Peptide mass fingerprinting (PMF) is a powerful technique used to identify unknown proteins by leveraging mass spectrometry. The process begins with obtaining a sample of the unknown protein, which is then subjected to tandem mass spectrometry (MS/MS) to generate a spectrum. This spectrum is compared against a database of known protein spectra to find a match, allowing for the identification of the unknown protein.
In practice, only small portions of the unknown protein are analyzed, which streamlines the identification process. However, a key limitation of PMF is that the protein must already be present in the database for identification. If the protein is novel and not in the database, it can be fully sequenced and added for future reference.
The PMF process involves several steps. Initially, the unknown protein is fragmented using a chemical or protease, producing various peptide fragments. These fragments are ionized and subjected to the first mass spectrometry, which acts as a filter to select specific peptide fragments for further analysis. The selected fragments undergo additional fragmentation in a collision cell, followed by a second mass spectrometry to generate unique spectra for each fragment.
These spectra serve as "fingerprints" for the peptides, similar to how human fingerprints are used for identification. Once the spectra are generated, they are entered into a computer database linked to known protein sequences. The database search continues until a match is found, allowing researchers to identify the original protein by determining the subunits from which the fragments originated.
In summary, peptide mass fingerprinting utilizes tandem mass spectrometry to create unique mass spectra that can be matched against a database, facilitating the identification of unknown proteins. This method is efficient and effective, provided the protein is already cataloged in the database.