Open AccessConnecting Phenotype and Chemotype: High-Content Discovery Strategies for Natural Products Research
Author(s) -
Kenji L. Kurita,
Roger G. Linington
Publication year - 2015
Publication title -
journal of natural products
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.976
H-Index - 139
eISSN - 1520-6025
pISSN - 0163-3864
DOI - 10.1021/acs.jnatprod.5b00017
Subject(s) - profiling (computer programming) , chemotype , metabolite profiling , drug discovery , data science , computational biology , chemical space , computer science , biology , bioinformatics , metabolomics , food science , essential oil , operating system
In recent years, the field of natural products has seen an explosion in the breadth, resolution, and accuracy of profiling platforms for compound discovery, including many new chemical and biological annotation methods. With these new tools come opportunities to examine extract libraries using systematized profiling approaches that were not previously available to the field and which offer new approaches for the detailed characterization of the chemical and biological attributes of complex natural products mixtures. This review will present a summary of some of these untargeted profiling methods and provide perspective on the future opportunities offered by integrating these tools for novel natural products discovery.