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Building Block Extractor: An MS/MS Data Mining Tool for Targeted Discovery of Natural Products with Specified Features

文献类型：期刊论文

作者Zhu, Dafu1,2,3; Yuan, Jie4; Yue, Quanqi5; Zhao, Yinggong5; Yu, Shan1,3; Zhamilya, Abilova3; Jenis, Janar6; Tang, Chunping3; Wang, Bo7; Liu, Jia4,8
刊名ANALYTICAL CHEMISTRY
出版日期2023-07-10
页码8
ISSN号0003-2700
DOI10.1021/acs.analchem.3c00744
通讯作者Wang, Bo(wangbo1@bmi.ac.cn) ; Liu, Jia(jia.liu@simm.ac.cn) ; Ye, Yang(yye@simm.ac.cn)
英文摘要The utilization of a building-block-based molecular networkisan efficient approach to investigate the unknown chemical space ofnatural products. However, structure-based automated MS/MS data miningremains challenging. This study introduces building block extractor,a user-friendly MS/MS data mining program that automatically extractsuser-defined specified features. In addition to the characteristicproduct ions and neutral losses, this program integrates the abundanceof the product ions and sequential neutral loss features as buildingblocks for the first time. The discovery of nine undescribed sesquiterpenoiddimers from Artemisia heptapotamica highlights the power of this tool. One of these dimers, artemiheptolideI (9), exhibited in vitro inhibitionof influenza A/Hongkong/8/68 (H3N2) with an IC50 of 8.01 & PLUSMN; 6.19 & mu;M. Furthermore, two known guaianolide derivatives(16 and 17) possessed remarkable antiviralactivity against influenza A/Puerto Rico/8/1934 H1N1, H3N2, and influenzaB/Lee/40 with IC50 values ranging from 3.46 to 11.77 & mu;M.In addition to the efficient discovery of novel natural products,this strategy can be generally applied to grab derivatives with specificfragments and enhance the annotation power of LC-MS/MS analysis.
WOS关键词SOFTWARE
资助项目International Partnership Program of Chinese Academy of Sciences[153631KYSB20160004] ; National Natural Science Foundation of China[81573305] ; National Natural Science Foundation of China[81673327] ; Key Area Research and Development Program of Guangdong Province[2020B0303070002] ; Ministry of Education and Science of the Republic of Kazakhstan[0118PK00458]
WOS研究方向Chemistry
语种英语
出版者AMER CHEMICAL SOC
WOS记录号WOS:001024312000001
源URL[http://119.78.100.183/handle/2S10ELR8/306427]  
专题新药研究国家重点实验室
通讯作者Wang, Bo; Liu, Jia; Ye, Yang
作者单位1.Univ Chinese Acad Sci, Beijing 100049, Peoples R China
2.ShanghaiTech Univ, Sch Life Sci & Technol, Shanghai 201203, Peoples R China
3.Chinese Acad Sci, Shanghai Inst Mat Med, Nat Prod Chem Dept, State Key Lab Drug Res, Shanghai 201203, Peoples R China
4.Chinese Acad Sci, Shanghai Inst Mat Med, Shanghai 201203, Peoples R China
5.China ChemBioX Co Ltd, Shanghai 201100, Peoples R China
6.Al Farabi Kazakh Natl Univ, Res Ctr Med Plants, Al-Farabi Ave 71, Alma Ata 050040, Kazakhstan
7.Beijing Inst Pharmacol & Toxicol, State Key Lab Toxicol & Med Countermeasures, Beijing 100850, Peoples R China
8.Univ Chinese Acad Sci, Hangzhou Inst Adv Study, Sch Pharmaceut Sci & Technol, Hangzhou 310058, Peoples R China
推荐引用方式
GB/T 7714		 Zhu, Dafu,Yuan, Jie,Yue, Quanqi,et al. Building Block Extractor: An MS/MS Data Mining Tool for Targeted Discovery of Natural Products with Specified Features[J]. ANALYTICAL CHEMISTRY,2023:8.
APA Zhu, Dafu.,Yuan, Jie.,Yue, Quanqi.,Zhao, Yinggong.,Yu, Shan.,...&Ye, Yang.(2023).Building Block Extractor: An MS/MS Data Mining Tool for Targeted Discovery of Natural Products with Specified Features.ANALYTICAL CHEMISTRY,8.
MLA Zhu, Dafu,et al."Building Block Extractor: An MS/MS Data Mining Tool for Targeted Discovery of Natural Products with Specified Features".ANALYTICAL CHEMISTRY (2023):8.

入库方式： OAI收割

来源：上海药物研究所

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