Data sharing in PredRet for accurate prediction of retention time: Application to plant food bioactive compounds

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61388971%3A_____%2F21%3A00543397" target="_blank" >RIV/61388971:_____/21:00543397 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0308814621007639?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0308814621007639?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.foodchem.2021.129757" target="_blank" >10.1016/j.foodchem.2021.129757</a>

Result language
angličtina
Original language name
Data sharing in PredRet for accurate prediction of retention time: Application to plant food bioactive compounds
Original language description
Prediction of retention times (RTs) is increasingly considered in untargeted metabolomics to complement MS/MS matching for annotation of unidentified peaks. We tested the performance of PredRet (http://predret.org/) to & nbsp.predict RTs for plant food bioactive metabolites in a data sharing initiative containing entry sets of 29 & ndash,103 compounds (totalling 467 compounds, >30 families) across 24 chromatographic systems (CSs). Between 27 and 667 predictions were obtained with a median prediction error of 0.03 & ndash,0.76 min and interval width of 0.33 & ndash,8.78 min. An external validation test of eight CSs showed high prediction accuracy. RT prediction was dependent on shape and type of LC gradient, and number of commonly measured compounds. Our study highlights PredRet & rsquo, s accuracy and ability to transpose RT data acquired from one CS to another CS. We recommend extensive RT data sharing in PredRet by the community interested in plant food bioactive metabolites to achieve a powerful community-driven open-access tool for metabolomics annotation.
Czech name
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Czech description
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Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
10406 - Analytical chemistry

Project
<a href="/en/project/GA19-00043S" target="_blank" >GA19-00043S: Aryl-sulfotransferases and their application in sulfated metabolite preparation</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2021
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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