How to identify the peptides by using MS1 spectra?

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How to identify the peptides by using MS1 spectra? zzhang9  2018-01-11 13:20
 
Hi,

How to identify the peptides by using MS1 spectra in Skyline? Similar as "match between runs" in MaxQuant, but I want to use the normalized retention time instead of the measured one. Thank you!

Best,

Zhenbin
 
 
Brendan MacLean responded:  2018-01-12 20:52
Hi Zhenbin,
I am afraid this doesn't make much sense to me, maybe because I am regrettably not that familiar with MaxQuant.

Can you give a more detailed description of what you are seeking? We'd love to help, but not yet sure how.

--Brendan
 
zzhang9 responded:  2018-01-17 12:16
Hi Brendan,

I want to build a library including the peptide sequence, normalized retention time and m/z information. Then extract the MS1 features from the raw file with m/z and normalized retention time and search against the library built above to get the identification information. Can we realize that in Skyline? Thank you!

Best,

Zhenbin
 
Brendan MacLean responded:  2018-02-03 23:53
Yes, you can do that in Skyline. Mileage may vary depending on how complex your sample is. There are certainly people using Skyline to extract targets from MS1 based on library information alone. I think it works best for somewhat purified samples, or with injected stable isotope labeled standards, and has been used for characterization of biologics.

I am less sure how well this would work out in something as complex as, say, a cell lysate or the types of cases we are currently seeing success with in DIA. MS1 is less selective and the available scores are less specific. You can still do this, and even score with an mProphet model. I just wouldn't expect it to work as well as with DIA, and it is not as thoroughly tested.

As far as I know, though, there is nothing that would block you from trying it, and if your sample is less complex, or you know your targets well or have some other way of increasing your detection confidence like injected stable isotope standards, then it can work quite well.

For more complex samples, I would still recommend using DDA and in-sample peptide IDs, as outlined in the MS1 filtering tutorial.

--Brendan