Sarah Szwarc, Adriano Rutz, Kyungha Lee, Yassine Mejri, Olivier Bonnet, Hazrina Hazni, Adrien Jagora, Rany B. Mbeng Obame, Jin Kyoung Noh, Elvis Otogo N’Nang, Stephenie C. Alaribe, Khalijah Awang, Guillaume Bernadat, Young Hae Choi, Vincent Courdavault, Michel Frederich, Thomas Gaslonde, Florian Huber, Toh-Seok Kam, Yun Yee Low, Erwan Poupon, Justin J. J. van der Hooft, Kyo Bin Kang, Pierre Le Pogam, Mehdi A. Beniddir
{"title":"Translating community-wide spectral library into actionable chemical knowledge: a proof of concept with monoterpene indole alkaloids","authors":"Sarah Szwarc, Adriano Rutz, Kyungha Lee, Yassine Mejri, Olivier Bonnet, Hazrina Hazni, Adrien Jagora, Rany B. Mbeng Obame, Jin Kyoung Noh, Elvis Otogo N’Nang, Stephenie C. Alaribe, Khalijah Awang, Guillaume Bernadat, Young Hae Choi, Vincent Courdavault, Michel Frederich, Thomas Gaslonde, Florian Huber, Toh-Seok Kam, Yun Yee Low, Erwan Poupon, Justin J. J. van der Hooft, Kyo Bin Kang, Pierre Le Pogam, Mehdi A. Beniddir","doi":"10.1186/s13321-025-01009-0","DOIUrl":null,"url":null,"abstract":"<div><p>With over 3000 representatives, the monoterpene indole alkaloids (MIAs) class is among the most diverse families of plant natural products. The MS/MS spectral space exploration of these complex compounds using chemoinformatic and computational mass spectrometry tools offers a valuable opportunity to extract and share chemical insights from this emblematic family of natural products (NPs). In this work, we first present a substantially updated version of the MIADB, a database now containing 422 MS/MS spectra of MIAs that has been uploaded to the GNPS library versus 172 initial entries. We then introduce an innovative workflow that leverages hundreds of fragmentation spectra to support the FAIRification, extraction and dissemination of chemical knowledge. This workflow aims at the extraction of spectral patterns matching finely defined MIA skeletons. These extracted signatures can then be queried against complex biological extract datasets using MassQL. By applying this strategy to an LC-MS/MS dataset of 75 plant extracts, our results demonstrated the efficiency of this approach in identifying the diversity of MIA skeletons present in the analyzed samples. Additionally, our work enabled the digitization of structural data for diverse MIA skeletons by converting them into machine-readable formats and thereby enhancing their dissemination for the scientific community.</p><p><b>Scientific contribution</b> A comprehensive investigation of the monoterpene indole alkaloid chemical space, aiming to highlight skeleton-dependent fragmentation similarity trends and to generate valuable spectrometric signatures that could be used as queries.</p><h3>Graphical Abstract</h3>\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":617,"journal":{"name":"Journal of Cheminformatics","volume":"17 1","pages":""},"PeriodicalIF":7.1000,"publicationDate":"2025-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://jcheminf.biomedcentral.com/counter/pdf/10.1186/s13321-025-01009-0","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cheminformatics","FirstCategoryId":"92","ListUrlMain":"https://link.springer.com/article/10.1186/s13321-025-01009-0","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"CHEMISTRY, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
With over 3000 representatives, the monoterpene indole alkaloids (MIAs) class is among the most diverse families of plant natural products. The MS/MS spectral space exploration of these complex compounds using chemoinformatic and computational mass spectrometry tools offers a valuable opportunity to extract and share chemical insights from this emblematic family of natural products (NPs). In this work, we first present a substantially updated version of the MIADB, a database now containing 422 MS/MS spectra of MIAs that has been uploaded to the GNPS library versus 172 initial entries. We then introduce an innovative workflow that leverages hundreds of fragmentation spectra to support the FAIRification, extraction and dissemination of chemical knowledge. This workflow aims at the extraction of spectral patterns matching finely defined MIA skeletons. These extracted signatures can then be queried against complex biological extract datasets using MassQL. By applying this strategy to an LC-MS/MS dataset of 75 plant extracts, our results demonstrated the efficiency of this approach in identifying the diversity of MIA skeletons present in the analyzed samples. Additionally, our work enabled the digitization of structural data for diverse MIA skeletons by converting them into machine-readable formats and thereby enhancing their dissemination for the scientific community.
Scientific contribution A comprehensive investigation of the monoterpene indole alkaloid chemical space, aiming to highlight skeleton-dependent fragmentation similarity trends and to generate valuable spectrometric signatures that could be used as queries.
期刊介绍：
Journal of Cheminformatics is an open access journal publishing original peer-reviewed research in all aspects of cheminformatics and molecular modelling.
Coverage includes, but is not limited to:
chemical information systems, software and databases, and molecular modelling,
chemical structure representations and their use in structure, substructure, and similarity searching of chemical substance and chemical reaction databases,
computer and molecular graphics, computer-aided molecular design, expert systems, QSAR, and data mining techniques.
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