Automated Author Profile

Rønsted, Nina

Natural History Museum Aarhus

Current S-Index

0.8

Sum of Dataset Indices for all datasets

Average Dataset Index per Dataset

0.8

Average Dataset Index per dataset

Total Datasets

1

Total datasets for this author

Average FAIR Score

76.9%

Average FAIR Score per dataset

Total Citations

2

Total citations to the author's datasets

Total Mentions

0

Total mentions of the author's datasets

S-Index Interpretation

S-Index Over Time

Cumulative Citations Over Time

Cumulative Mentions Over Time

Datasets

Data from: Evolutionary prediction of medicinal properties in the genus Euphorbia L. (Version: 2)

The current decrease of new drugs brought to the market has fostered renewed interest in plant-based drug discovery. Given the alarming rate of biodiversity loss, systematic methodologies in finding new plant-derived drugs are urgently needed. Medicinal uses of plants were proposed as proxy for bioactivity, and phylogenetic patterns in medicinal plant uses have suggested that phylogeny can be used as predictive tool. However, the common practice of grouping medicinal plant uses into standardised categories may restrict the relevance of phylogenetic predictions. Standardised categories are mostly associated to systems of the human body and only poorly reflect biological responses to the treatment. Here we show that medicinal plant uses interpreted from a perspective of a biological response can reveal different phylogenetic patterns of presumed underlying bioactivity compared to standardised methods of medicinal plant use classification. In the cosmopolitan and pharmaceutically highly relevant genus Euphorbia L., identifying plant uses modulating the inflammatory response highlighted a greater phylogenetic diversity and number of potentially promising species than standardised categories. Our interpretation of medicinal plant uses may therefore allow for a more targeted approach for future phylogeny-guided drug discovery at an early screening stage, which will likely result in higher discovery rates of novel chemistry with functional biological activity.

Authors

  • Ernst, Madeleine ;
  • Saslis-Lagoudakis, C. Haris ;
  • Grace, Olwen M. ;
  • Nilsson, Niclas ;
  • Simonsen, Henrik Toft ;
  • Horn, James W. ;
  • Rønsted, Nina
2 Citations0 Mentions77% FAIR1.1 Dataset Index
10.5061/dryad.s2df32016