Phylogenies reveal predictive power of traditional medicine in bioprospectingSaslis Lagoudakis, C.H., Savolainen, V., Williamson, L., Forest, F., Wagstaff, S., Baral, S.R., Watson, M., Pendry, C. and Hawkins, J. ORCID: https://orcid.org/0000-0002-9048-8016 (2012) Phylogenies reveal predictive power of traditional medicine in bioprospecting. Proceedings of the National Academy of Sciences of the United States of America, 109 (39). pp. 15835-15840. ISSN 1091-6490 Full text not archived in this repository. It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing. To link to this item DOI: 10.1073/pnas.1202242109 Abstract/SummaryThere is controversy about whether traditional medicine can guide drug discovery, and investment in ethnobotanically led research has fluctuated. One view is that traditionally used plants are not necessarily efficacious and there are no robust methods for distinguishing the ones that are most likely to be bioactive when selecting species for further testing. Here, we reconstruct a genus-level molecular phylogeny representing the 20,000 species found in the floras of three disparate biodiversity hotspots: Nepal, New Zealand and the Cape of South Africa. Borrowing phylogenetic methods from community ecology, we reveal significant clustering of the 1,500 traditionally used species, and provide a direct measure of the relatedness of the three medicinal floras. We demonstrate shared phylogenetic patterns across the floras: related plants from these regions are used to treat medical conditions in the same therapeutic areas. This strongly suggests independent discovery of plant efficacy, an interpretation corroborated by the presence of a significantly greater proportion of known bioactive species in these plant groups than in a random sample. Phylogenetic cross-cultural comparison can focus screening efforts on a subset of traditionally used plants that are richer in bioactive compounds, and could revitalise the use of traditional knowledge in bioprospecting.
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