College of Life and Health Sciences, Northeastern University, Shenyang 110819, People's Republic of China.
Key Laboratory of Data Analytics and Optimization for Smart Industry (Northeastern University), Ministry of Education, Shenyang 110819, People's Republic of China.
STAR Protoc. 2021 Jul 7;2(3):100653. doi: 10.1016/j.xpro.2021.100653. eCollection 2021 Sep 17.
Drug repositioning represents a cost- and time-efficient strategy for drug development. Artificial intelligence-based algorithms have been applied in drug repositioning by predicting drug-target interactions in an efficient and high throughput manner. Here, we present a workflow of drug repositioning for host-based antivirals using specially defined targets, a refined list of drug candidates, and an easily implemented computational framework. The workflow described here can also apply to more general purposes, especially when given a user-defined druggable target gene set. For complete details on the use and execution of this protocol, please refer to Li et al. (2021).
药物重定位是一种具有成本效益和时间效益的药物开发策略。基于人工智能的算法已被应用于药物重定位，通过高效和高通量的方式预测药物-靶标相互作用。在这里，我们提出了一种使用专门定义的靶标、经过改进的候选药物列表和易于实现的计算框架的基于宿主的抗病毒药物重定位工作流程。这里描述的工作流程也可适用于更一般的用途，特别是在给定用户定义的可成药靶标基因集的情况下。有关此协议的使用和执行的完整详细信息，请参阅 Li 等人（2021 年）。
