Attention is all you need: utilizing attention in AI-enabled drug discovery
Chengdu University of Traditional Chinese Medicine · Harbin Medical University · +7 more institutions
Abstract
Recently, attention mechanism and derived models have gained significant traction in drug development due to their outstanding performance and interpretability in handling complex data structures. This review offers an in-depth exploration of the principles underlying attention-based models and their advantages in drug discovery. We further elaborate on their applications in various aspects of drug development, from molecular screening and target binding to property prediction and molecule generation. Finally, we discuss the current challenges faced in the application of attention mechanisms and Artificial Intelligence technologies, including data quality, model interpretability and computational resource…
Citation impact
- FWCI
- 67.77
- Percentile
- 100%
- References
- 233
Authors
7- YZYang Zhang
Chengdu University of Traditional Chinese Medicine
- CLCaiqi Liu
Harbin Medical University, Third Affiliated Hospital of Harbin Medical University
- MLMujiexin Liu
Chengdu University of Traditional Chinese Medicine
- TLTianyuan Liu
University of Tsukuba
- HLHao LinCorresponding
University of Electronic Science and Technology of China
Topics & keywords
- Pace
- Interpretability
- Drug discovery
- Computer science
- Data science
- Resource (disambiguation)
- Drug development
- Domain (mathematical analysis)