Is it time for artificial intelligence to predict the function of natural products based on 2D-structure

Miaomiao Liu; Peter Karuso; Yunjiang Feng; Esther Kellenberger; Fei Liu; Can Wang; Ronald J. Quinn

doi:10.1039/C9MD00128J

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Is it time for artificial intelligence to predict the function of natural products based on 2D-structure

Miaomiao Liu,

^a Peter Karuso,

^b Yunjiang Feng,

^a Esther Kellenberger,

^c Fei Liu,

^b Can Wang

^d and Ronald J. Quinn

*^a

Author affiliations

* Corresponding authors

^a Griffith Institute for Drug Discovery, Griffith University, Brisbane, Australia
E-mail: r.quinn@griffith.edu.au
Tel: +61 7 3735 6006

^b Department of Molecular Sciences, Macquarie University, Sydney, NSW, Australia

^c Laboratory of Therapeutic Innovation, Medalis Drug Discovery Center, University of Strasbourg, Illkirch, France

^d School of Information and Communication Technology, Griffith University, Gold Coast campus, Qld 4222, Australia

Abstract

Currently, there is no established technique that allows the function of a compound produced by nature to be predicted by looking at its 2-dimensional chemical structure. One of chemistry's grand challenges: to find a function for every known metabolite. We explore the opportunity for Artificial Intelligence to provide rationale interrogation of metabolites to predict their function.

This article is part of the themed collection: Natural Products

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Article information

DOI: https://doi.org/10.1039/C9MD00128J
Article type: Review Article
Submitted: 02 Mar 2019
Accepted: 04 Jun 2019
First published: 06 Jun 2019

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Med. Chem. Commun., 2019,10, 1667-1677

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Is it time for artificial intelligence to predict the function of natural products based on 2D-structure

M. Liu, P. Karuso, Y. Feng, E. Kellenberger, F. Liu, C. Wang and R. J. Quinn, Med. Chem. Commun., 2019, 10, 1667 DOI: 10.1039/C9MD00128J

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Is it time for artificial intelligence to predict the function of natural products based on 2D-structure

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Is it time for artificial intelligence to predict the function of natural products based on 2D-structure

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