Literature DB >> 28873655

Proteomic analysis of sweet algerian apricot kernels (Prunus armeniaca L.) by combinatorial peptide ligand libraries and LC-MS/MS.

Hamida Ghorab1, Carmen Lammi2, Anna Arnoldi3, Zahia Kabouche1, Gilda Aiello2.   

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.
Copyright © 2017 Elsevier Ltd. All rights reserved.

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Keywords:  Apricot; Combinatorial peptide ligand libraries (CPLL); GO analysis; LC–MS/MS; Proteomics; Prunin

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Year:  2017        PMID: 28873655     DOI: 10.1016/j.foodchem.2017.07.054

Source DB:  PubMed          Journal:  Food Chem        ISSN: 0308-8146            Impact factor:   7.514


  1 in total

1.  Insight of the Functional and Biological Activities of Coconut (Cocos nucifera L.) Protein by Proteomics Analysis and Protein-Based Bioinformatics.

Authors:  Jingrong Ma; Chuang Pan; Haiming Chen; Weijun Chen; Wenxue Chen; Ming Zhang; Qiuping Zhong
Journal:  Molecules       Date:  2022-05-06       Impact factor: 4.927

  1 in total

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