RDKG-115:通过嵌入三模式知识图,协助对罕见疾病的药物重新定位和发现
Chaoyu Zhu1, Xiaoqiong Xia1, Nan Li2
1Intelligent Medicine Institute, Shanghai Medical College, Fudan University, Shanghai, 200032, China.
Computers in biology and medicine
|July 23, 2023
概括
这项研究介绍了RDKG-115,一种针对罕见疾病 (RDs) 的新型知识图,以及一种知识图嵌入 (KGE) 模型,以加速药物重定向. 这种方法可以识别罕见疾病的潜在新疗法,通过加速药物开发,使患者受益.
科学领域:
- 生物医学信息学 生物医学信息学
- 药理学 药理学是指药理学的学科.
- 基因组学就是基因组学.
背景情况:
- 由于诊断困难和治疗选择有限,罕见疾病 (RDs) 构成重大全球健康挑战.
- 传统的研发药物被高昂的成本,风险和漫长的时间限制了.
- 药物再利用提供了一个更有效的策略,利用现有的药物知识用于新的治疗应用.
研究的目的:
- 构建一个全面的罕见病知识图 (RDKG-115),整合各种生物医学数据.
- 开发和应用一个三模知识图嵌入 (KGE) 模型来预测新药与疾病的关系.
- 用多发性硬化症作为案例研究来确定115种罕见疾病的潜在药物改用候选者.
主要方法:
- 构建RDKG-115,一个包含35,643个实体和5,539,839个三重体的知识图,来自文学和生物医学数据集.
- 通过反向超平面投影开发一个包含结构,类别和描述嵌入的三模式KGE模型.
- 从RDKG-115推断了4,199个新的三胞胎,以预测药物重新利用的机会.
主要成果:
- RDKG-115知识图为罕见疾病研究提供了丰富的资源.
- 该KGE模型成功推断出了大量可靠的新关系.
- 针对115种罕见疾病确定了潜在的药物和小分子,证明了该模型在药物发现中的实用性.
结论:
- 开发的KGE方法提供了一种高效和方便的方法,用于在罕见疾病中重新定位药物.
- 这项研究建立了一个大规模查药物重定向候选人RDs的范式.
- 这些发现加速了药物开发管道,最终旨在改善罕见病患者的治疗结果.
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