对冠状病毒的潜在目标发现和药物重新定位:研究涉及基于知识图的方法
Pei Lou1, An Fang1, Wanqing Zhao1
1Institute of Medical Information, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China.
Journal of medical Internet research
|October 20, 2023
概括
这项研究使用了知识图来识别潜在的药物标和针对冠状病毒的重定向药物,为未来的病毒性疾病研究提供了一种新方法.
科学领域:
- 生物医学信息学 生物医学信息学
- 计算生物学 计算生物学
- 病毒学 病毒学
背景情况:
- 由冠状病毒 (SARS,MERS,COVID-19) 引起的全球流行病突显出迫切需要有效的对策.
- 冠状病毒正在不断演变,构成未来疫情的持续威胁.
- 知识图为了解病毒病原性和传播机制提供了一个有希望的途径.
研究的目的:
- 为了发现冠状病毒的潜在治疗点.
- 为了确定针对冠状病毒的重新用途的候选药物.
- 利用基于知识图的方法来加速药物发现.
主要方法:
- 通过整合生物医学文献和现有知识库,构建了一个全面的冠状病毒知识图 (CovKG).
- 开发了一个语义转换模型,将提取的文献数据组织成语义三重组.
- 采用知识图嵌入和语义推理来发现新药机制,并确定潜在的目标和药物候选者.
主要成果:
- 该CovKG包含超过1700万个三位数,整合了各种生物医学信息.
- 语义推理确定了41种新的药物作用机制.
- 该研究确定了33种潜在的标和18种候选药物,包括7种新药和3种关键标 (ACE2,TMPRSS2,M蛋白).
结论:
- 证明了知识图的有效性,用于冠状病毒的目标发现和药物重定位.
- 该方法提供了一个适用于其他病毒和疾病的生物医学知识发现的框架.
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