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Analyst. 2016 Aug 2;141(16):4816-4832. doi: 10.1039/c6an00919k.

Predictive chromatography of peptides and proteins as a complementary tool for proteomics.

Author information

1
Institute for Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia. mike.gorshkov@gmail.com.
2
CEA, iRTSV-BGE, Laboratoire d'Etude de la Dynamique des Protéomes, Grenoble, F-38000, France and INSERM, U1038-BGE, F-38000, Grenoble, France.
3
N.N. Semenov Institute of Chemical Physics, Russian Academy of Sciences, Moscow 119991, Russia.
4
Institute for Energy Problems of Chemical Physics, Russian Academy of Sciences, Moscow 119334, Russia. mike.gorshkov@gmail.com and Moscow Institute of Physics and Technology (State University), Dolgoprudny, Moscow region 141700, Russia.

Abstract

In the last couple of decades, considerable effort has been focused on developing methods for quantitative and qualitative proteome characterization. The method of choice in this characterization is mass spectrometry used in combination with sample separation. One of the most widely used separation techniques at the front end of a mass spectrometer is high performance liquid chromatography (HPLC). A unique feature of HPLC is its specificity to the amino acid sequence of separated peptides and proteins. This specificity may provide additional information about the peptides or proteins under study which is complementary to the mass spectrometry data. The value of this information for proteomics has been recognized in the past few decades, which has stimulated significant effort in the development and implementation of computational and theoretical models for the prediction of peptide retention time for a given sequence. Here we review the advances in this area and the utility of predicted retention times for proteomic applications.

PMID:
27419248
DOI:
10.1039/c6an00919k
[Indexed for MEDLINE]

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