On peptidede novo sequencing: a new approach

Bruni, Renato; Gianfranceschi, G.; Koch, G.

doi:10.1002/psc.595

Cited by 31 publications

(18 citation statements)

References 28 publications

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“…5B and C, predominant mass peaks at m/z 430.20 and m/z 231.20, as well as their ion peaks, were analyzed by manual calculation to be Asn-Thr-Val-Pro (NTVP) and Ile-Val (IV) or Leu-Val (LV). According to the principle of various classical types of amino acid fragments, a-ion, b-ion, c-ion, x-ion, y-ion and z-ion, which have unique weights depending on their components, are detected by the following criteria: a-ions, molecular mass of amino acid residue plus 27; b-ions, plus 1; c-ions, plus 18; x-ions, plus 45; y-ions, plus 19; and z-ions, plus 2 (Bruni, Gianfranceschi, & Koch, 2005;Li et al, 2007) Nevertheless, the peptide sequence at m/z 231.20 (Fig. 5C) should be confirmed, because I (Ile) and L (Leu) have the same molecular weight of 131.…”

Section: Characterization Of Peptide Sequences In the Adsorbatementioning

confidence: 99%

Hydrophobicity exerts different effects on bioavailability and stability of antioxidant peptide fractions from casein during simulated gastrointestinal digestion and Caco-2 cell absorption

Xie

Wang

Jiang

et al. 2015

Food Research International

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Section: Characterization Of Peptide Sequences In the Adsorbatementioning

confidence: 99%

Hydrophobicity exerts different effects on bioavailability and stability of antioxidant peptide fractions from casein during simulated gastrointestinal digestion and Caco-2 cell absorption

Xie

Wang

Jiang

et al. 2015

Food Research International

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“…Another important area of development is bioinformatic analysis software for de novo peptide sequencing [37–40, 42, 60, 61], and those combining de novo peptide sequencing (sequence tag) with MS/MS database searching for protein identification [41, 62]. Performance of de novo sequencing is likely crucial to successful amyloidosis typing due to (1) high likelihood of mutations and immunoglobulin variable regions that are not in the sequence database, and (2) increased likelihood of chemical modifications due to FFPE processing.…”

Section: Outlook For Proteomics In Amyloidosis Typingmentioning

confidence: 99%

Proteomics in Molecular Diagnosis: Typing of Amyloidosis

Loo

Mollee

Renaut

et al. 2011

BioMed Research International

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Amyloidosis is a group of disorders caused by deposition of misfolded proteins as aggregates in the extracellular tissues of the body, leading to impairment of organ function. Correct identification of the causal amyloid protein is absolutely crucial for clinical management in order to avoid misdiagnosis and inappropriate, potentially harmful treatment, to assess prognosis and to offer genetic counselling if relevant. Current diagnostic methods, including antibody-based amyloid typing, have limited ability to detect the full range of amyloid forming proteins. Recent investigations into proteomic identification of amyloid protein have shown promise. This paper will review the current state of the art in proteomic analysis of amyloidosis, discuss the suitability of techniques based on the properties of amyloidosis, and further suggest potential areas of development. Establishment of mass spectrometry aided amyloid typing procedures in the pathology laboratory will allow accurate amyloidosis diagnosis in a timely manner and greatly facilitate clinical management of the disease.

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“…After possible amino acid (AA) compositions had been determined from the accurate mass value measured in tandem MS, the resulting expected fragment ion signals of permuted sequence propositions were compared with the observed fragment ion information. Bruni et al [19,23] developed a computational analysis procedure obtained by building a mathematical model of peptide sequence determination and by searching for all possible sequences of given components compatible with particular constraints.…”

Section: Introductionmentioning

confidence: 99%

Hydrophilic properties as a new contribution for computer-aided identification of short peptides in complex mixtures

et al. 2012

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A new method to predict elementary amino acid (AA) composition of peptides (molar mass <1,000 g/mol) is described. This procedure is based on a computer-aided method using three combined analyses-reversed phase liquid chromatography (RPLC), hydrophilic interaction chromatography (HILIC) and capillary electrophoresis coupled with mass spectrometry-and using a software calculating all possible amino acid combinations from the mass of any given peptide. The complementarity between HILIC and RPLC was demonstrated. Peptide retention prediction in HILIC was successfully modelled, and the achieved prediction accuracy was as high as r²=0.97. This mathematical model, based on amino acid retention contributions and peptide length, provided the information about peptide hydrophilicity that was not redundant with its hydrophobicity. Correlations between respectively the hydrophobicity coefficients and RPLC retention time, hydrophilicity and HILIC retention time, and electrophoretic mobility and migration time were used for ranking all potential AA combinations corresponding to the given mass. The essential contribution of HILIC in this identification strategy and the need to combine the three models to significantly increase identification capabilities were both shown. Applied to an 18-standard peptide mixture, the identification procedure enabled the actual AA combination determination of the 14 di- to pentapeptides, in addition to an over 98 % reduction of possible combination numbers for the four hexapeptides. This procedure was then applied to the identification of 24 unknown peptides in a rapeseed protein hydrolysate. The effective AA composition was found for ten peptides, whereas for the 14 other peptides, the number of possible combinations was reduced by over 95 % thanks to the association of the three analyses. Finally, as a result of the information provided by the analytical techniques about peptides present in the mixture, the proposed method could become a highly valuable tool to recover bioactive peptides from undefined protein hydrolysates.

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On peptidede novo sequencing: a new approach

Cited by 31 publications

References 28 publications

Hydrophobicity exerts different effects on bioavailability and stability of antioxidant peptide fractions from casein during simulated gastrointestinal digestion and Caco-2 cell absorption

Hydrophobicity exerts different effects on bioavailability and stability of antioxidant peptide fractions from casein during simulated gastrointestinal digestion and Caco-2 cell absorption

Proteomics in Molecular Diagnosis: Typing of Amyloidosis

Hydrophilic properties as a new contribution for computer-aided identification of short peptides in complex mixtures

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