TY - JOUR
T1 - Improved short peptide identification using HILIC-MS/MS
T2 - Retention time prediction model based on the impact of amino acid position in the peptide sequence
AU - Le Maux, Solène
AU - Nongonierma, Alice B.
AU - Fitzgerald, Richard J.
N1 - Publisher Copyright:
© 2014 Elsevier Ltd. All rights reserved.
PY - 2015/4/15
Y1 - 2015/4/15
N2 - Short peptides can have interesting beneficial effects but they are difficult to identify in complex mixtures. We developed a method to improve short peptide identification based on HILIC-MS/MS. The apparent hydrophilicity of peptides was determined as a function of amino acid position in the sequence. This allowed the differentiation of peptides with the same amino acid composition but with a different sequence (homologous peptides). A retention time prediction model was established using the hydrophilicity and peptide length of 153 di- to tetrapeptides. This model was proven to be reliable (R2 = 0.992), it was validated using statistical methods and a mixture of 14 synthetic peptides. A whey protein hydrolysate was analysed to assess the ability of the model to identify unknown peptides. In parallel to milk protein database and de novo searches, the retention time prediction model permitted reduction and ranking of potential short peptides, including homologous peptides, present in the hydrolysate.
AB - Short peptides can have interesting beneficial effects but they are difficult to identify in complex mixtures. We developed a method to improve short peptide identification based on HILIC-MS/MS. The apparent hydrophilicity of peptides was determined as a function of amino acid position in the sequence. This allowed the differentiation of peptides with the same amino acid composition but with a different sequence (homologous peptides). A retention time prediction model was established using the hydrophilicity and peptide length of 153 di- to tetrapeptides. This model was proven to be reliable (R2 = 0.992), it was validated using statistical methods and a mixture of 14 synthetic peptides. A whey protein hydrolysate was analysed to assess the ability of the model to identify unknown peptides. In parallel to milk protein database and de novo searches, the retention time prediction model permitted reduction and ranking of potential short peptides, including homologous peptides, present in the hydrolysate.
KW - Amino acid coefficients
KW - Di-, tri- and tetrapeptides
KW - N-, C-terminal
KW - Retention time prediction
KW - UPLC-HILIC
UR - http://www.scopus.com/inward/record.url?scp=84908608722&partnerID=8YFLogxK
U2 - 10.1016/j.foodchem.2014.10.104
DO - 10.1016/j.foodchem.2014.10.104
M3 - Article
C2 - 25466098
AN - SCOPUS:84908608722
SN - 0308-8146
VL - 173
SP - 847
EP - 854
JO - Food Chemistry
JF - Food Chemistry
ER -