Natural product drug discovery in the artificial intelligence era

Abstract

Natural products (NPs) are primarily recognized as privileged structures to interact with protein drug targets. Their unique characteristics and structural diversity continue to marvel scientists for developing NP-inspired medicines, even though the pharmaceutical industry has largely given up. High-performance computer hardware, extensive storage, accessible software and affordable online education have democratized the use of artificial intelligence (AI) in many sectors and research areas. The last decades have introduced natural language processing and machine learning algorithms, two subfields of AI, to tackle NP drug discovery challenges and open up opportunities. In this article, we review and discuss the rational applications of AI approaches developed to assist in discovering bioactive NPs and capturing the molecular “patterns” of these privileged structures for combinatorial design or target selectivity.

Graphical abstract: Natural product drug discovery in the artificial intelligence era

Article information

Article type
Perspective
Submitted
13 Aug 2021
Accepted
10 Dec 2021
First published
13 Dec 2021
This article is Open Access

All publication charges for this article have been paid for by the Royal Society of Chemistry
Creative Commons BY-NC license

Chem. Sci., 2022, Advance Article

Natural product drug discovery in the artificial intelligence era

F. I. Saldívar-González, V. D. Aldas-Bulos, J. L. Medina-Franco and F. Plisson, Chem. Sci., 2022, Advance Article , DOI: 10.1039/D1SC04471K

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