Characterization of the protein and peptide of excipient zein by the multi-enzyme digestion coupled with nano-LC-MS/MS. (15th August 2020)

• Record Type: Journal Article
• Authors: Li, Menglin; Zheng, Hao; Lin, Miao; Zhu, Wenwen; Zhang, Jinlan
• Is Part Of: Food chemistry. Volume 321(2020)
• Publication Date: 2020-08-15
• Subjects: Excipient zein -- Multi enzyme digestion -- Proteomics -- Peptidomics -- In silico analysis; Food -- Analysis -- Periodicals; Food -- Composition -- Periodicals; 664
• DOI: 10.1016/j.foodchem.2020.126712
• Languages: English
• ISSNs: 0308-8146

Abstract

Highlights: Multi-enzyme digestion can improve protein sequence coverage as well as the number of detectable zein proteins. 51 proteins were identified in excipient zein, including 37 zeins and 14 non-zein proteins. 420 zein peptides were identified, with 116 predicted as potentially bioactive by using in silico approach. Abstract: Zein, a class of prolamine proteins extracted from maize, is extensively used in the food and pharmaceutical industries. Characterization of its components is essential for quality control and safety evaluation. We performed in silico digestion of zein proteins using tandem combinations of different proteinases, to improve protein sequence coverage and subsequent identification by nano-LC-MS/MS analysis. Trypsin/chymotrypsin yielded the highest protein sequence coverage of up to 79.5% and increased the number of proteins from 11 to 35 compared to trypsin/Lys-C. Besides, SDS-PAGE analysis revealed 37 proteins in the zein extract, as well as the possibility of protein polymers. Also, 420 peptides originating from 71 proteins were identified, of which 116 were predicted as bioactive by in silico approach. In conclusion, in silico prediction coupled with multi-enzyme digestion can significantly improve the coverage of complex zein protein proteome, and the potential function of zein proteins and peptides need be further investigated.