-by":"publisher","first-page":"323","DOI":"10.1038\/srep00323","article-title":"How well do\nthe substrates KISS the enzyme? Molecular docking program selection\nfor feruloyl esterases","volume":"2","author":"Udatha","year":"2012","journal-title":"Sci. Rep."},{"issue":"6","key":"2026081910175596100_cit12","doi-asserted-by":"publisher","first-page":"1687","DOI":"10.1021\/ci5001554","article-title":"Prediction of Substrates\nfor Glutathione Transferases by Covalent Docking","volume":"54","author":"Dong","year":"2014","journal-title":"J. Chem. Inf. Model."},{"issue":"2","key":"2026081910175596100_cit13","doi-asserted-by":"publisher","first-page":"528","DOI":"10.1021\/bi501140k","article-title":"Covalent Docking Predicts Substrates for Haloalkanoate\nDehalogenase Superfamily Phosphatases","volume":"54","author":"London","year":"2015","journal-title":"Biochemistry"},{"issue":"22","key":"2026081910175596100_cit14","doi-asserted-by":"publisher","first-page":"5363","DOI":"10.1021\/acs.jpcb.4c01875","article-title":"Utility of the Morgan\nFingerprint in Structure-Based\nVirtual Ligand Screening","volume":"128","author":"Zhou","year":"2024","journal-title":"J. Phys. Chem. B"},{"issue":"2","key":"2026081910175596100_cit15","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1007\/s10822-025-00686-1","article-title":"\u03bcOR-ligand:\ntarget-aware view-based hybrid feature selection for \u03bc-opioid\nreceptor ligand functional classification","volume":"39","author":"Ugurlu","year":"2025","journal-title":"J.\nComput.-Aided Mol. Des."},{"issue":"02","key":"2026081910175596100_cit16","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1142\/S2737416525500474","article-title":"Discovery\nof Novel Potential Binders Targeting Norovirus 3CL Protease: A Machine\nLearning and Molecular Dynamics Approach","volume":"25","author":"Babaker","year":"2026","journal-title":"J.\nComput. Biophys. Chem."},{"issue":"4","key":"2026081910175596100_cit17","doi-asserted-by":"publisher","first-page":"715","DOI":"10.1016\/j.fmre.2024.02.011","article-title":"A review of deep learning methods for ligand based\ndrug virtual screening","volume":"4","author":"Wu","year":"2024","journal-title":"Fundam. Res."},{"issue":"1","key":"2026081910175596100_cit18","doi-asserted-by":"publisher","first-page":"56","DOI":"10.1186\/s13321-020-00460-5","article-title":"Molecular representations\nin AI-driven drug discovery: a review and practical guide","volume":"12","author":"David","year":"2020","journal-title":"J. Cheminf."},{"issue":"5","key":"2026081910175596100_cit19","doi-asserted-by":"publisher","first-page":"742","DOI":"10.1021\/ci100050t","article-title":"Extended-Connectivity\nFingerprints","volume":"50","author":"Rogers","year":"2010","journal-title":"J. Chem.\nInf. Model."},{"issue":"16","key":"2026081910175596100_cit20","doi-asserted-by":"publisher","first-page":"8705","DOI":"10.1021\/acs.jmedchem.0c00385","article-title":"Learning\nMolecular Representations\nfor Medicinal Chemistry","volume":"63","author":"Chuang","year":"2020","journal-title":"J. Med. Chem."},{"issue":"1","key":"2026081910175596100_cit21","doi-asserted-by":"publisher","first-page":"9431","DOI":"10.1038\/s41467-024-53751-y","article-title":"MolE: a foundation\nmodel for molecular\ngraphs using disentangled attention","volume":"15","author":"Me\u0301ndez-Lucio","year":"2024","journal-title":"Nat. Commun."},{"issue":"5","key":"2026081910175596100_cit22","doi-asserted-by":"publisher","first-page":"1189","DOI":"10.1007\/s00253-012-3905-7","article-title":"High-yield\nenzymatic bioconversion of hydroquinone to \u03b1-arbutin, a powerful\nskin lightning agent, by amylosucrase","volume":"94","author":"Seo","year":"2012","journal-title":"Appl.\nMicrobiol. Biotechnol."},{"issue":"1","key":"2026081910175596100_cit23","doi-asserted-by":"publisher","first-page":"287","DOI":"10.1021\/acs.biomac.5c01328","article-title":"Physicochemical\nProperties of Thermoreversible Glucan Aggregates Synthesized by Amylosucrase\nfrom Deinococcus geothermalis","volume":"27","author":"So","year":"2026","journal-title":"Biomacromolecules"},{"key":"2026081910175596100_cit24","first-page":"125","volume-title":"Molecular Cloning of the Amylosucrase Gene\nfrom a Moderate Thermophilic Bacterium Deinococcus geothermalis and\nAnalysis of Its Dual Enzyme Activity. Carbohydrate-Active Enzymes:\nStructure, Function and Applications","author":"Seo","year":"2008"},{"issue":"47","key":"2026081910175596100_cit25","doi-asserted-by":"publisher","first-page":"13798","DOI":"10.1021\/acs.jafc.0c05625","article-title":"Using amylosucrase\nfor the controlled synthesis of novel isoquercitrin glycosides with\ndifferent glycosidic linkages","volume":"68","author":"Rha","year":"2020","journal-title":"J. Agric. Food\nChem."},{"issue":"7","key":"2026081910175596100_cit26","doi-asserted-by":"publisher","first-page":"1205","DOI":"10.1021\/ci100010v","article-title":"When is Chemical Similarity Significant? The Statistical Distribution\nof Chemical Similarity Scores and Its Extreme Values","volume":"50","author":"Baldi","year":"2010","journal-title":"J. Chem. Inf. Model."},{"issue":"5","key":"2026081910175596100_cit27","doi-asserted-by":"publisher","first-page":"2430","DOI":"10.1021\/acs.jafc.2c07778","article-title":"Synthesis of Alpha-Linked Glucosides\nfrom Soybean Isoflavone Aglycones Using Amylosucrase from Deinococcus geothermalis","volume":"71","author":"Jung","year":"2023","journal-title":"J. Agric.\nFood Chem."},{"issue":"48","key":"2026081910175596100_cit28","doi-asserted-by":"publisher","first-page":"46300","DOI":"10.1021\/acsomega.3c08255","article-title":"Regioselective Glycosylation\nof Polyphenols by Family 1 Glycosyltransferases: Experiments and Simulations","volume":"8","author":"de Boer","year":"2023","journal-title":"ACS Omega"},{"key":"2026081910175596100_cit29","doi-asserted-by":"publisher","first-page":"109361","DOI":"10.1016\/j.enzmictec.2019.109361","article-title":"Site-specific\n\u03b1-glycosylation of hydroxyflavones and hydroxyflavanones by\namylosucrase from Deinococcus geothermalis","volume":"129","author":"Rha","year":"2019","journal-title":"Enzyme Microb. Technol."},{"key":"2026081910175596100_cit30","doi-asserted-by":"publisher","first-page":"19","DOI":"10.1016\/j.ab.2017.05.028","article-title":"Fluorescence\ndetection of the transglycosylation\nactivity of amylosucrase","volume":"532","author":"Seo","year":"2017","journal-title":"Anal. Biochem."},{"issue":"9","key":"2026081910175596100_cit31","doi-asserted-by":"publisher","first-page":"1436","DOI":"10.4014\/jmb.2003.03066","article-title":"Molecular docking and kinetic studies of the A226N\nmutant of Deinococcus geothermalis amylosucrase with\nenhanced transglucosylation activity","volume":"30","author":"Seungpyo","year":"2020","journal-title":"J. Microbiol.\nBiotechnol."},{"issue":"1","key":"2026081910175596100_cit32","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1021\/ci0342472","article-title":"The Problem\nof Overfitting","volume":"44","author":"Hawkins","year":"2004","journal-title":"J. Chem. Inf. Comput. Sci."},{"issue":"8","key":"2026081910175596100_cit33","doi-asserted-by":"publisher","first-page":"3370","DOI":"10.1021\/acs.jcim.9b00237","article-title":"Analyzing\nlearned molecular representations for property prediction","volume":"59","author":"Yang","year":"2019","journal-title":"J. Chem. Inf. Model."},{"issue":"8","key":"2026081910175596100_cit34","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0220113","article-title":"Hidden bias\nin the\nDUD-E dataset leads to misleading performance of deep learning in\nstructure-based virtual screening","volume":"14","author":"Chen","year":"2019","journal-title":"PLoS One"},{"issue":"15","key":"2026081910175596100_cit35","doi-asserted-by":"publisher","first-page":"2134","DOI":"10.1093\/bioinformatics\/btab080","article-title":"Generating\nproperty-matched decoy\nmolecules using deep learning","volume":"37","author":"Imrie","year":"2021","journal-title":"Bioinformatics"},{"issue":"6","key":"2026081910175596100_cit36","doi-asserted-by":"publisher","first-page":"983","DOI":"10.1021\/ci9800211","article-title":"Chemical\nSimilarity Searching","volume":"38","author":"Willett","year":"1998","journal-title":"J. Chem. Inf. Comput.\nSci."},{"issue":"14","key":"2026081910175596100_cit37","doi-asserted-by":"publisher","first-page":"6582","DOI":"10.1021\/jm300687e","article-title":"Directory of Useful\nDecoys, Enhanced (DUD-E): Better Ligands and Decoys for Better Benchmarking","volume":"55","author":"Mysinger","year":"2012","journal-title":"J. Med. Chem."},{"issue":"5","key":"2026081910175596100_cit38","doi-asserted-by":"publisher","first-page":"916","DOI":"10.1021\/acs.jcim.7b00403","article-title":"Most Ligand-Based Classification Benchmarks Reward\nMemorization Rather than Generalization","volume":"58","author":"Wallach","year":"2018","journal-title":"J.\nChem. Inf. Model."},{"issue":"11","key":"2026081910175596100_cit39","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0224365","article-title":"Machine learning\nalgorithm validation with a limited sample size","volume":"14","author":"Vabalas","year":"2019","journal-title":"PLoS One"},{"issue":"10","key":"2026081910175596100_cit40","doi-asserted-by":"publisher","first-page":"78","DOI":"10.1145\/2347736.2347755","article-title":"A few useful\nthings to know about machine learning","volume":"55","author":"Domingos","year":"2012","journal-title":"Commun.\nACM"},{"issue":"3","key":"2026081910175596100_cit41","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pone.0342408","article-title":"Random subspace-based\nensemble classifier for high-dimensional\ndata Using SPARK","volume":"21","author":"Bhimineni","year":"2026","journal-title":"PLoS One"},{"issue":"1","key":"2026081910175596100_cit42","doi-asserted-by":"publisher","first-page":"267","DOI":"10.1111\/j.2517-6161.1996.tb02080.x","article-title":"Regression\nShrinkage and Selection Via the Lasso","volume":"58","author":"Tibshirani","year":"1996","journal-title":"Journal\nof the Royal Statistical Society: Series B (Methodological)"},{"issue":"4","key":"2026081910175596100_cit43","doi-asserted-by":"publisher","first-page":"1535","DOI":"10.1021\/ci060117s","article-title":"On Outliers\nand Activity CliffsWhy QSAR Often Disappoints","volume":"46","author":"Maggiora","year":"2006","journal-title":"J. Chem. Inf. Model."},{"key":"2026081910175596100_cit44","doi-asserted-by":"publisher","first-page":"810875","DOI":"10.3389\/fgene.2021.810875","article-title":"Application\nof Sparse Representation in Bioinformatics","volume":"12","author":"Han","year":"2021","journal-title":"Front. Genet."},{"issue":"1","key":"2026081910175596100_cit45","doi-asserted-by":"publisher","first-page":"100","DOI":"10.1038\/s43586-022-00184-w","article-title":"Principal\ncomponent analysis","volume":"2","author":"Greenacre","year":"2022","journal-title":"Nat. Rev. Methods Primers"},{"issue":"5","key":"2026081910175596100_cit46","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/j.drudis.2007.01.011","article-title":"Molecular similarity\nanalysis in virtual screening:\nfoundations, limitations and novel approaches","volume":"12","author":"Eckert","year":"2007","journal-title":"Drug Discovery Today"},{"key":"2026081910175596100_cit47","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.jbiotec.2015.07.002","article-title":"Biotransformation of\nphloretin by\namylosucrase yields three novel dihydrochalcone glucosides","volume":"211","author":"Overwin","year":"2015","journal-title":"J. Biotechnol."},{"issue":"1","key":"2026081910175596100_cit48","doi-asserted-by":"publisher","first-page":"181","DOI":"10.3390\/molecules25010181","article-title":"Enrichment of Polyglucosylated\nIsoflavones from Soybean\nIsoflavone Aglycones Using Optimized Amylosucrase Transglycosylation","volume":"25","author":"Jung","year":"2020","journal-title":"Molecules"},{"key":"2026081910175596100_cit49","doi-asserted-by":"publisher","first-page":"139182","DOI":"10.1016\/j.foodchem.2024.139182","article-title":"Efficient biotransformation\nof naringenin to naringenin\n\u03b1-glucoside, a novel \u03b1-glucosidase inhibitor, by amylosucrase\nfrom Deinococcus wulumuquiensis","volume":"448","author":"Yu","year":"2024","journal-title":"Food Chem."},{"key":"2026081910175596100_cit50","doi-asserted-by":"publisher","first-page":"104442","DOI":"10.1016\/j.fbio.2024.104442","article-title":"Improving the transglycosylation\nreaction of amylosucrase\nfrom Deinococcus geothermalis variant for increased\nflavonoid reactivity","volume":"61","author":"Ryu","year":"2024","journal-title":"Food Biosci."},{"issue":"12","key":"2026081910175596100_cit51","doi-asserted-by":"publisher","first-page":"9975","DOI":"10.1021\/acs.jafc.6c01781","article-title":"Artificial Intelligence-Driven Enzyme\nEngineering from\nStructural Prediction to De Novo Design","volume":"74","author":"Shi","year":"2026","journal-title":"J.\nAgric. Food Chem."},{"issue":"11","key":"2026081910175596100_cit52","doi-asserted-by":"publisher","first-page":"4178","DOI":"10.1021\/acssynbio.5c00452","article-title":"Artificial\nIntelligence-Driven de Novo Design of Robust Enzymes to Enhance Their\nPerformance","volume":"14","author":"Tang","year":"2025","journal-title":"ACS Synth. Biol."}],"container-title":["Journal of Agricultural and Food Chemistry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jafc.6c05432","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/jafcau\/article-pdf\/74\/32\/25452\/66395077\/acs.jafc.6c05432.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/pubs.acs.org\/jafcau\/article-pdf\/74\/32\/25452\/66395077\/acs.jafc.6c05432.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,8,19]],"date-time":"2026-08-19T14:31:38Z","timestamp":1787149898000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/jafcau\/article\/74\/32\/25452\/5243736\/Data-Driven-Digital-Twin-for-Amylosucrase-from"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,8,4]]},"references-count":52,"journal-issue":{"issue":"32","published-online":{"date-parts":[[2026,8,4]]},"published-print":{"date-parts":[[2026,8,19]]}},"URL":"https:\/\/doi.org\/10.1021\/acs.jafc.6c05432","relation":{},"ISSN":["0021-8561","1520-5118"],"issn-type":[{"value":"0021-8561","type":"print"},{"value":"1520-5118","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,8,4]]}}}