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[pipettemonkey]

the garlic and substitute fresh mint for dill. Adding salt and pepper to taste or a squeeze of clean air, rural living, year-round sunshine, 8 ounces steamed or broiled salmon, boned
whereby acetylation can reversibly regulate The market for oils rich in GLA now weapons, inexpensive, and difficult to de
Elucidation of the detailed structures of resent the major permeability pathwayMitochondrial Porins, Eukaryotic 379 about 80% of colorectal adenocarcinoma
The hit on performances is huge, actually, when it comes down to servers, as it has to send infos about each and every placeable to each and every client If the objects are part of a tile, the server

[Uwe Neue]

I am not sure if there is a program, since there are complications due to folding of these things. If there is anything, I would look for publications of Mant and Hodges, who have probably done the best homework on such things.

[Kostas Petritis]

I have worked a lot on peptide retention time prediction in reversed phase and made models based on amino acid composition (see Petritis et al. Anal. Chem. 75 (2003) 1039-1048) or amino acid sequence, peptide length and amphipathicity (see Petritis et al. Anal. Chem. 78 (2006) 5026-5039). In the latter publication I compare my model with all other previously published ones and as you will see my model outperforms all of them.

There are several programs out there:
Here you will find the Krokhin algorith: http://hs2.proteome.ca/SSRCalc/SSRCalc.html

Here you will find a software called peptide companion which is based on early work done in the 80's: http://www.5z.com/csps/comer/pcom/

Here you will find a utility that uses the early Krokhin algorithm and my algorithm: http://omics.pnl.gov/software/NETPredictionUtility.php

My algorithm is patent pending and is -unfortunately- not freely available (which has limited it's use by other groups) unless you work for a non for profit organization and you request it through the links of the website above. If you want to avoid the hassle, you can just e-mail me the sequence and I'll provide you with the predicted retention time for your peptides...

[pipettemonkey]

Thanks for the replies.

Kostas: I have emailed you a couple of sequences I'd appreciate you looking at.

I forgot to add in my email that, not only am I using Vydac (protein/peptide) C4 column, but my mobile phase is 0.1% TFA and acetonitrile. I typically run a 4-60% acetonitrile gradient. The column temp is 40 C.

Actually, % of ACN required to elute the peptides would be most useful.

Thanks in advance.

[Kostas Petritis]

I calculated and sent you the information you requested as well as some bonus things.

I wonder though why do you want predicted retention time values of these peptides if you already have fragment MS data on them. If you are sure that the peptide comes from the small protein you provided you should able to tell what the peptide is by it's m/z value and some information from it's fragmentation (as there are not too many possibilites there). I did a non specific cleavage of your peptide and provided you with all possible peptides (around 5500 of them) along with their monoisotopic masses etc. If you have used only trypsin you only need to use a subset of these peptides (the number of possibilities should go down to < 100)...

[oleg krokhin]

I wasn't visiting forum lately, so sorry for late reply.
there are only few models are available freely or on-line:
as Kostas mentioned PNNL predictor:
http://omics.pnl.gov/software/NETPredictionUtility.php
ours SSRCalc model:
http://hs2.proteome.ca/SSRCalc/SSRCalc33B
Gorshkov's group from Moscow:
http://theorchromo.ru/

"Classical" models which Uwe was talking about - not a good choice when it comes to big real proteomics data. But may provide ok result in some cases.
as for better performer it is really depends from your conditions. As you will see SSRCalc has different ion pairing modifiers embedded - so there is more choices (TFA, formic acid, high pH).
Kostas model will work for TFA condition (although was created for mixture of TFA-Formic acid), but in-general his model and SSRCalc TFA is quite comparable. You can try and see which one is better
In our hands for diverse set of tryptic peptides (~1000) separated at 0.1%TFA C18 these models provide R2 correlations:
PNNL predictor ~0.96, SSRCalc TFA ~0.98, Gorshkov's ~0.86

One disadvantage SSRCalc has - it was done for tryptic peptides, so if you do not have C-terminal K or R - there might be problems. As far as I know - PNNL predictor might do a better job here.

we did recently some work on connecting the output of our predictor to actual ACN concentration scale. This might be interesting for your application:
Krokhin OV, Spicer V. “Peptide retention standards and hydrophobicity indexes in reversed-phase high-performance liquid chromatography of peptidesâ€

[Kostas Petritis]

Slight correction, the PNNL predictor was trained on TFA-acetic acid and not TFA-formic acid mixtures and it will work for TFA only mobile phases. At the same website there is an alignment algorithm that can help if you use different gradient and somewhat if you use different mobile phases.

Oleg's algorithm will work just fine for your application...

[oleg krokhin]

yes Kostas - it was TFA-acetic in your paper: I am getting old and start forgetting things

Pure acetic acid - other conditions which people use sometimes. We have actually one version of SSRCalc for acetic acid: it gives ~0.96 correlation for real ~6K peptides LC-ESI data set. The closest thing to it is Formic acid model, which is on-line.

your model Kostas (even it was trained for TFA) gives ~0.94 for formic acid data - which is pretty good.