Supporting data for "Open and re-usable annotated mass spectrometry dataset of a chemodiverse collection of 1,600 plant extracts."
收藏DataCite Commons2025-05-26 更新2025-04-15 收录
下载链接:
http://gigadb.org/dataset/102323
下载链接
链接失效反馈官方服务:
资源简介:
As privileged structures, natural products often display potent biological activities. However, the discovery of novel bioactive scaffolds is often hampered by the chemical complexity of the biological matrices they are found in. Large natural extracts collections are thus extremely valuable for their chemical novelty potential but also complicated to exploit in the frame of drug-discovery projects. In the end, it is the pure chemical substances that are desired for structural determination purposes and bioactivity evaluation. Researchers interested in the exploration of large and chemodiverse extracts collections should thus establish strategies aiming to efficiently tackle such chemical complexity and access these structures. Establishing carefully crafted digital layers documenting the spectral and chemical complexity as well as bioactivity results of natural products extracts collections can help to prioritize time-consuming but mandatory isolation efforts.<br>In this note, we report the results of our initial exploration of a collection of 1,600 plant extracts in the frame of a drug discovery effort. After describing the taxonomic coverage of this collection, we present the results of its liquid chromatography high-resolution mass spectrometric profiling and the exploitation of these profiles using computational solutions. The resulting annotated mass spectral dataset and associated chemical and taxonomic metadata are made available to the community and data reuse cases are proposed. We are currently continuing our exploration of this plant extracts collection for drug-discovery purposes (notably looking for novel anti-trypanosomatids, anti-infective and prometabolic compounds) and eco-metabolomics insights. We believe that such a dataset can be exploited and reused by researchers interested in computational natural products exploration.
提供机构:
GigaScience Database
创建时间:
2022-11-10



