{"title":"药用植物原料代谢组学研究","authors":"O. S. Popova","doi":"10.52419/issn2782-6252.2023.3.122","DOIUrl":null,"url":null,"abstract":"Every year, medicinal plant raw materials are increasingly found in the production of medicines. Despite a number of positive properties of plants and raw materials obtained from them, there are also negative aspects of the introduction of native (natural) drugs. For example, biological active substances, their quantity and activity, depend on the season of the year and the climatic conditions of the region. These factors are highly variable, and correlations of biologically active substances with weather are difficult to predict. Thus, only with the help of modern analytical instruments and validated methods can it be possible to create statistically reliable algorithms for searching for biologically active substances. The polythematic abstract and bibliographic database has been analyzed. The main attention was paid to such scientometric databases as: Web of Science Core Collection, Medline, PubMed, RSCI, as well as data from the eLIBRARY.ru portal over the past 10 years. An assessment was made of the statistical data and publication activity of the authors regarding the request for metabolomics of medicinal plant raw materials in medicine and veterinary medicine. Metabolomic studies of medicinal plants aim to provide a complete and accurate study of all small molecule metabolites and complement other omics technologies such as genomics, transcriptomics and proteomics. Based on the literature reviewed, it can be concluded that there are two main approaches to collecting metabolomic data: targeted and untargeted analysis. Targeted and untargeted metabolomics analyzes are similar in sample collection, preparation, and chromatographic conditions (stationary phase and mobile phase). 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引用次数: 0
摘要
每年,越来越多的药用植物原料被用于药品生产。尽管植物和从中获得的原料具有许多积极的特性,但引入本地(天然)药物也有消极的方面。例如,生物活性物质的数量和活性取决于一年中的季节和该地区的气候条件。这些因素变化很大,生物活性物质与天气的相关性很难预测。因此,只有借助现代分析仪器和经过验证的方法,才有可能创建统计可靠的算法来搜索生物活性物质。对多专题摘要和书目数据库进行了分析。主要关注的是Web of Science Core Collection、Medline、PubMed、RSCI等科学计量数据库,以及eLIBRARY.ru门户网站过去10年的数据。对作者对药用植物原料代谢组学要求的统计数据和发表活动进行了评价。药用植物代谢组学研究旨在为所有小分子代谢物提供完整和准确的研究,并补充其他组学技术,如基因组学、转录组学和蛋白质组学。根据文献综述,代谢组学数据的收集主要有两种方法:靶向分析和非靶向分析。靶向和非靶向代谢组学分析在样品收集、制备和色谱条件(固定相和流动相)方面是相似的。然而,靶向代谢组学研究主要关注来自相同或不同途径的多种代谢物。
Metabolomic studies for medicinal plant raw materials
Every year, medicinal plant raw materials are increasingly found in the production of medicines. Despite a number of positive properties of plants and raw materials obtained from them, there are also negative aspects of the introduction of native (natural) drugs. For example, biological active substances, their quantity and activity, depend on the season of the year and the climatic conditions of the region. These factors are highly variable, and correlations of biologically active substances with weather are difficult to predict. Thus, only with the help of modern analytical instruments and validated methods can it be possible to create statistically reliable algorithms for searching for biologically active substances. The polythematic abstract and bibliographic database has been analyzed. The main attention was paid to such scientometric databases as: Web of Science Core Collection, Medline, PubMed, RSCI, as well as data from the eLIBRARY.ru portal over the past 10 years. An assessment was made of the statistical data and publication activity of the authors regarding the request for metabolomics of medicinal plant raw materials in medicine and veterinary medicine. Metabolomic studies of medicinal plants aim to provide a complete and accurate study of all small molecule metabolites and complement other omics technologies such as genomics, transcriptomics and proteomics. Based on the literature reviewed, it can be concluded that there are two main approaches to collecting metabolomic data: targeted and untargeted analysis. Targeted and untargeted metabolomics analyzes are similar in sample collection, preparation, and chromatographic conditions (stationary phase and mobile phase). However, targeted metabolomics studies mainly focus on multiple metabolites from the same or different pathways.