实验技术与管理2025，Vol.42Issue(3)：80-87,8.DOI:10.16791/j.cnki.sjg.2025.03.010
采用GNPS-分子网络技术快速发掘天然除草剂aspterric acid类似物
Rapid discovery of the analogs of natural herbicide aspterric acid using GNPS molecular networking technology
摘要
Abstract
[Objective]Owing to the lack of effective,guided separation technology in traditional natural product research,the separation work is blind,random,and repetitive,which greatly wastes manpower and resources.Tandem mass spectrum-molecular networking based on the open-source database of Global Natural Products Social Molecular Networking(GNPS)is an effective strategy for rapidly identifying known natural products and discovering novel structures.Aspterric acid(AA)is a natural herbicide,a novel target discovered from the strain of Aspergillus terreus,that has aroused widespread attention.This comprehensive experiment combines cutting-edge research discoveries with new technologies in the course of"Natural Product Chemistry"to design innovative experiments for college students.The analogs of AA were isolated from the marine fungus Penicillium javanicum HK1-22,guided by GNPS molecular networking technology.The results of this experiment could provide more abundant candidate template molecules for the screening of new natural herbicides.[Methods]This fungus was fermented using a PDB medium on a large scale,and its secondary metabolites were then obtained by organic solvent extraction.The fungal crude extracts were analyzed using high-performance liquid chromatography and then with an automated full-dependent MS/MS scan.All MS/MS data were converted to the MZML format using the MZmine software,and molecular networks were then performed with the GNPS data analysis workflow using a spectral clustering algorithm.Analysis of curated molecular networks generated from the extracts of this fungus allowed the identification of molecular ion clusters containing AA.The comprehensive targeted isolation of AA analogs was subsequently conducted using silica gel column chromatography,Sephadex LH-20 column chromatography,and other separation methods,and their structures were elucidated via one-and two-dimensional nuclear magnetic resonance(NMR)spectroscopy,including 1H NMR,13C NMR,1H-1H COSY,HSQC,HMBC,NOESY.Finally,the MS/MS cracking characteristics of AA and its analogs were proposed by the manual analysis of MS/MS fragments,and new AA analogs with diverse structures from the molecular ion clusters were predicted.[Results]Four AA analogs(2-5)were isolated from the fermentation extracts of P.javanicum HK1-22,two of which,penijavanic acids A(4)and B(5),were new compounds reported for the first time.Based on the structural hints of isolated AA and its analogs,four analogs(6-9),including three new ones(penijavanic aldehyde(7),penijavanic acid C(8),and penijavanic terpene(9)),were successfully predicted from molecular networks.A careful analysis of the MS/MS spectra of these compounds revealed that the MS/MS fragmentation pathway was characteristic in these compounds as the first breakage occurred at the isopropyl and/or carboxyl group to form signals with high abundance.Subsequently,the remaining terpene skeleton rings were broken at different positions,which finally produced the dominant and conserved product ions related to benzyl carbocation.These MS/MS fragmentation features provided clues for the structure elucidation of 6-9 and were a basis for the rapid identification of these types of AA analogs based on the MS/MS spectra.[Conclusions]The GNPS platform was successfully applied to the mining of novel secondary metabolites from fungi.Under the guidance of this technology,students can clearly"see"target compounds to be separated so as to achieve the targeted separation of high-value natural products,which stimulates students'interest in scientific research and improves their practical innovation abilities.关键词
天然产物化学/导向分离/分子网络/GNPS平台/天然除草剂Key words
natural product chemistry/guided separation/molecular networking/GNPS platform/natural herbicides分类
社会科学引用本文复制引用
陈敏,缪莉,张立奎..采用GNPS-分子网络技术快速发掘天然除草剂aspterric acid类似物[J].实验技术与管理,2025,42(3):80-87,8.基金项目
国家自然科学基金项目(81703411) （81703411）
大学生创新创业训练计划项目(XCX20230629) （XCX20230629）
