scholarly journals Comparison of protein expression lists from mass spectrometry of human blood fluids using exact peptide sequences versus BLAST

2021 ◽  
Author(s):  
Peihong Zhu ◽  
Peter Bowden ◽  
Voitek Pendrak ◽  
Herbert Thiele ◽  
Du Zhang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Human Blood ◽  
Mass Spectra ◽  
Query Language ◽  
False Positive Rate ◽  
Peptide Sequence ◽  
Reference Sequence ◽  
Local Alignment ◽  
Human Beings ◽  
Refseq Database

The proteins in blood were all first expressed as mRNAs from genes within cells. There are databases of human proteins that are known to be expressed as mRNA in human cells and tissues. Proteins identified from human blood by the correlation of mass spectra that fail to match human mRNA expression products may not be correct. We compared the proteins identified in human blood by mass spectrometry by 10 different groups by correlation to human and nonhuman nucleic acid sequences. We determined whether the peptides or proteins identified by the different groups mapped to the human known proteins of the Reference Sequence (RefSeq) database. We used Structured Query Language data base searches of the peptide sequences correlated to tandem mass spectrometry spectra and basic local alignment search tool analysis of the identified full length proteins to control for correlation to the wrong peptide sequence or the existence of the same or very similar peptide sequence shared by more than one protein. Mass spectra were correlated against large protein data bases that contain many sequences that may not be expressed in human beings yet the search returned a very high percentage of peptides or proteins that are known to be found in humans. Only about 5% of proteins mapped to hypothetical sequences, which is in agreement with the reported false-positive rate of searching algorithms conditions. The results were highly enriched in secreted and soluble proteins and diminished in insoluble or membrane proteins. Most of the proteins identified were relatively short and showed a similar size distribution compared to the RefSeq database. At least three groups agree on a nonredundant set of 1671 types of proteins and a nonredundant set of 3151 proteins were identified by at least three peptides.

scholarly journals Comparison of protein expression lists from mass spectrometry of human blood fluids using exact peptide sequences versus BLAST

2021 ◽  
Author(s):  
Peihong Zhu ◽  
Peter Bowden ◽  
Voitek Pendrak ◽  
Herbert Thiele ◽  
Du Zhang ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Human Blood ◽  
Mass Spectra ◽  
Query Language ◽  
False Positive Rate ◽  
Peptide Sequence ◽  
Reference Sequence ◽  
Local Alignment ◽  
Human Beings ◽  
Refseq Database

The proteins in blood were all first expressed as mRNAs from genes within cells. There are databases of human proteins that are known to be expressed as mRNA in human cells and tissues. Proteins identified from human blood by the correlation of mass spectra that fail to match human mRNA expression products may not be correct. We compared the proteins identified in human blood by mass spectrometry by 10 different groups by correlation to human and nonhuman nucleic acid sequences. We determined whether the peptides or proteins identified by the different groups mapped to the human known proteins of the Reference Sequence (RefSeq) database. We used Structured Query Language data base searches of the peptide sequences correlated to tandem mass spectrometry spectra and basic local alignment search tool analysis of the identified full length proteins to control for correlation to the wrong peptide sequence or the existence of the same or very similar peptide sequence shared by more than one protein. Mass spectra were correlated against large protein data bases that contain many sequences that may not be expressed in human beings yet the search returned a very high percentage of peptides or proteins that are known to be found in humans. Only about 5% of proteins mapped to hypothetical sequences, which is in agreement with the reported false-positive rate of searching algorithms conditions. The results were highly enriched in secreted and soluble proteins and diminished in insoluble or membrane proteins. Most of the proteins identified were relatively short and showed a similar size distribution compared to the RefSeq database. At least three groups agree on a nonredundant set of 1671 types of proteins and a nonredundant set of 3151 proteins were identified by at least three peptides.

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

2020 ◽  
Author(s):  
Jie Cheng ◽  
Yuchen Tang ◽  
Baoquan Bao ◽  
Ping Zhang
Keyword(s):  
Mass Spectrometry ◽  
Molecular Docking ◽  
High Resolution ◽  
Mass Spectra ◽  
High Resolution Mass Spectrometry ◽  
Structural Formula ◽  
Active Compounds ◽  
High Resolution Mass ◽  
Q Exactive ◽  
Resolution Mass

<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>

Unrestrictive protein modification localization and quality control for open search of mass spectra

2018 ◽  
Author(s):  
Zhiwu An ◽  
Fuzhou Gong ◽  
Yan Fu
Keyword(s):  
Mass Spectrometry ◽  
Quality Control ◽  
Tandem Mass Spectrometry ◽  
Mass Spectra ◽  
Protein Modification ◽  
Software Tool ◽  
Tandem Mass ◽  
Simulation Data ◽  
Post Translational Modifications

We have developed PTMiner, a first software tool for automated, confident filtering, localization and annotation of protein post-translational modifications identified by open (mass-tolerant) search of large tandem mass spectrometry datasets. The performance of the software was validated on carefully designed simulation data. <br>

scholarly journals Chimera Spectrum Diagnostics for Peptides Using Two-Dimensional Partial Covariance Mass Spectrometry

Molecules ◽  
2021 ◽  
Vol 26 (12) ◽  
pp. 3728
Author(s):  
Taran Driver ◽  
Nikhil Bachhawat ◽  
Leszek J. Frasinski ◽  
Jonathan P. Marangos ◽  
Vitali Averbukh ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Peptide Sequence ◽  
Two Dimensional ◽  
Peptide Ions ◽  
Finite Mass ◽  
Protein Database ◽  
Spectra Analysis ◽  
Fragment Ions ◽  
Single Precursor ◽  
The Common

The rate of successful identification of peptide sequences by tandem mass spectrometry (MS/MS) is adversely affected by the common occurrence of co-isolation and co-fragmentation of two or more isobaric or isomeric parent ions. This results in so-called `chimera spectra’, which feature peaks of the fragment ions from more than a single precursor ion. The totality of the fragment ion peaks in chimera spectra cannot be assigned to a single peptide sequence, which contradicts a fundamental assumption of the standard automated MS/MS spectra analysis tools, such as protein database search engines. This calls for a diagnostic method able to identify chimera spectra to single out the cases where this assumption is not valid. Here, we demonstrate that, within the recently developed two-dimensional partial covariance mass spectrometry (2D-PC-MS), it is possible to reliably identify chimera spectra directly from the two-dimensional fragment ion spectrum, irrespective of whether the co-isolated peptide ions are isobaric up to a finite mass accuracy or isomeric. We introduce ‘3-57 chimera tag’ technique for chimera spectrum diagnostics based on 2D-PC-MS and perform numerical simulations to examine its efficiency. We experimentally demonstrate the detection of a mixture of two isomeric parent ions, even under conditions when one isomeric peptide is at one five-hundredth of the molar concentration of the second isomer.

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