Applications of Machine Learning in Drug Target Discovery

Dongrui       Gao; Qingyuan       Chen; Yuanqi       Zeng; Meng       Jiang; Yongqing       Zhang
doi:10.2174/1567201817999200728142023
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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DOI https://dx.doi.org/10.2174/1567201817999200728142023	Print ISSN 1389-2002
Publisher Name Bentham Science Publisher	Online ISSN 1875-5453
Current Drug Metabolism

Applications of Machine Learning in Drug Target Discovery

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