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Inventa: A computational tool to discover structural novelty in natural extracts libraries
Collections of natural extracts hold potential for the discovery of novel natural products with original modes of action. The prioritization of extracts from collections remains challenging due to the lack of a workflow that combines multiple-source information to facilitate the data interpretation....
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9692083/ https://www.ncbi.nlm.nih.gov/pubmed/36438653 http://dx.doi.org/10.3389/fmolb.2022.1028334 |
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author | Quiros-Guerrero, Luis-Manuel Nothias, Louis-Félix Gaudry, Arnaud Marcourt, Laurence Allard, Pierre-Marie Rutz, Adriano David, Bruno Queiroz, Emerson Ferreira Wolfender, Jean-Luc |
author_facet | Quiros-Guerrero, Luis-Manuel Nothias, Louis-Félix Gaudry, Arnaud Marcourt, Laurence Allard, Pierre-Marie Rutz, Adriano David, Bruno Queiroz, Emerson Ferreira Wolfender, Jean-Luc |
author_sort | Quiros-Guerrero, Luis-Manuel |
collection | PubMed |
description | Collections of natural extracts hold potential for the discovery of novel natural products with original modes of action. The prioritization of extracts from collections remains challenging due to the lack of a workflow that combines multiple-source information to facilitate the data interpretation. Results from different analytical techniques and literature reports need to be organized, processed, and interpreted to enable optimal decision-making for extracts prioritization. Here, we introduce Inventa, a computational tool that highlights the structural novelty potential within extracts, considering untargeted mass spectrometry data, spectral annotation, and literature reports. Based on this information, Inventa calculates multiple scores that inform their structural potential. Thus, Inventa has the potential to accelerate new natural products discovery. Inventa was applied to a set of plants from the Celastraceae family as a proof of concept. The Pristimera indica (Willd.) A.C.Sm roots extract was highlighted as a promising source of potentially novel compounds. Its phytochemical investigation resulted in the isolation and de novo characterization of thirteen new dihydro-β-agarofuran sesquiterpenes, five of them presenting a new 9-oxodihydro-β-agarofuran base scaffold. |
format | Online Article Text |
id | pubmed-9692083 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96920832022-11-26 Inventa: A computational tool to discover structural novelty in natural extracts libraries Quiros-Guerrero, Luis-Manuel Nothias, Louis-Félix Gaudry, Arnaud Marcourt, Laurence Allard, Pierre-Marie Rutz, Adriano David, Bruno Queiroz, Emerson Ferreira Wolfender, Jean-Luc Front Mol Biosci Molecular Biosciences Collections of natural extracts hold potential for the discovery of novel natural products with original modes of action. The prioritization of extracts from collections remains challenging due to the lack of a workflow that combines multiple-source information to facilitate the data interpretation. Results from different analytical techniques and literature reports need to be organized, processed, and interpreted to enable optimal decision-making for extracts prioritization. Here, we introduce Inventa, a computational tool that highlights the structural novelty potential within extracts, considering untargeted mass spectrometry data, spectral annotation, and literature reports. Based on this information, Inventa calculates multiple scores that inform their structural potential. Thus, Inventa has the potential to accelerate new natural products discovery. Inventa was applied to a set of plants from the Celastraceae family as a proof of concept. The Pristimera indica (Willd.) A.C.Sm roots extract was highlighted as a promising source of potentially novel compounds. Its phytochemical investigation resulted in the isolation and de novo characterization of thirteen new dihydro-β-agarofuran sesquiterpenes, five of them presenting a new 9-oxodihydro-β-agarofuran base scaffold. Frontiers Media S.A. 2022-11-11 /pmc/articles/PMC9692083/ /pubmed/36438653 http://dx.doi.org/10.3389/fmolb.2022.1028334 Text en Copyright © 2022 Quiros-Guerrero, Nothias, Gaudry, Marcourt, Allard, Rutz, David, Queiroz and Wolfender. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Molecular Biosciences Quiros-Guerrero, Luis-Manuel Nothias, Louis-Félix Gaudry, Arnaud Marcourt, Laurence Allard, Pierre-Marie Rutz, Adriano David, Bruno Queiroz, Emerson Ferreira Wolfender, Jean-Luc Inventa: A computational tool to discover structural novelty in natural extracts libraries |
title |
Inventa: A computational tool to discover structural novelty in natural extracts libraries |
title_full |
Inventa: A computational tool to discover structural novelty in natural extracts libraries |
title_fullStr |
Inventa: A computational tool to discover structural novelty in natural extracts libraries |
title_full_unstemmed |
Inventa: A computational tool to discover structural novelty in natural extracts libraries |
title_short |
Inventa: A computational tool to discover structural novelty in natural extracts libraries |
title_sort | inventa: a computational tool to discover structural novelty in natural extracts libraries |
topic | Molecular Biosciences |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9692083/ https://www.ncbi.nlm.nih.gov/pubmed/36438653 http://dx.doi.org/10.3389/fmolb.2022.1028334 |
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