Exploring the Active Compounds of Traditional Mongolian Medicine Agsirga in Intervention of Novel Coronavirus (2019-nCoV) Based on HPLC-Q-Exactive-MS/MS and Molecular Docking Method

Author(s):  
Jie Cheng ◽  
Yuchen Tang ◽  
Baoquan Bao ◽  
Ping Zhang

<p><a></a><a></a><a></a><a><b>Objective</b></a>: To screen all compounds of Agsirga based on the HPLC-Q-Exactive high-resolution mass spectrometry and find potential inhibitors that can respond to 2019-nCoV from active compounds of Agsirga by molecular docking technology.</p> <p><b>Methods</b>: HPLC-Q-Exactive high-resolution mass spectrometry was adopted to identify the complex components of Mongolian medicine Agsirga, and separated by the high-resolution mass spectrometry Q-Exactive detector. Then the Orbitrap detector was used in tandem high-resolution mass spectrometry, and the related molecular and structural formula were found by using the chemsipider database and related literature, combined with precise molecular formulas (errors ≤ 5 × 10<sup>−6</sup>) , retention time, primary mass spectra, and secondary mass spectra information, The fragmentation regularities of mass spectra of these compounds were deduced. Taking ACE2 as the receptor and deduced compounds as the ligand, all of them were pretreated by discover studio, autodock and Chem3D. The molecular docking between the active ingredients and the target protein was studied by using AutoDock molecular docking software. The interaction between ligand and receptor is applied to provide a choice for screening anti-2019-nCoV drugs.</p> <p><b>Result</b>: Based on the fragmentation patterns of the reference compounds and consulting literature, a total of 96 major alkaloids and stilbenes were screened and identified in Agsirga by the HPLC-Q-Exactive-MS/MS method. Combining with molecular docking, a conclusion was got that there are potential active substances in Mongolian medicine Agsirga which can block the binding of ACE2 and 2019-nCoV at the molecular level.</p>

Author(s):  
Jie Cheng ◽  
Yuchen Tang ◽  
Baoquan Bao ◽  
Ping Zhang

<p><a></a><a></a><a></a><a><b>Objective</b></a>: To screen all compounds of Agsirga based on the HPLC-Q-Exactive high-resolution mass spectrometry and find potential inhibitors that can respond to 2019-nCoV from active compounds of Agsirga by molecular docking technology.</p> <p><b>Methods</b>: HPLC-Q-Exactive high-resolution mass spectrometry was adopted to identify the complex components of Mongolian medicine Agsirga, and separated by the high-resolution mass spectrometry Q-Exactive detector. Then the Orbitrap detector was used in tandem high-resolution mass spectrometry, and the related molecular and structural formula were found by using the chemsipider database and related literature, combined with precise molecular formulas (errors ≤ 5 × 10<sup>−6</sup>) , retention time, primary mass spectra, and secondary mass spectra information, The fragmentation regularities of mass spectra of these compounds were deduced. Taking ACE2 as the receptor and deduced compounds as the ligand, all of them were pretreated by discover studio, autodock and Chem3D. The molecular docking between the active ingredients and the target protein was studied by using AutoDock molecular docking software. The interaction between ligand and receptor is applied to provide a choice for screening anti-2019-nCoV drugs.</p> <p><b>Result</b>: Based on the fragmentation patterns of the reference compounds and consulting literature, a total of 96 major alkaloids and stilbenes were screened and identified in Agsirga by the HPLC-Q-Exactive-MS/MS method. Combining with molecular docking, a conclusion was got that there are potential active substances in Mongolian medicine Agsirga which can block the binding of ACE2 and 2019-nCoV at the molecular level.</p>


2020 ◽  
Author(s):  
Jie Cheng ◽  
Yuchen Tang ◽  
Baoquan Bao ◽  
Ping Zhang

<p><a></a><a></a><a></a><a><b>Objective</b></a>: To screen all compounds of Agsirga based on the HPLC-Q-Exactive high-resolution mass spectrometry and find potential inhibitors that can respond to 2019-nCoV from active compounds of Agsirga by molecular docking technology.</p> <p><b>Methods</b>: HPLC-Q-Exactive high-resolution mass spectrometry was adopted to identify the complex components of Mongolian medicine Agsirga, and separated by the high-resolution mass spectrometry Q-Exactive detector. Then the Orbitrap detector was used in tandem high-resolution mass spectrometry, and the related molecular and structural formula were found by using the chemsipider database and related literature, combined with precise molecular formulas (errors ≤ 5 × 10<sup>−6</sup>) , retention time, primary mass spectra, and secondary mass spectra information, The fragmentation regularities of mass spectra of these compounds were deduced. Taking ACE2 as the receptor and deduced compounds as the ligand, all of them were pretreated by discover studio, autodock and Chem3D. The molecular docking between the active ingredients and the target protein was studied by using AutoDock molecular docking software. The interaction between ligand and receptor is applied to provide a choice for screening anti-2019-nCoV drugs.</p> <p><b>Result</b>: Based on the fragmentation patterns of the reference compounds and consulting literature, a total of 96 major alkaloids and stilbenes were screened and identified in Agsirga by the HPLC-Q-Exactive-MS/MS method. Combining with molecular docking, a conclusion was got that there are potential active substances in Mongolian medicine Agsirga which can block the binding of ACE2 and 2019-nCoV at the molecular level.</p>


2015 ◽  
Vol 7 (14) ◽  
pp. 5748-5759 ◽  
Author(s):  
Arnaud Djintchui Ngongang ◽  
Sung Vo Duy ◽  
Sébastien Sauvé

A selective and robust methodology for the analysis of nineN-nitrosamines (NAs) was developed and validated.


2005 ◽  
Vol 51 (10) ◽  
pp. 1946-1954 ◽  
Author(s):  
Mary F Lopez ◽  
Alvydas Mikulskis ◽  
Scott Kuzdzal ◽  
David A Bennett ◽  
Jeremiah Kelly ◽  
...  

Abstract Background: Researchers typically search for disease markers using a “targeted” approach in which a hypothesis about the disease mechanism is tested and experimental results either confirm or disprove the involvement of a particular gene or protein in the disease. Recently, there has been interest in developing disease diagnostics based on unbiased quantification of differences in global patterns of protein and peptide masses, typically in blood from individuals with and without disease. We combined a suite of methods and technologies, including novel sample preparation based on carrier-protein capture and biomarker enrichment, high-resolution mass spectrometry, a unique cohort of well-characterized persons with and without Alzheimer disease (AD), and powerful bioinformatic analysis, that add statistical and procedural robustness to biomarker discovery from blood. Methods: Carrier-protein–bound peptides were isolated from serum samples by affinity chromatography, and peptide mass spectra were acquired by a matrix-assisted laser desorption/ionization (MALDI) orthogonal time-of-flight (O-TOF) mass spectrometer capable of collecting data over a broad mass range (100 to &gt;300 000 Da) in a single acquisition. Discriminatory analysis of mass spectra was used to process and analyze the raw mass spectral data. Results: Coupled with the biomarker enrichment protocol, the high-resolution MALDI O-TOF mass spectra provided informative, reproducible peptide signatures. The raw mass spectra were analyzed and used to build discriminant disease models that were challenged with blinded samples for classification. Conclusions: Carrier-protein enrichment of disease biomarkers coupled with high-resolution mass spectrometry and discriminant pattern analysis is a powerful technology for diagnostics and population screening. The mass fingerprint model successfully classified blinded AD patient and control samples with high sensitivity and specificity.


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