Predicting Peptide Retention Times for Proteomics

互联网2013-12-31

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Abstract
Table of Contents
Materials
Figures
Literature Cited

Abstract

The vast majority of modern bottom?up proteomic protocols include chromatographic reversed?phase (RP) fractionation of peptides prior to mass?spectrometric analysis. Retention time information can be easily extracted from LC?MS data and it can be used to improve protein identification/characterization procedures. The key to the success of this procedure is the correct retention time prediction based on compositional and structural properties of the separated species. Our Sequence Specific Retention Calculator (SSRCalc) is a Web?based peptide retention prediction that covers the separation selectivity of the most popular RP?HPLC conditions applied in proteomics. Procedures for the application of SSRCalc to proteomic analyses are described in this unit. Curr. Protoc. Bioinform. 31:13.14.1?13.14.15. © 2010 by John Wiley & Sons, Inc.

Keywords: peptide retention prediction; reversed?phase HPLC; protein identification

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Introduction
Strategic Planning
Basic Protocol 1: Predicting Peptide Retention Times for Filtering MS/MS Identifications
Basic Protocol 2: Predicting Peptide Retention Times for De‐Novo Development of Scheduled MRM/SRM Procedures
Guidelines for Understanding Results
Commentary
Literature Cited
Figures
Tables

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Materials

Basic Protocol 1: Predicting Peptide Retention Times for Filtering MS/MS Identifications

Mass‐spectrometer capable of performing MRM/SRM analysis

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PDF or HTML at Wiley Online Library

Figures

Figure 13.14.1 The basic workflow steps for applying peptide retention prediction in proteomics.

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Figure 13.14.2 The “chromatographic calibration” of the RP‐HPLC system using synthetic standard peptides (A ) and 20 confidently identified peptides from analyzed sample (B ) –formic acid conditions.

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Figure 13.14.3 The data input page of the Web‐based SSRCalc models.

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Figure 13.14.4 The results output page of the Web‐based SSRCalc models.

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Figure 13.14.5 t_R versus H and t_R versus t_Rpredicted for the whole set [Log(e) <0] of tryptic unmodified peptides (panels A, B ), and for high confidence identifications [Log(e) < −3; panels C, D ]. Obvious cases of false‐positive identifications are highlighted in panels A, B.

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Figure 13.14.6 The distribution of the retention time prediction error for the training set of the SSRCalc 100 Å‐FA model [∼3500 tryptic peptides, R ² ∼0.97 (A )]; and an approximate correlation between model accuracy and σ value (B ) based on variable magnitude random fluctuations introduced into the SSRCalc 100Å‐TFA model (∼5000 tryptic peptides, R² ∼0.98).

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Figure 13.14.7 Retention time prediction for post‐translationally modified peptides (A ), nontryptic peptides and redundant identifications (B ). Panel A: • correct LC calibration using the P2‐P6 standard peptides; ◯ peptides containing oxidized Met residues; □ peptides with N‐terminal cyclization at Gln and cabramidomethyl‐Cys. Panel B: • correct LC calibration using the P2‐P6 standard peptides; ◯ confidently identified peptides DLLFRDDTVCLAK (3+), LFRDDTVCLAK (2+), FRDDTVCLAK (2+) (the last two species formed due to in‐source fragmentation); □ three redundant identifications of LVNEVTEFAK (2+).

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Figure 13.14.8 Application of different peptide retention prediction models to a set of peptides separated using 0.5% acetic acid as ion‐pairing additive. Panel A : SSRCalc 100 Å FA, panel B : PNNL NET, and panel C : BioLCCC.

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Videos

Literature Cited

	Baczek, T., Wiczling, P., Marszall, M., Heyden, Y.V., and Kaliszan, R. 2005. Prediction of peptide retention at different HPLC conditions from multiple linear regression models. J. Proteome Res. 4:555‐563.
	Browne, C.A., Bennett, H.P., and Solomon, S. 1982. The isolation of peptides by high‐performance liquid chromatography using predicted elution positions. Anal Biochem. 124:201‐208.
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	Gorshkov, A.V., Tarasova, I.A., Evreinov, V.V., Savitski, M.M., Nielsen, M.L., Zubarev, R.A., and Gorshkov, M.V. 2006. Liquid chromatography at critical conditions: Comprehensive approach to sequence‐dependent retention time prediction. Anal Chem. 78:7770‐7777.
	Guo, D., Mant, C.T., Taneja, A.K., Parker, R., and Hodges, R.S. 1986. Prediction of peptide retention times in reversed‐phase high‐performance liquid chromatography. I. Determination of retention coefficients of amino acid residues of model synthetic peptides. J. Chromatogr. 359:499‐517.
	Krokhin, O.V. 2006. Sequence‐specific retention calculator. Algorithm for peptide retention prediction in ion‐pair RP‐HPLC: Application to 300‐ and 100‐A pore size C18 sorbents. Anal Chem. 78:7785‐7795.
	Krokhin, O.V. and Spicer, V. 2009. Peptide retention standards and hydrophobicity indexes in reversed‐phase high‐performance liquid chromatography of peptides. Anal Chem. 81:9522‐9530.
	Krokhin, O.V., Ens, W., and Standing, K.G. 2003. Characterizing degradation products of peptides containing N‐terminal Cys residues by (off‐line high‐performance liquid chromatography)/matrix‐assisted laser desorption/ionization quadrupole time‐of‐flight measurements. Rapid Commun. Mass Spectrom. 17:2528‐2534.
	Krokhin, O.V., Craig, R., Spicer, V., Ens, W., Standing, K.G., Beavis, R.C., and Wilkins, J.A. 2004. An improved model for prediction of retention times of tryptic peptides in ion pair reversed‐phase HPLC: Its application to protein peptide mapping by off‐line HPLC‐MALDI MS. Mol. Cell Proteomics 3:908‐919.
	Lange, V., Picotti, P., Domon, B., and Aebersold, R. 2008. Selected reaction monitoring for quantitative proteomics: A tutorial. Mol. Syst. Biol. 4:222.
	Mead, J.A., Bianco, L., Ottone, V., Barton, C., Kay, R.G., Lilley, K.S., Bond, N.J., and Bessant, C. 2009. MRMaid, the web‐based tool for designing multiple reaction monitoring (MRM) transitions. Mol. Cell Proteomics 8:696‐705.
	Meek, J.L. 1980. Prediction of peptide retention times in high‐pressure liquid chromatography on the basis of amino acid composition. Proc. Natl. Acad. Sci. U.S.A. 3:1632‐1636.
	Petritis, K., Kangas, L.J., Yan, B., Monroe, M.E., Strittmatter, E.F., Qian, W.J., Adkins, J.N., Moore, R.J., Xu, Y., Lipton, M.S., Camp, D.G. 2nd, and Smith, R.D. 2006. Improved peptide elution time prediction for reversed‐phase liquid chromatography‐MS by incorporating peptide sequence information. Anal Chem. 78:5026‐5039.
	Shinoda, K., Sugimoto, M., Yachie, N., Sugiyama, N., Masuda, T., Robert, M., Soga, T., and Tomita, M. 2006. Prediction of liquid chromatographic retention times of peptides generated by protease digestion of the Escherichia coli proteome using artificial neural networks. J. Proteome Res. 5:3312‐3317.
	Spicer, V., Yamchuk, A., Cortens, J., Sousa, S., Ens, W., Standing, K. G., Wilkins, J.A., and Krokhin, O.V. 2007. Sequence‐specific retention calculator. A family of peptide retention time prediction algorithms in reversed‐phase HPLC: Applicability to various chromatographic conditions and columns. Anal Chem. 79:8762‐8768.
	Strittmatter, E.F., Kangas, L.J., Petritis, K., Mottaz, H.M., Anderson, G.A., Shen, Y., Jacobs, J.M., Camp, D.G. 2nd, and Smith, R.D. 2004. Application of peptide LC retention time information in a discriminant function for peptide identification by tandem mass spectrometry. J. Proteome Res. 3:760‐769.
Key References
	Krokhin, 2006. See above.
	The most complete description of the SSRCalc model.
	Krokhin et al., 2004. See above.
	First version of the SSRCalc model.
	Krokhin and Spicer, 2009. See above.
	Introduction of standard P1‐P6 peptide mixture and new hydrophobicity scales.
Internet Resources
	http://hs2.proteome.ca/SSRCalc/SSRCalc33B
	SSRCalc online version.
	http://theorchromo.ru/
	TheorChromo online version.
	http://omics.pnl.gov/software/NETPredictionUtility.php
	NET Prediction Utility download site.
Supplemental Data
	Mascot Generic Format file: 101208‐mix25‐075‐1.mgf
	Sample file for the LC‐MS/MS analysis of the tryptic digest mixture of four human proteins spiked with a 6‐peptide standard mixture ().
	Excel file: 101208‐mix25‐075‐1.xls
	Contains the list of all identified peptides (including non‐tryptic peptides and post‐translationally modified ones), as well as a non‐redundant list of tryptic unmodified species.