Nowadays, the toxicity of traditional Chinese medicine (TCM) has aroused widespread concern. It is critical for the guidance of safe TCM medication that to quickly discover the toxic components of TCM. At present, there are three main problems on nephrotoxicity evaluation: Firstly, due to the absence of normal and complete physiological function in vitro, it can’t exactly reflect the state of the bodies. Secondly, traditional inspection methods are not sensitive enough for early discovery of toxic components. Thirdly, conventional toxicology methods can’t meet the requirements for high-throughput screening the chemical composition of TCM in entities library. Consequently, the discovery of overall sensitive toxicity evaluation index in early stage and high-throughput rapid screening of toxic components has been becoming an important means in discovering nephrotoxic components. In the present project, based on metabonomics which has unique advantages in sensitively evaluating the body damage in early stage caused by medicine and high throughput computational virtual screening features, a set of ‘early evaluation-computational toxicology virtual screening and verification’ key technologies in discovering nephrotoxic components of TCM have been constructed. On the basis of confirmed nephrotoxic components of TCM by overall animal models, virtual screening was utilized in combination of entity experimental verification on animal models to ultimately determine the biomarkers for early evaluation of nephrotoxicity, and to build the early safety warning database of nephrotoxic components of TCM. By successful completion of the present project, we can not only achieve quick discovery of toxic components of TCM from the overall animal models, and open up a new thought for the study of TCM safety pre-warning, but also provide indication for other key issues in TCM research areas such as disease prediction, discovery of therapeutic substances, etc.
当前中药毒性问题引起社会广泛关注,如何快速发现中药毒性成分,这对于指导临床安全用药至关重要。肾毒性研究主要存在三个问题:一是体外评价不能全面真实反映机体状态;二是传统检查方法对毒性早期评价不敏感;三是常规毒理学方法无法满足对中药化学成分高通量筛选的要求。为此,敏感的毒性整体早期评价指标和毒性物质高通量快速筛选是中药肾毒性成分发现的重要手段。本课题基于代谢组学早期、敏感评价机体损伤的独特优势和计算毒理学高通量虚拟筛选的特征,构建一套“毒性整体早期评价-计算毒理学虚拟筛选及验证”的毒性成分发现关键技术,在确定基于整体动物肾毒性早期评价生物标志物的基础上,虚拟筛选和实体动物验证相结合,建立中药肾毒性成分安全预警数据库。本课题的顺利完成不仅从动物整体水平上快速敏感的发现中药毒性成分,为中药安全预警开辟一条新的研究思路,而且还为中医药领域其他关键问题如疾病早期预测、药效物质发现等研究提供指示作用。
当前中药毒性问题引起社会广泛关注,中药毒性成分的快速发现及确认对于指导临床安全用药至关重要。本课题基于代谢组学早期、敏感评价机体损伤的独特优势和计算毒理学高通量虚拟筛选的特征,构建一套“毒性整体早期评价-计算毒理学虚拟筛选及验证”的毒性成分发现关键技术,在确定基于整体动物肾毒性早期评价生物标志物的基础上,虚拟筛选和实体动物验证相结合,建立中药肾毒性成分安全预警数据库。. 按照申请书内容,本课题计划取得如下进展:(1)建立了一套基于代谢组学技术的药物肾毒性整体预测与评价方法,筛选出5个与给药时间相关的肾毒性生物标志物,并建立肾毒性预测模型;(2)建立毒效团虚拟筛选模型,确定可能的中药肾毒性成分;(3)以代表性中药毒性成分开展代谢组学与蛋白质组学研究,并对其生物学机制进行阐述;(4)建立中药肾毒性成分安全预警数据库。以此为依据获批软件著作权1项。本课题的顺利完成不仅从动物整体水平上快速敏感的发现中药毒性成分,为中药安全预警开辟一条新的研究思路,而且还为中医药领域其他关键问题如疾病早期预测、药效物质发现等研究提供指示作用。. 发表SCI论文8篇,中文文章2篇。获得天津市科技进步二等奖1项,获中华中医药学会科学技术二等奖1项,获批天津市第三批人才发展特殊支持计划高层次创新团队,此外再投SCI论文2篇。
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数据更新时间:2023-05-31
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