College of Computer Science, Sichuan University, Chengdu, 610065, China.
Laboratory of Systems Tumor Immunology, Friedrich-Alexander-Universität Erlangen-Nürnberg (FAU) and Universitätsklinikum Erlangen, Erlangen, 91052, Germany.
Signal Transduct Target Ther. 2022 May 10;7(1):156. doi: 10.1038/s41392-022-00994-0.
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.
人工智能是一种从生物学网络中识别新型抗癌靶点和发现新型药物的先进方法,因为这些网络可以有效地保存和量化人类疾病(如癌症)细胞系统成分之间的相互作用。在这里,我们将回顾和讨论如何利用人工智能方法来识别新型抗癌靶点和发现药物。首先,我们描述了人工智能生物学分析在新型抗癌靶点研究中的应用范围。其次,我们回顾和讨论了常用的基于网络和基于机器学习的人工智能算法的基本原理和理论。最后,我们展示了人工智能方法在癌症靶点识别和药物发现中的应用。总之,人工智能模型为我们提供了一个定量框架来研究网络特征与癌症之间的关系,从而识别潜在的抗癌靶点和发现新型药物候选物。