scholarly journals Peptide and protein analysis with mass spectrometry

2002 ◽  
Vol 16 (1) ◽  
pp. 15-28 ◽  
Author(s):  
Sunia A. Trauger ◽  
William Webb ◽  
Gary Siuzdak

Mass spectrometry (MS) is rapidly becoming a fundamental tool for biologists and biochemists in their efforts to characterize cellular function. Recent advancements in MS technology and front-end methodologies, along with the completion of the human genome have greatly popularized its use by researchers for protein identification and characterization. This paper is a general overview of how mass spectrometry is being used for the analysis of peptides and proteins, focusing on its application to molecular weight determination. Sample preparatory and cleanup techniques used in our laboratory for protein and peptide analysis are provided, along with a discussion of data interpretation. The utility of mass spectrometry for protein and peptide analyses lies in its ability to provide highly accurate molecular weight information on intact molecules. The ability to generate such accurate information can be extremely useful for protein identification and characterization. For example, a protein can often be unambiguously identified by the accurate mass analysis of its constituent peptides produced by either chemical or enzymatic treatment of the sample. Furthermore, protein identification can also be facilitated by analysis of the protein's proteolytic peptide fragments in the gas phase; fragment ions generated inside the mass spectrometer via collision-induced dissociation (CID) to yield information about the primary structure and modifications. This overview describes how electrospray ionization (ESI) and matrix‒assisted laser desorption/ionization (MALDI) mass spectrometry is being used for peptide and protein characterization focusing on its application to molecular weight determination.

2021 ◽  
Author(s):  
Robert Gerbasi ◽  
Rafael D. Melani ◽  
Susan E. Abbatiello ◽  
Michael W. Belford ◽  
Romain Huguet ◽  
...  

<div> <p>Field Asymmetric Ion Mobility Spectrometry (FAIMS), when used in proteomics studies, provides superior selectivity, and enables more proteins to be identified by providing additional gas phase separation. Here, we tested the performance of cylindrical FAIMS for the identification and characterization of proteoforms by top-down mass spectrometry of heterogeneous protein mixtures. Combining FAIMS with chromatographic separation resulted in a 62% increase in protein identifications and an 8% increase in proteoform identifications as compared to samples analyzed without FAIMS. This increase was attributable, in part, to improved signal-to-noise for proteoforms with similar retention times. Additionally, our results show that the optimal compensation voltage of any given proteoform was correlated with the molecular weight of the analyte. Collectively these results suggest that the addition of FAIMS can enhance top-down proteomics in both discovery and targeted applications. </p> </div>


2021 ◽  
Author(s):  
Robert Gerbasi ◽  
Rafael D. Melani ◽  
Susan E. Abbatiello ◽  
Michael W. Belford ◽  
Romain Huguet ◽  
...  

<div> <p>Field Asymmetric Ion Mobility Spectrometry (FAIMS), when used in proteomics studies, provides superior selectivity, and enables more proteins to be identified by providing additional gas phase separation. Here, we tested the performance of cylindrical FAIMS for the identification and characterization of proteoforms by top-down mass spectrometry of heterogeneous protein mixtures. Combining FAIMS with chromatographic separation resulted in a 62% increase in protein identifications and an 8% increase in proteoform identifications as compared to samples analyzed without FAIMS. This increase was attributable, in part, to improved signal-to-noise for proteoforms with similar retention times. Additionally, our results show that the optimal compensation voltage of any given proteoform was correlated with the molecular weight of the analyte. Collectively these results suggest that the addition of FAIMS can enhance top-down proteomics in both discovery and targeted applications. </p> </div>


2000 ◽  
Vol 28 (5) ◽  
pp. A260-A260
Author(s):  
D. Gostick ◽  
J. Brown ◽  
A. Dobbins ◽  
E. Kapp ◽  
R. O'malley ◽  
...  

1986 ◽  
Vol 13 (12) ◽  
pp. 689-691 ◽  
Author(s):  
P. Roepstorff ◽  
P. Højrup ◽  
B. U. R. Sundqvist ◽  
G. Jonsson ◽  
P. Håkansson ◽  
...  

2017 ◽  
Vol 89 (9) ◽  
pp. 4793-4797 ◽  
Author(s):  
Guanbo Wang ◽  
Rob N. de Jong ◽  
Ewald T. J. van den Bremer ◽  
Paul W. H. I. Parren ◽  
Albert J. R. Heck

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