Influence of Mobile Phase Gradients on the Retention and Separation of Peptides from a Cytochrome-c Digest by Reversed-Phase Liquid Chromatography

Riddle, Lance A.; Guiochon, Georges

doi:10.1365/s10337-006-0839-1

Cited by 12 publications

(7 citation statements)

References 25 publications

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“…For simplicity, we refer to the values in this iRT‐C18 scale as iRT values. The use of different columns, ion‐pairing agents, or organic modifiers can affect the elution order of peptides []. If different types of resins (e.g.…”

Section: Resultsmentioning

confidence: 99%

“…We have shown that the linearity assumption is valid across different LC systems. While the use of other mobile phases can lead to changes in the elution order, which would require the definition of a new scale [], the linearity is largely conserved for different resin types typically used in proteomics experiments []. The iRT concept shows some similarity to the SSRCalc approach [].…”

Section: Discussionmentioning

confidence: 99%

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Using iRT, a normalized retention time for more targeted measurement of peptides

et al. 2012

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Multiple reaction monitoring (MRM) has recently become the method of choice for targeted quantitative measurement of proteins using mass spectrometry. The method, however, is limited in the number of peptides that can be measured in one run. This number can be markedly increased by scheduling the acquisition if the accurate retention time (RT) of each peptide is known. Here we present iRT, an empirically derived dimensionless peptide-specific value that allows for highly accurate RT prediction. The iRT of a peptide is a fixed number relative to a standard set of reference iRT-peptides that can be transferred across laboratories and chromatographic systems. We show that iRT facilitates the setup of multiplexed experiments with acquisition windows more than 4 times smaller compared to in silico RT predictions resulting in improved quantification accuracy. iRTs can be determined by any laboratory and shared transparently. The iRT concept has been implemented in Skyline, the most widely used software for MRM experiments.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Using iRT, a normalized retention time for more targeted measurement of peptides

et al. 2012

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“…[75][76][77] The separation doesn't yet ensure a reliable identification of the isobars, because Both of these values are not fundamental to molecules and are sensitive to experimental conditions, which may not be always reproduced with sufficient accuracy. [78][79] In contrast, vibronic transitions in isolated molecules and ions reflect differences in energies between their initial and terminal quantum states, making vibrationally resolved electronic spectra unique fundamental fingerprints of such species. Electronic excitation of ions may produce specific to their 3D structure photofragments, which are absent (or low abundant) in the products of thermal-like dissociation.…”

Section: Discussionmentioning

confidence: 99%

Cold ion spectroscopy for structural identifications of biomolecules

Boyarkin

2018

International Reviews in Physical Chemistry

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Over last decade the spectroscopy of cryogenically cold ions isolated in the gas phase has been developed to a new tool for structural elucidations of biological molecules. Cooling allows for vibrational resolution in UV and IR spectra of small to midsize peptides, enabling different multi-laser techniques of conformer-specific spectroscopy. We first briefly overview some fundamental and technical aspects of the cold-ion spectroscopy (CIS) approach and illustrate its application to protonated peptides, carbohydrates and to non-covalent complexes of these biomolecules. The challenges and limitations of CIS in view of its relevance to life-science studies are critically assessed. Finally, we discuss and illustrate some approaches of CIS to analytical identifications of biomolecules, in particular the recently developed method of 2D UV-MS fingerprinting, which combines CIS with high-resolution mass spectrometry.

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“…They constitute an emerging class of therapeutic agents, possessing greater efficacy and selectivity, as well as an inherent lower toxicity profile compared to the conventional small molecules [1] . For the separation of peptides, reversed-phase high performance liquid chromatography (RP-HPLC) has been most widely employed [2] , [3] , [4] , [5] . In order to identify peptides in complex mixtures, RP-HPLC is combined with mass spectrometry (LC-MS), having an excellent sensitivity and selectivity [6] , [7] .…”

Section: Introductionmentioning

confidence: 99%

“…In this work, different fused-core column chemistries (HALO ® C18, Peptide ES-C18, RP-amide and Phenyl-hexyl) are compared and evaluated using a mixture of synthetic peptides. In addition to the selectivity differences of the stationary phases, the selectivity effects of the mobile phase composition are studied as well [2] , [38] , [39] , [40] , [41] . Finally, reversed-phase fused-core peptide retention models were constructed on the different chromatographic systems, containing a novel in-silico calculated amino acid descriptor.…”

Section: Introductionmentioning

confidence: 99%

Reversed-phase fused-core HPLC modeling of peptides

D׳Hondt

Gevaert

Stalmans

et al. 2013

Journal of Pharmaceutical Analysis

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Different fused-core stationary phase chemistries (C18, Amide, Phenyl-hexyl and Peptide ES-C18) were used for the analysis of 21 structurally representative model peptides. In addition, the effects of the mobile phase composition (ACN or MeOH as organic modifier; formic acid or acetic acid, as acidifying component) on the column selectivity, peak shape and overall chromatographic performance were evaluated. The RP-amide column, combined with a formic acid–acetonitrile based gradient system, performed as best. A peptide reversed-phase retention model is proposed, consisting of 5 variables: log SumAA, log Sv, clog P, log nHDon and log nHAcc. Quantitative structure-retention relationship (QSRR) models were constructed for 16 different chromatographic systems. The accuracy of this peptide retention model was demonstrated by the comparison between predicted and experimentally obtained retention times, explaining on average 86% of the variability. Moreover, using an external set of 5 validation peptides, the predictive power of the model was also demonstrated. This peptide retention model includes the novel in-silico calculated amino acid descriptor, AA, which was calculated from log P, 3D-MoRSE, RDF and WHIM descriptors.

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Influence of Mobile Phase Gradients on the Retention and Separation of Peptides from a Cytochrome-c Digest by Reversed-Phase Liquid Chromatography

Cited by 12 publications

References 25 publications

Using iRT, a normalized retention time for more targeted measurement of peptides

Using iRT, a normalized retention time for more targeted measurement of peptides

Cold ion spectroscopy for structural identifications of biomolecules

Reversed-phase fused-core HPLC modeling of peptides

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