期刊
NATURE COMMUNICATIONS
卷 12, 期 1, 页码 -出版社
NATURE PORTFOLIO
DOI: 10.1038/s41467-021-21770-8
关键词
-
资金
- National Science Foundation [DGE-1656518]
- Stanford Enhancing Diversity in Graduate Education (EDGE) Fellowship
- NSF [IIS311 2030459, IIS-2033384, OAC-1835598, OAC-1934578, CCF-1918940, IIS-2030477]
- Harvard Data Science Initiative
- DARPA [N660011924033]
- ARO [W911NF-16-1-0342, W911NF-16-1-0171]
- Stanford Data Science Initiative
- Wu Tsai Neurosciences Institute
- Chan Zuckerberg Biohub
- Amazon
- JPMorgan Chase
- Docomo
- Hitachi
- JD.com
- KDDI
- NVIDIA
- Dell
- Toshiba
- UnitedHealth Group
This study introduces a multiscale interactome approach to explain disease treatment by integrating disease-perturbed proteins, drug targets, and biological functions into a network. Through a random walk-based method, the authors successfully predict drug-disease treatment, identify proteins and functions related to treatment, and predict genes influencing treatment efficacy and adverse reactions. The results show that drugs often treat diseases by influencing disrupted biological functions rather than directly targeting disease proteins, providing a general framework for understanding treatment mechanisms.
Most diseases disrupt multiple proteins, and drugs treat such diseases by restoring the functions of the disrupted proteins. How drugs restore these functions, however, is often unknown as a drug's therapeutic effects are not limited to the proteins that the drug directly targets. Here, we develop the multiscale interactome, a powerful approach to explain disease treatment. We integrate disease-perturbed proteins, drug targets, and biological functions into a multiscale interactome network. We then develop a random walk-based method that captures how drug effects propagate through a hierarchy of biological functions and physical protein-protein interactions. On three key pharmacological tasks, the multiscale interactome predicts drug-disease treatment, identifies proteins and biological functions related to treatment, and predicts genes that alter a treatment's efficacy and adverse reactions. Our results indicate that physical interactions between proteins alone cannot explain treatment since many drugs treat diseases by affecting the biological functions disrupted by the disease rather than directly targeting disease proteins or their regulators. We provide a general framework for explaining treatment, even when drugs seem unrelated to the diseases they are recommended for. Most diseases disrupt multiple proteins, and drugs treat such diseases by restoring the functions of the disrupted proteins; how drugs restore these functions, however, is often unknown. Here, the authors develop the multiscale interactome, a powerful approach to explain disease treatment.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据