Applications of Machine Learning in Drug Target Discovery

Author(s): Dongrui Gao, Qingyuan Chen, Yuanqi Zeng, Meng Jiang, Yongqing Zhang*

Journal Name: Current Drug Metabolism

Volume 21 , Issue 10 , 2020


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Abstract:

Drug target discovery is a critical step in drug development. It is the basis of modern drug development because it determines the target molecules related to specific diseases in advance. Predicting drug targets by computational methods saves a great deal of financial and material resources compared to in vitro experiments. Therefore, several computational methods for drug target discovery have been designed. Recently, machine learning (ML) methods in biomedicine have developed rapidly. In this paper, we present an overview of drug target discovery methods based on machine learning. Considering that some machine learning methods integrate network analysis to predict drug targets, network-based methods are also introduced in this article. Finally, the challenges and future outlook of drug target discovery are discussed.

Keywords: Drug target discovery, drug target interaction, machine learning, network-based methods, drug development, biomedicine.

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Article Details

VOLUME: 21
ISSUE: 10
Year: 2020
Published on: 15 December, 2020
Page: [790 - 803]
Pages: 14
DOI: 10.2174/1567201817999200728142023
Price: $65

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