{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T07:57:18Z","timestamp":1778227038936,"version":"3.51.4"},"reference-count":43,"publisher":"Oxford University Press (OUP)","issue":"4","license":[{"start":{"date-parts":[[2023,5,23]],"date-time":"2023-05-23T00:00:00Z","timestamp":1684800000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/pages\/standard-publication-reuse-rights"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2020YFC2008802"],"award-info":[{"award-number":["2020YFC2008802"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100012166","name":"National Key Research and Development Program of China","doi-asserted-by":"publisher","award":["2021SFGC0504"],"award-info":[{"award-number":["2021SFGC0504"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009108","name":"Shandong University","doi-asserted-by":"publisher","award":["21320082064101"],"award-info":[{"award-number":["21320082064101"]}],"id":[{"id":"10.13039\/100009108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100009108","name":"Shandong University","doi-asserted-by":"publisher","award":["21320082164070"],"award-info":[{"award-number":["21320082164070"]}],"id":[{"id":"10.13039\/100009108","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"National Institutes of Health","doi-asserted-by":"publisher","award":["R35ES028365"],"award-info":[{"award-number":["R35ES028365"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,7,20]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>Enzymatic reactions are crucial to explore the mechanistic function of metabolites and proteins in cellular processes and to understand the etiology of diseases. The increasing number of interconnected metabolic reactions allows the development of in silico deep learning-based methods to discover new enzymatic reaction links between metabolites and proteins to further expand the landscape of existing metabolite\u2013protein interactome. Computational approaches to predict the enzymatic reaction link by metabolite\u2013protein interaction (MPI) prediction are still very limited. In this study, we developed a Variational Graph Autoencoders (VGAE)-based framework to predict MPI in genome-scale heterogeneous enzymatic reaction networks across ten organisms. By incorporating molecular features of metabolites and proteins as well as neighboring information in the MPI networks, our MPI-VGAE predictor achieved the best predictive performance compared to other machine learning methods. Moreover, when applying the MPI-VGAE framework to reconstruct hundreds of metabolic pathways, functional enzymatic reaction networks and a metabolite\u2013metabolite interaction network, our method showed the most robust performance among all scenarios. To the best of our knowledge, this is the first MPI predictor by VGAE for enzymatic reaction link prediction. Furthermore, we implemented the MPI-VGAE framework to reconstruct the disease-specific MPI network based on the disrupted metabolites and proteins in Alzheimer\u2019s disease and colorectal cancer, respectively. A substantial number of novel enzymatic reaction links were identified. We further validated and explored the interactions of these enzymatic reactions using molecular docking. These results highlight the potential of the MPI-VGAE framework for the discovery of novel disease-related enzymatic reactions and facilitate the study of the disrupted metabolisms in diseases.<\/jats:p>","DOI":"10.1093\/bib\/bbad189","type":"journal-article","created":{"date-parts":[[2023,5,25]],"date-time":"2023-05-25T01:48:55Z","timestamp":1684979335000},"source":"Crossref","is-referenced-by-count":7,"title":["MPI-VGAE: protein\u2013metabolite enzymatic reaction link learning by variational graph autoencoders"],"prefix":"10.1093","volume":"24","author":[{"given":"Cheng","family":"Wang","sequence":"first","affiliation":[{"name":"Shandong University Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, , Jinan, 250012 , China"},{"name":"Shandong University National Institute of Health Data Science of China, , Jinan, 250000 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chuang","family":"Yuan","sequence":"additional","affiliation":[{"name":"Shandong University Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, , Jinan, 250012 , China"},{"name":"Shandong University National Institute of Health Data Science of China, , Jinan, 250000 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yahui","family":"Wang","sequence":"additional","affiliation":[{"name":"Washington University in St. Louis Department of Chemistry, , St. Louis, MO, 63130 , USA"},{"name":"Washington University in St. Louis Center for Metabolomics and Isotope Tracing, , St. Louis, MO, 63130 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Ranran","family":"Chen","sequence":"additional","affiliation":[{"name":"Shandong University Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, , Jinan, 250012 , 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University Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, , Jinan, 250012 , China"},{"name":"Shandong University National Institute of Health Data Science of China, , Jinan, 250000 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gary J","family":"Patti","sequence":"additional","affiliation":[{"name":"Washington University in St. Louis Department of Chemistry, , St. Louis, MO, 63130 , USA"},{"name":"Washington University in St. Louis Department of Medicine, , St. Louis, MO, 63130 , USA"},{"name":"Washington University in St. Louis Siteman Cancer Center, , St. Louis, MO, 63130 , USA"},{"name":"Washington University in St. Louis Center for Metabolomics and Isotope Tracing, , St. Louis, MO, 63130 , USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leyi","family":"Wei","sequence":"additional","affiliation":[{"name":"Shandong University School of Software, , Jinan, 250100 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qingzhen","family":"Hou","sequence":"additional","affiliation":[{"name":"Shandong University Department of Biostatistics, School of Public Health, Cheeloo College of Medicine, , Jinan, 250012 , China"},{"name":"Shandong University National Institute of Health Data Science of China, , Jinan, 250000 , China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"286","published-online":{"date-parts":[[2023,5,23]]},"reference":[{"key":"2023072020060561600_ref1","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1038\/nchembio.204","article-title":"A 21st century revisionist\u2019s view at a turning point in enzymology","volume":"5","author":"Nagel","year":"2009","journal-title":"Nat Chem Biol"},{"key":"2023072020060561600_ref2","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1038\/s41580-019-0108-4","article-title":"Identification of bioactive metabolites using activity 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