Peptide Mass Fingerprinting - Online Tutor, Practice Problems & Exam Prep

Peptide mass fingerprinting (PMF) is a technique used to identify unknown proteins by comparing their mass spectrometry spectra to those in databases. The process involves fragmenting the protein, ionizing the fragments, and performing tandem mass spectrometry (MSMS) to generate unique spectra, akin to fingerprints. These spectra are matched against known protein sequences in databases. A limitation of PMF is that it requires the protein to be in the database; otherwise, new proteins can be sequenced and added for future identification. This method streamlines protein identification, enhancing proteomics research.

Peptide Mass Fingerprinting

In this video, we're going to talk about peptide mass fingerprinting. Peptide mass fingerprinting can be abbreviated as PMF, and it's a technique that we use to identify unknown proteins. It uses the mass spectrometry spectrums from very large computer databases to identify unknown proteins. If we have an unknown protein sample, we can take a little bit of this sample and subject it to tandem mass spectrometry to acquire an actual spectrum of the unknown protein. Then we compare this actual spectrum to the spectrums of all known proteins stored in computer databases until a match is found. Once a match has been made, we are able to identify the unknown protein. Typically, it's only necessary to analyze very small portions of the protein to identify it, which speeds up the process.

A limitation to peptide mass fingerprinting is that the database must already include the protein to identify it. If the database doesn't include the unknown protein, then a brand new protein that has never been discovered before is identified. We can fully sequence this unknown protein and enter its sequence into the database, so that later, if anyone extracts that same unknown protein, they can use peptide mass fingerprinting to quickly identify it.

Let's take a look at our example of peptide mass fingerprinting to clarify this concept better. We have two brackets here. The first bracket, highlighted in yellow, represents the entire tandem mass spectrometry process covered in previous lesson videos. The second bracket refers to peptide mass fingerprinting, the main focus of this video. We start with an already purified protein and subject it to fragmentation with a chemical or a protease, generating different protein fragments. These fragments are then ionized and subjected to the first mass spectrometry, which acts as a filter to select specific peptide fragments to continue forward in the process. Here, it's possible that the first mass spectrometry generates an actual spectrum, which is acceptable. With tandem mass spectrometry, only particular peptide fragments are selected to move forward. For example, we might subject a fragment to a collision cell to fragment it further, and then subject it to a second mass spectrometry (MS/MS) to generate a spectrum of this particular peptide fragment. We generate spectrums from multiple rounds of MS/MS, which are unique and specific enough to act like fingerprints. We then enter these MS/MS spectrums into a computer database, and the computer searches the database until it finds a match for these spectrums. The spectrums in the computer database are linked to protein sequences. Once a match is made, it's relatively simple to identify the subunits these fragments originated from and identify the original unknown protein.

This concludes our lesson on peptide mass fingerprinting, where we use tandem mass spectrometry to generate unique mass spectrums and enter them into a computer database until a match is found. In our next video, we will discuss other ways to sequence a protein. See you in our practice session.

Peptide mass fingerprinting (PMF) is a method used to determine the sequence of an unknown peptide. In the sequencing of peptides by PMF, tandem mass spectrometry fragments peptides into smaller molecules to obtain the mass spectrum, which acts like a fingerprint & can be compared to theoretical spectrums in a database to derive the amino acid sequence. Mainly which types of bonds are broken to fragment the peptide & generate tandem mass spectra data?

• A. Carbon-carbon bonds within the amino acid R-groups.
• B. Disulfide bonds.
• C. Omega bonds.
• D. Phi bonds.
• E. Psi bonds.

Explain how a 5-residue amino acid sequence could uniquely identify a 200-residue protein via PMF. 

Hint #1: Compare the number of pentapeptides in the 200-residue protein to the total number of all possible pentapeptide sequences.

Hint #2: 

Hint #3: 

Alright. So this practice problem wants us to explain how a 5 residue amino acid sequence could uniquely identify a 200 residue protein via PMF, or peptide mass fingerprinting. And so notice down below, we're given these 3 different hints that we're going to need to use. And recall from our previous lesson videos, we said that usually it's only necessary to analyze very small portions of an entire protein to uniquely identify that protein. And really, this practice problem is emphasizing that same exact idea by saying again that just a 5 residue amino acid sequence could uniquely identify a 200 residue protein. And so the best way to explain how this is possible is to compare the number of pentapeptides in a 200 residue protein to the total number of all possible pentapeptide sequences. And so notice that hint number 2 below is telling us how to determine the number of pentapeptides in a 200 residue protein. And notice that hint number 3 below is telling us how to determine the total number of all possible pentapeptide sequences. And so notice up above, I've drawn a little sketch of our 200 residue protein, where each of these circles represents amino acids. Now notice I didn't draw all 200 amino acids, but you can imagine that these dotted lines here represent the remaining amino acids. And so if we're trying to determine the number of pentapeptides in our 200 residue protein, all we need to do is start counting pentapeptides from the far left and shifting over one amino acid residue. And so our first pentapeptide will be the first five amino acids. Now the second pentapeptide, all we need to do is shift over 1 amino acid residue and count 5 pentapeptides over. And so this pentapeptide could potentially be different than the first pentapeptide. And so the 3rd pentapeptide, all we need to do is shift over another one and count over 5. And the 4th pentapeptide, all we need to do is shift over another one and count over 5. And so we can continuously count pentapeptides by shifting over 1 amino acid residue and counting over 5 until we get to the very end of our 200 residue protein. And so just to save you guys some time, we're told that a protein sequence of n residues has the potential to give rise to n minus 4 pentapeptides. And so because we have a 200 residue protein, this means that n here is going to be equal to 200. And so 200 minus 4 is, of course, equal to 196. And so what this means is that a 200 residue protein could potentially give rise to a maximum of 196 different pentapeptides. Now at first glance, this might seem like a pretty large number. But once we compare this number to the total number of all possible pentapeptides, we'll see that this number is really just a small fraction of all possible pentapeptides. And so to calculate the total number of all possible pentapeptides, all we need to do is take the number of alpha amino acids, which we know there are 20 alpha amino acids, and raise it to the power of the number of positions in the pentapeptide. And so we know that a pentapeptide has a total of 5 amino acid positions. And at each amino acid position, we have an option for 20 amino acids. And so all we need to do is multiply all of these numbers together. And essentially, that's the same thing as taking 20 and raising it to the 5th power. And so if you take your calculators and do 205, you'll get an answer of 3,200,000, which is a massively large number, and this is the total number of all possible pentapeptides. Now because, you'll see that a single pentapeptide is incredibly unique, literally 1 out of 3,200,000. Because a single pentapeptide is so unique, we can use a single pentapeptide to uniquely identify a 200 residue protein. And so again, we said earlier that this number here, this number of pentapeptides in our 200 residue protein is just a small fraction of all of the possible pentapeptides. And so if we were to turn that into a percentage, all we would need to do is take the number of pentapeptides in our 200 residue protein, which is a 196, and divide it by the total number of all possible pentapeptides, which is 3,200,000. And so, if we want to turn this ratio here into a percentage, all we need to do is multiply it by 100%. And so if you type this into your calculator, you'll get an answer of about 0.006125%, and that is incredibly, incredibly small percentage, way less than just 1%. And so, really, what this percentage represents is the incredibly small chance that any random pentapeptide sequence is going to be matching a sequence, confirming an incredibly rare event. And so, we can use rare events as identifiers. And so, if we confirm a rare event in our 200 residue protein, then we can use it to identify that 200 residue protein. And so again, this percentage here just shows, this percentage here. And, especially this is going to be important when we can use a database that can compare this 5 residue amino acid sequence with all of the other proteins stored in the database to see if there is a match for this sequence or not. And so, essentially, the main takeaway for this problem is again that usually it's only necessary to analyze small portions of a protein to uniquely identify it. And so that concludes this practice problem, and I'll see you guys in our next video.

Here’s what students ask on this topic:

What is peptide mass fingerprinting (PMF) and how does it work?

Peptide mass fingerprinting (PMF) is a technique used to identify unknown proteins by comparing their mass spectrometry spectra to those in databases. The process involves fragmenting the protein, ionizing the fragments, and performing tandem mass spectrometry (MSMS) to generate unique spectra, akin to fingerprints. These spectra are then matched against known protein sequences in databases. If a match is found, the unknown protein can be identified. A limitation of PMF is that it requires the protein to be in the database; otherwise, new proteins can be sequenced and added for future identification. This method streamlines protein identification, enhancing proteomics research.

What are the limitations of peptide mass fingerprinting?

The primary limitation of peptide mass fingerprinting (PMF) is that the protein must already be present in the database for identification. If the unknown protein is not in the database, it cannot be identified using PMF. In such cases, the new protein must be fully sequenced and added to the database for future identification. Additionally, PMF requires high-quality mass spectrometry data and may not work well with complex mixtures or highly modified proteins. Despite these limitations, PMF is a powerful tool for rapid protein identification in proteomics research.

How does tandem mass spectrometry (MSMS) contribute to peptide mass fingerprinting?

Tandem mass spectrometry (MSMS) is crucial for peptide mass fingerprinting (PMF) as it generates the unique spectra needed for protein identification. In MSMS, protein fragments are first ionized and subjected to a first round of mass spectrometry, which acts as a filter to select specific peptide fragments. These selected fragments are then further fragmented in a collision cell and subjected to a second round of mass spectrometry. The resulting spectra are highly specific and act like fingerprints. These spectra are then compared to known spectra in databases to identify the unknown protein.

What role do computer databases play in peptide mass fingerprinting?

Computer databases play a critical role in peptide mass fingerprinting (PMF) by storing the mass spectrometry spectra of known proteins. When an unknown protein is analyzed, its spectra are compared against these stored spectra to find a match. If a match is found, the unknown protein can be identified. These databases are continually updated with new protein sequences, enhancing the accuracy and scope of PMF. Without these databases, the identification process would be significantly slower and less reliable, as each unknown protein would need to be fully sequenced manually.

What are the steps involved in peptide mass fingerprinting?

The steps involved in peptide mass fingerprinting (PMF) are as follows: 1) Start with an unknown protein sample. 2) Fragment the protein using a chemical or protease. 3) Ionize the protein fragments. 4) Perform the first round of mass spectrometry to filter specific peptide fragments. 5) Subject selected fragments to a collision cell for further fragmentation. 6) Perform a second round of mass spectrometry (MSMS) to generate unique spectra. 7) Compare these spectra to those in a computer database. 8) Identify the unknown protein if a match is found. This process allows for rapid and accurate protein identification.