Use of Multiple Proteases for Improved Protein Digestion

One of the approaches to identify proteins by mass spectrometry includes the separation of proteins by gel electrophoresis or liquid chromatography. Subsequently the proteins are cleaved with sequence-specific endoproteases. Following digestion the generated peptides are investigated by determination of molecular masses or specific sequence. For protein identification the experimentally obtained masses/sequences are compared with theoretical masses/sequences compiled in various databases.

Trypsin is the favored enzyme for this application, for the following reasons: A) the peptides contain a basic residue (Arg or Lys) on the C terminus and thus are good candidates for collision induced activation (CAD) in tandem experiments (low charge states and high mass-to-charge ratios); B) it is relatively Inexpensive; and C) optimal digestion conditions have been well characterized.

An inherent limitation of trypsin is the size of the peptides that it generates. For most organisms > 50% of tryptic peptides are less than 6 amino acids, too small for mass spectrometry based sequencing.

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One recent publication examined the use of multiple proteases (trypsin, LysC, ArgC , AspN and GluC) in combination with either CAD or electron-based fragmentation (ETD) to improve protein identification (1). Their results indicated a significant improvement from a single protease digestion (trypsin), which yielded 27,822 unique peptides corresponding to 3313 proteins. In contrast using a combination of proteases with either CAD or ETD fragmentation methods yielded 92,095 unique peptides mapping to 3908 proteins.

Swaney DL, Wenger CD, & Coon JJ (2010). Value of using multiple proteases for large-scale mass spectrometry-based proteomics. Journal of proteome research, 9 (3), 1323-9 PMID: 20113005

Trypsin: Innovative Applications

3D model of protein and protease cleavage

Tryptic digestion of samples and subsequent analysis by mass spectrometry is a popular technique for the identification of proteins typically those related to interaction partners or biomarkers characterization. This powerful tool can also be used for less traditional experimental designs. Three examples are:

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