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Using evolutionary tools to search for novel psychoactive plants
Published online by Cambridge University Press: 25 October 2016
Abstract
Bioprospecting is the search for valuable products from natural sources. Given that most species are poorly known, a key question is where to search. Ethnodirected bioprospecting approaches use traditional knowledge in the process of selecting plants to screen for desired properties. A complementary approach is to utilize phylogenetic analyses based on traditional uses or known chemistry to identify lineages in which desired properties are most likely to be found. Novel discoveries of plant bioactivity from these approaches can aid the development of treatments for diseases with unmet medical needs. For example, neurological disorders are a growing concern, and psychoactive plants used in traditional medicine may provide botanical sources for bioactivity relevant for treating diseases related to the brain and nervous system. However, no systematic study has explored the diversity and phylogenetic distribution of psychoactive plants. We compiled a database of 501 psychoactive plant species and their properties from published sources. We mapped these plant attributes on a phylogenetic tree of all land plant genera and showed that psychoactive properties are not randomly distributed on the phylogeny of land plants; instead certain plant lineages show overabundance of psychoactive properties. Furthermore, employing a ‘hot nodes’ approach to identify these lineages, we can narrow down our search for novel psychoactive plants to 8.5% of all plant genera for psychoactivity in general and 1–4% for specific categories of psychoactivity investigated. Our results showcase the potential of using a phylogenetic approach to bioprospect plants for psychoactivity and can serve as foundation for future investigations.
- Type
- Research Article
- Information
- Plant Genetic Resources , Volume 14 , Special Issue 4: Evolving trends in plant based drug discovery , December 2016 , pp. 246 - 255
- Copyright
- Copyright © NIAB 2016
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