{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,17]],"date-time":"2026-03-17T07:59:50Z","timestamp":1773734390996,"version":"3.50.1"},"reference-count":37,"publisher":"Oxford University Press (OUP)","issue":"21","license":[{"start":{"date-parts":[[2021,8,6]],"date-time":"2021-08-06T00:00:00Z","timestamp":1628208000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"MELICOMO","award":["031B0358B"],"award-info":[{"award-number":["031B0358B"]}]},{"name":"German Federal Ministry of Science and Education to Zoran Nikoloski"},{"name":"European Union's Horizon 2020 research and innovation programme","award":["862201"],"award-info":[{"award-number":["862201"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,11,5]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:sec>\n                  <jats:title>Motivation<\/jats:title>\n                  <jats:p>Constraint-based modeling approaches allow the estimation of maximal in vivo enzyme catalytic rates that can serve as proxies for enzyme turnover numbers. Yet, genome-scale flux profiling remains a challenge in deploying these approaches to catalogue proxies for enzyme catalytic rates across organisms.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Results<\/jats:title>\n                  <jats:p>Here, we formulate a constraint-based approach, termed NIDLE-flux, to estimate fluxes at a genome-scale level by using the principle of efficient usage of expressed enzymes. Using proteomics data from Escherichia coli, we show that the fluxes estimated by NIDLE-flux and the existing approaches are in excellent qualitative agreement (Pearson correlation &amp;gt; 0.9). We also find that the maximal in vivo catalytic rates estimated by NIDLE-flux exhibits a Pearson correlation of 0.74 with in vitro enzyme turnover numbers. However, NIDLE-flux results in a 1.4-fold increase in the size of the estimated maximal in vivo catalytic rates in comparison to the contenders. Integration of the maximum in vivo catalytic rates with publically available proteomics and metabolomics data provide a better match to fluxes estimated by NIDLE-flux. Therefore, NIDLE-flux facilitates more effective usage of proteomics data to estimate proxies for kcatomes.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Availability and implementation<\/jats:title>\n                  <jats:p>https:\/\/github.com\/Rudan-X\/NIDLE-flux-code.<\/jats:p>\n               <\/jats:sec>\n               <jats:sec>\n                  <jats:title>Supplementary information<\/jats:title>\n                  <jats:p>Supplementary data are available at Bioinformatics online.<\/jats:p>\n               <\/jats:sec>","DOI":"10.1093\/bioinformatics\/btab575","type":"journal-article","created":{"date-parts":[[2021,8,4]],"date-time":"2021-08-04T11:56:40Z","timestamp":1628078200000},"page":"3848-3855","source":"Crossref","is-referenced-by-count":14,"title":["Maximization of non-idle enzymes improves the coverage of the estimated maximal <i>in vivo<\/i> enzyme catalytic rates in <i>Escherichia coli<\/i>"],"prefix":"10.1093","volume":"37","author":[{"given":"Rudan","family":"Xu","sequence":"first","affiliation":[{"name":"Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam , 14476 Potsdam, Germany"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5513-4677","authenticated-orcid":false,"given":"Zahra","family":"Razaghi-Moghadam","sequence":"additional","affiliation":[{"name":"Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam , 14476 Potsdam, Germany"},{"name":"Systems Biology and Mathematical Modelling Group, Max Planck Institute of Molecular Plant Physiology , 14476 Potsdam, Germany"}]},{"given":"Zoran","family":"Nikoloski","sequence":"additional","affiliation":[{"name":"Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam , 14476 Potsdam, Germany"},{"name":"Systems Biology and Mathematical Modelling Group, Max Planck Institute of Molecular Plant Physiology , 14476 Potsdam, Germany"}]}],"member":"286","published-online":{"date-parts":[[2021,8,6]]},"reference":[{"key":"2023051608255400100_btab575-B1","doi-asserted-by":"crossref","first-page":"e1002575","DOI":"10.1371\/journal.pcbi.1002575","article-title":"Prediction of microbial growth rate versus biomass yield by a metabolic network with kinetic parameters","volume":"8","author":"Adadi","year":"2012","journal-title":"PLoS Comput. 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