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

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

Medchemcomm. 2019 Jun 6;10(10):1667-1677. doi: 10.1039/c9md00128j. eCollection 2019 Oct 1.

Authors

Miaomiao Liu¹, Peter Karuso², Yunjiang Feng¹, Esther Kellenberger³, Fei Liu², Can Wang⁴, Ronald J Quinn¹

Affiliations

¹ Griffith Institute for Drug Discovery , Griffith University , Brisbane , Qld 4111 , Australia . Email: r.quinn@griffith.edu.au ; Tel: +61 7 3735 6006.
² Department of Molecular Sciences , Macquarie University , Sydney , NSW 2109 , Australia.
³ Laboratory of Therapeutic Innovation , Medalis Drug Discovery Center , University of Strasbourg , Illkirch , France.
⁴ 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.

Publication types

Review