Natural products have long played a leading role as direct source of drugs or as a means to inspire informed molecular design. Indeed, natural products have been biologically prevalidated as protein-binding motifs by millions of years of evolutionary pressure. Despite the tailored architectures, and the ever-growing chemistry toolbox to aid access such privileged structures, identifying the modes of action by which these molecules can be harnessed as therapeutics remains a major bottleneck in discovery chemistry. Herein, an overview of cheminformatics methods applied to the identification of modes of action of natural products is given, and a discussion of successful case studies is provided. A special focus is given to machine learning methods that may help to streamline the development of natural products into drug leads.
CITATION STYLE
Rodrigues, T. (2019). A Toolbox for the Identification of Modes of Action of Natural Products. In Progress in the Chemistry of Organic Natural Products (Vol. 110, pp. 73–97). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-14632-0_3
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