<HashMap><database>iProX</database><scores/><additional><omics_type>Proteomics</omics_type><submitter>Jinlan Zhang</submitter><species>Zea Mays</species><full_dataset_link>http://www.iprox.org/page/project.html?id=IPX0001710000</full_dataset_link><submitter_email>zhjl@imm.ac.cn</submitter_email><submitter_affiliation>Institute of Meteria Medica, Chinese Academy of Medical Sciences &amp;amp; Peking Union Medical College</submitter_affiliation><sample_protocol></sample_protocol><repository>iProX</repository><data_protocol></data_protocol><pubmed_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.</pubmed_abstract><pubmed_title>Characterization of the protein and peptide of excipient zein by the multi-enzyme digestion coupled with nano-LC-MS/MS.</pubmed_title><pubmed_authors>Li Menglin M, Zheng Hao H, Lin Miao M, Zhu Wenwen W, Zhang Jinlan J</pubmed_authors></additional><is_claimable>false</is_claimable><name>Identification of zein proteome by multi-enzyme digestion</name><description>Zeins are a class of prolamine proteins extracted from maize, and are extensively used in the food and pharmaceutical industries. Therefore, characterization of its components is essential for quality control and safety evaluation. However, zein proteins have low abundance of the trypsin targets lysine and arginine, thereby requiring enzymes of different cleavage sites for shotgun proteomic analyses. To this end, we performed in silico digestion of zein proteins using tandem combinations of trypsin/Lys-C, trypsin/chymotrypsin and trypsin/thermolysin, in order to improve protein sequence coverage and subsequent identification by LC-MS/MS analysis. Trypsin/chymotrypsin yielded the highest protein sequence coverage of up to 79.5% by the filter-aided sample preparation (FASP) method, and increased the number of detectable proteins from 11 to 35 compared to trypsin/Lys-C. Furthermore, SDS-PAGE revealed 37 proteins in the zein extract, as well as the possibility of protein polymers. A total of 51 proteins were detected by FASP and in-gel digestion, including 37 zein and 14 non-zein proteins. In addition, 420 peptides originating from 71 zein proteins were identified, of which 116 were predicted as bioactive. In conclusion, in silico digestion coupled with multi enzyme digestion can significantly improve the proteomic and peptidomic analysis of complex protein extracts.</description><dates><publication>Thu Jul 25 00:00:00 BST 2019</publication></dates><accession>PXD014743</accession><cross_references><TAXONOMY>4577</TAXONOMY><pubmed>32247179</pubmed></cross_references></HashMap>