Artificial intelligence in cancer target identification 1 and drug discovery

Yujie You, Xin Lai, Yi Pan, Huiru Zheng, Julio Vera, Suran Liu, Senyi Deng, Le Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as cancer. Here, we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover drugs. First, we describe the scope of artificial intelligence biology analysis for novel anticancer target investigations. Second, we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence algorithms. Finally, we showcase the applications of artificial intelligence approaches in cancer target identification and drug discovery. Taken together, the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer, thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.
Original languageEnglish
Article number156
Pages (from-to)1-24
Number of pages24
JournalSignal Transduction and Targeted Therapy
Volume7
Early online date10 May 2022
DOIs
Publication statusE-pub ahead of print - 10 May 2022

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