基于转录组数据分析的药物功能发现以及机制研究

    具有良好临床疗效的先导化合物发现是一个高风险、耗时、且花费高昂的过程。传统中药具有长期临床使用历史，包含了丰富的活性天然产物资源，具有广泛的疾病治疗潜力。然而由于中药的使用主要依靠经验的积累，特别是中药传统的多成分、多靶点整体作用特点，使其难以通过传统实验手段和方法解释其作用原理和机制，从而限制了传统中药的开发和推广。近年来高速发展的功能基因组学手段，比如基于高通量核酸测序的转录组学实验技术，以及对应的生物信息学计算分析方法，可以通过对大量的药物引起的基因表达数据进行挖掘以及整合，实现化合物功能和靶点、以及作用机制的高效研究。

    本文从生物信息学分析方法出发，整合实验室前期对来自人参，贝母，百部等药物中上百种天然产物诱导人体细胞后检测的近千个转录组测序数据进行深入功能挖掘分析。通过系统生物学的研究手段如聚类分析，富集分析， connectivity map分析等，结合现代药物诱导人体细胞后进行的转录组测序数据研究天然化合物的潜在作用靶点和机制。同时，我们将所有天然产物的大量分析结果整合成一个基于转录组的中药功能基因组学分析平台和数据库——MecoTCM，借此加速针对不同疾病先导化合物的计算机筛选。

    结合MecoTCM和新型冠状病毒感染后宿主转录组动态变化，我们从MecoTCM中筛选到一系列有抗新冠病毒潜力的化合物，并且通过体外细胞实验验证出13个具有抗新冠感染能力的化合物。更进一步地，我们通过MecoTCM的转录组通路研究数据对药物抗新冠的机制做了深入的分析，提出药物通过激活细胞内质网应激通路实现抑制新冠病毒复制感染的新机制。

    综上，本课题利用化合物诱导的转录组学数据，从生物信息学角度探索了高效预测天然化合物生物功能和作用机制的计算分析方法，为推动中药现代化进程提供了前沿的策略。

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