Proteomic analysis of sweet algerian apricot kernels (Prunus armeniaca L.) by combinatorial peptide ligand libraries and LC-MS/MS.
Identifieur interne : 000408 ( Main/Exploration ); précédent : 000407; suivant : 000409Proteomic analysis of sweet algerian apricot kernels (Prunus armeniaca L.) by combinatorial peptide ligand libraries and LC-MS/MS.
Auteurs : Hamida Ghorab [Algérie] ; Carmen Lammi [Italie] ; Anna Arnoldi [Italie] ; Zahia Kabouche [Algérie] ; Gilda Aiello [Italie]Source :
- Food chemistry [ 1873-7072 ] ; 2018.
Descripteurs français
- KwdFr :
- MESH :
English descriptors
- KwdEn :
- MESH :
- chemical : Peptide Library, Peptides.
- Proteomics, Prunus armeniaca, Tandem Mass Spectrometry.
Abstract
An investigation on the proteome of the sweet kernel of apricot, based on equalisation with combinatorial peptide ligand libraries (CPLLs), SDS-PAGE, nLC-ESI-MS/MS, and database search, permitted identifying 175 proteins. Gene ontology analysis indicated that their main molecular functions are in nucleotide binding (20.9%), hydrolase activities (10.6%), kinase activities (7%), and catalytic activity (5.6%). A protein-protein association network analysis using STRING software permitted to build an interactomic map of all detected proteins, characterised by 34 interactions. In order to forecast the potential health benefits deriving from the consumption of these proteins, the two most abundant, i.e. Prunin 1 and 2, were enzymatically digested in silico predicting 10 and 14 peptides, respectively. Searching their sequences in the database BIOPEP, it was possible to suggest a variety of bioactivities, including dipeptidyl peptidase-IV (DPP-IV) and angiotensin converting enzyme I (ACE) inhibition, glucose uptake stimulation and antioxidant properties.
DOI: 10.1016/j.foodchem.2017.07.054
PubMed: 28873655
Affiliations:
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Le document en format XML
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Gene ontology analysis indicated that their main molecular functions are in nucleotide binding (20.9%), hydrolase activities (10.6%), kinase activities (7%), and catalytic activity (5.6%). A protein-protein association network analysis using STRING software permitted to build an interactomic map of all detected proteins, characterised by 34 interactions. In order to forecast the potential health benefits deriving from the consumption of these proteins, the two most abundant, i.e. Prunin 1 and 2, were enzymatically digested in silico predicting 10 and 14 peptides, respectively. 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