Nam-Chul Cho, SeongEun Hong, Jin Sook Song, EuiJu Yeo, SoI Jung, Yuno Lee, Seul Gee Hwang, Su Min Kang, JaeSung Hwang, Tae-Eun Jin
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引用次数: 0
Abstract
The Korea Chemical Bank (KCB) has generated a dataset containing metabolic stability data for approximately 4,000 compounds that have been tested on human and mouse liver microsomes. The first South Korea Data Challenge, named the Jump AI Challenge for Drug Discovery (JUMP AI 2023), was opened using the metabolic stability data of KCB in 2023. The objective of the JUMP AI 2023 was to promote and encourage the development of new drugs using artificial intelligence (AI) technology in South Korea. A total of 1254 teams participated in the competition, developing algorithms to estimate the remaining percentage of compounds after 30 min of incubation with human and mouse liver microsomes. The data set comprised training and test sets of 3498 and 483 compounds, respectively. This paper provides an overview of the JUMP AI 2023 and its outcomes, highlighting the diverse range of algorithms and artificial intelligence technologies employed by the competing teams. Among these, five teams stood out by utilizing GNN-based approaches winning awards. This competition was the first AI competition for drug discovery in South Korea, attracting numerous researchers and playing a key role in promoting drug research through the application of artificial intelligence technologies.
韩国化学银行(KCB)制作了包含在人类和小鼠肝微粒体上测试的4000多种化合物的代谢稳定性数据的数据集。第一届韩国数据挑战赛名为Jump AI药物发现挑战赛(Jump AI 2023),于2023年利用KCB的代谢稳定性数据开启。JUMP AI 2023的目标是促进和鼓励利用人工智能(AI)技术在韩国开发新药。共有1254个团队参加了比赛,开发算法来估计人类和小鼠肝微粒体孵育30分钟后化合物的剩余百分比。数据集分别由3498个化合物的训练集和483个化合物的测试集组成。本文概述了JUMP AI 2023及其成果,重点介绍了参赛团队采用的各种算法和人工智能技术。其中,5个团队利用基于gnn的方法脱颖而出,获得了奖项。此次大赛是韩国首次举办药物研发人工智能大赛,吸引了众多研究人员,在通过应用人工智能技术促进药物研究方面发挥了关键作用。
期刊介绍:
Journal of Cheminformatics is an open access journal publishing original peer-reviewed research in all aspects of cheminformatics and molecular modelling.
Coverage includes, but is not limited to:
chemical information systems, software and databases, and molecular modelling,
chemical structure representations and their use in structure, substructure, and similarity searching of chemical substance and chemical reaction databases,
computer and molecular graphics, computer-aided molecular design, expert systems, QSAR, and data mining techniques.