scholarly journals Tandem Mass-Remainder Analysis of Industrially Important Polyether Polyols

Polymers ◽  
2020 ◽  
Vol 12 (12) ◽  
pp. 2768
Author(s):  
Mahir Hashimov ◽  
Ákos Kuki ◽  
Tibor Nagy ◽  
Miklós Zsuga ◽  
Sándor Kéki

The characteristics of the polyalkylene oxide polyether polyols highly influence the properties of final polyurethane products. As a novel approach, in order to gain structural information, the recently invented data mining procedures, namely the Mass-remainder analysis (MARA) and the Multistep Mass-remainder analysis (M-MARA) are successfully applied for the processing of tandem mass spectrometry (MS/MS) data of various industrially important polyether polyols. M-MARA yields an ultra-simplified graphical representation of the MS/MS spectra and sorts the product ions based on their double bond equivalent (DBE) values. The maximum DBE values unambiguously differentiate among the various polyether polyols. Accordingly, the characteristic DBE values were 0, 1 for the linear diol polyethers, 0, 1, 2 for the three-arm, and 0, 1 2, 3, 4 for the six-arm polyether polyols. In addition, it was also found that the characteristic collision energy necessary for the optimum fragmentation yield depended linearly on the molecular weight of the polyols. This relationship offers an easy way for instrument tuning to gain structural information.

2007 ◽  
Vol 367 (1) ◽  
pp. 40-48 ◽  
Author(s):  
Benlian Wang ◽  
Gang Sun ◽  
David R. Anderson ◽  
Minghong Jia ◽  
Stephen Previs ◽  
...  

1983 ◽  
Vol 105 (6) ◽  
pp. 1654-1655 ◽  
Author(s):  
I. J. Amster ◽  
M. A. Baldwin ◽  
M. T. Cheng ◽  
C. J. Proctor ◽  
F. W. McLafferty

Author(s):  
Haipeng Wang

Protein identification (sequencing) by tandem mass spectrometry is a fundamental technique for proteomics which studies structures and functions of proteins in large scale and acts as a complement to genomics. Analysis and interpretation of vast amounts of spectral data generated in proteomics experiments present unprecedented challenges and opportunities for data mining in areas such as data preprocessing, peptide-spectrum matching, results validation, peptide fragmentation pattern discovery and modeling, and post-translational modification (PTM) analysis. This article introduces the basic concepts and terms of protein identification and briefly reviews the state-of-the-art relevant data mining applications. It also outlines challenges and future potential hot spots in this field.


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