{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,13]],"date-time":"2026-07-13T20:23:03Z","timestamp":1783974183443,"version":"3.55.0"},"update-to":[{"DOI":"10.1371\/journal.pcbi.1009550","type":"new_version","label":"New version","source":"publisher","updated":{"date-parts":[[2021,11,18]],"date-time":"2021-11-18T00:00:00Z","timestamp":1637193600000}}],"reference-count":54,"publisher":"Public Library of Science (PLoS)","issue":"11","license":[{"start":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T00:00:00Z","timestamp":1636329600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Italian Ministry of University and Research","award":["Dipartimenti di Eccellenza 2017"],"award-info":[{"award-number":["Dipartimenti di Eccellenza 2017"]}]}],"content-domain":{"domain":["www.ploscompbiol.org"],"crossmark-restriction":false},"short-container-title":["PLoS Comput Biol"],"abstract":"<jats:p>Metabolic network models are increasingly being used in health care and industry. As a consequence, many tools have been released to automate their reconstruction process<jats:italic>de novo<\/jats:italic>. In order to enable gene deletion simulations and integration of gene expression data, these networks must include gene-protein-reaction (GPR) rules, which describe with a Boolean logic relationships between the gene products (e.g., enzyme isoforms or subunits) associated with the catalysis of a given reaction. Nevertheless, the reconstruction of GPRs still remains a largely manual and time consuming process. Aiming at fully automating the reconstruction process of GPRs for any organism, we propose the open-source python-based framework<jats:monospace>GPRuler<\/jats:monospace>. By mining text and data from 9 different biological databases,<jats:monospace>GPRuler<\/jats:monospace>can reconstruct GPRs starting either from just the name of the target organism or from an existing metabolic model. The performance of the developed tool is evaluated at small-scale level for a manually curated metabolic model, and at genome-scale level for three metabolic models related to<jats:italic>Homo sapiens<\/jats:italic>and<jats:italic>Saccharomyces cerevisiae<\/jats:italic>organisms. By exploiting these models as benchmarks, the proposed tool shown its ability to reproduce the original GPR rules with a high level of accuracy. In all the tested scenarios, after a manual investigation of the mismatches between the rules proposed by<jats:monospace>GPRuler<\/jats:monospace>and the original ones, the proposed approach revealed to be in many cases more accurate than the original models. By complementing existing tools for metabolic network reconstruction with the possibility to reconstruct GPRs quickly and with a few resources,<jats:monospace>GPRuler<\/jats:monospace>paves the way to the study of context-specific metabolic networks, representing the active portion of the complete network in given conditions, for organisms of industrial or biomedical interest that have not been characterized metabolically yet.<\/jats:p>","DOI":"10.1371\/journal.pcbi.1009550","type":"journal-article","created":{"date-parts":[[2021,11,8]],"date-time":"2021-11-08T18:42:42Z","timestamp":1636396962000},"page":"e1009550","update-policy":"https:\/\/doi.org\/10.1371\/journal.pcbi.corrections_policy","source":"Crossref","is-referenced-by-count":22,"title":["GPRuler: Metabolic gene-protein-reaction rules automatic reconstruction"],"prefix":"10.1371","volume":"17","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7428-0522","authenticated-orcid":true,"given":"Marzia","family":"Di Filippo","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5742-8302","authenticated-orcid":true,"given":"Chiara","family":"Damiani","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3090-4823","authenticated-orcid":true,"given":"Dario","family":"Pescini","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"340","published-online":{"date-parts":[[2021,11,8]]},"reference":[{"issue":"5","key":"pcbi.1009550.ref001","doi-asserted-by":"crossref","first-page":"971","DOI":"10.1016\/j.cell.2015.05.019","article-title":"Using genome-scale models to predict biological capabilities","volume":"161","author":"EJ O\u2019Brien","year":"2015","journal-title":"Cell"},{"key":"pcbi.1009550.ref002","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/j.copbio.2014.12.020","article-title":"The widespread role of non-enzymatic reactions in cellular metabolism","volume":"34","author":"MA Keller","year":"2015","journal-title":"Current opinion in biotechnology"},{"key":"pcbi.1009550.ref003","article-title":"Protein isoforms and isozymes","author":"PW Gunning","year":"2005","journal-title":"eLS"},{"issue":"D1","key":"pcbi.1009550.ref004","doi-asserted-by":"crossref","first-page":"D457","DOI":"10.1093\/nar\/gkv1070","article-title":"KEGG as a reference resource for gene and protein annotation","volume":"44","author":"M Kanehisa","year":"2016","journal-title":"Nucleic Acids Research"},{"issue":"D1","key":"pcbi.1009550.ref005","doi-asserted-by":"crossref","first-page":"D506","DOI":"10.1093\/nar\/gky1049","article-title":"UniProt: a worldwide hub of protein knowledge","volume":"47","author":"Consortium UniProt","year":"2019","journal-title":"Nucleic acids research"},{"issue":"D1","key":"pcbi.1009550.ref006","doi-asserted-by":"crossref","first-page":"D607","DOI":"10.1093\/nar\/gky1131","article-title":"STRING v11: protein\u2013protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets","volume":"47","author":"D Szklarczyk","year":"2019","journal-title":"Nucleic acids research"},{"issue":"D1","key":"pcbi.1009550.ref007","doi-asserted-by":"crossref","first-page":"D445","DOI":"10.1093\/nar\/gkz862","article-title":"The MetaCyc database of metabolic pathways and enzymes-a 2019 update","volume":"48","author":"R Caspi","year":"2020","journal-title":"Nucleic Acids Research"},{"issue":"1","key":"pcbi.1009550.ref008","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s13068-014-0144-4","article-title":"Capturing the response of Clostridium acetobutylicum to chemical stressors using a regulated genome-scale metabolic model","volume":"7","author":"S Dash","year":"2014","journal-title":"Biotechnology for biofuels"},{"issue":"1","key":"pcbi.1009550.ref009","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1104\/pp.16.01487","article-title":"A comprehensively curated genome-scale two-cell model for the heterocystous cyanobacterium Anabaena sp. 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