使用疾病特定的超图生成新的药物重新定位假设
Ayush Jain1, Marie-Laure Charpignon, Irene Y Chen
1Broad Institute of MIT and Harvard, Cambridge, MA, USA2Duke University, Durham, NC, USA†Corresponding author, a.jain@duke.edu.
Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing
|December 31, 2023
概括
这项研究引入了特定疾病的超图,以改善阿尔茨海默病 (AD) 的药物重定向. 这种新的方法可以识别出一些有前途的AD药物候选者,这些药物被当前的方法遗漏了,并提供了生物学上可信的途径.
科学领域:
- 计算生物学是一种计算生物学.
- 网络医学 网络医学
- 药理学 药理学是指药理学的学科.
背景情况:
- 药物开发是漫长而昂贵的;药物的重新利用提供了一个具有成本效益的替代方案.
- 目前用于药物重定向的基于网络的计算方法缺乏疾病特异性,可能会限制它们的有效性.
- 现有的互动组模型汇总疾病和相互作用数据,稀释识别相关药物点的关键信息.
研究的目的:
- 开发一种特定于疾病的计算方法,用于增强药物重定向.
- 通过结合特定疾病的生物途径来解决聚合网络模型的局限性.
- 通过支持生物逻辑,确定用于阿尔茨海默病 (AD) 的新药重定向候选药物.
主要方法:
- 构建特定疾病的超图,其中超边形代表生物通路.
- 使用修改的 node2vec 算法来生成路径嵌入.
- 评估了AD药物重定向的超图方法,将结果与最先进的知识图 (多尺度互动组) 进行比较.
主要成果:
- 确定了7种对阿尔茨海默病的有前途的药物改性候选药物.
- 这些候选人被评为不太可能的多尺度互动体,但得到了现有文献的支持.
- 该方法为药物重新定位建议提供了解释,突出了可信的生物途径.
结论:
- 疾病特定的超图代表了计算药物重定向的重大进步.
- 拟议的方法成功地确定了AD等复杂疾病的新疗法机会.
- 未来的工作包括扩大方法,以更广泛地覆盖疾病,并根据患者的并发症提供个性化的建议.
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