Recently I worked on an ETD dataset generated from Orbitrap Velos. The user mentioned that Carbamidomethyl on Cysteine and some phosphopeptides are expected but he was not able to get any good identification results using Mascot.
My first attempt is to use the information provided by the user and run the PEAKS DB search. The result shocked me as under 1% FDR, PEAKS DB only reported 170 PSMs. What could possibly go wrong?
Looking at the PEAKS DB result, there are many "de novo only" peptides, which means many spectrum can produce confident de novo sequences but they do not have a confident database hit. This could be a result of unsuspected PTMs and mutations.
So I decided to do a PEAKS PTM search on the db result as my second attempt. PEAKS PTM reported 582 PSMs under 1% FDR. In the summary view, PTM profile section, there are many PSMs found with the PTM Carbamidomethyl on D, E, H, K and N-term. This could be an indication of excess iodoacetamide during alkylation procedure.
Now I know more PTM information of this data. In the last attempt, I added Carbamidomethyl @ DEHK,N-term and Dehydration @ DST into the variable PTM list along with Phosphorylation @ STY. PEAKS DB search was then performed with PEAKS PTM option enabled. This time, under 1% FDR, 736 PSMs were reported, more than four times the number of the initial search.
PEAKS PTM is a great tool to find unsuspected PTMs thus help explaining more spectrum.
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ReplyDeleteThe article discusses a user's struggle with Carbamidomethyl and PTM analysis using PEAKS DB and PEAKS PTM. The author's meticulous approach and the use of advanced tools like PEAKS PTM demonstrate the power of these tools in identifying unsuspected PTMs. abogado de testamentos y sucesiones cerca de mí
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