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A Toolbox for the Identification of Modes of Action of Natural Products

  • Tiago RodriguesEmail author
Chapter
Part of the Progress in the Chemistry of Organic Natural Products book series (POGRCHEM, volume 110)

Abstract

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.

Keywords

Cheminformatics Machine learning Chemical biology Medicinal chemistry Natural products Drug discovery Target identification 

Notes

Acknowledgments

Tiago Rodrigues is a Marie Skłodowska-Curie Fellow (Grant 743640) and acknowledges the FCT/FEDER (02/SAICT/2017, Grant 28333) for funding.

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© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Chemical BiologyInstituto de Medicina Molecular João Lobo AntunesLisbonPortugal

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