Issue 61, 2020, Issue in Progress

Evaluation of the site-unspecified peptide identification method for proteolytic peptide mapping

Abstract

Proteases are widely used in the food industry to hydrolyze proteins and prepare bioactive peptides. Peptide mapping identification supports the application of proteases in the food industry. The site-specified peptide identification method, which was developed for site-specific proteases like trypsin, is relatively mature and reliable but cannot be applied using most industrial proteases with weak site specificity. To address this issue, the performance and reliability of the site-unspecified peptide identification method should be investigated and evaluated. In this study, tryptic hydrolysates of a single protein and a protein mixture were used to evaluate the site-unspecified identification method. The species origin of the hydrolyzed proteins was not specified in a database search, meaning that millions of protein sequences were included for calculating and matching. At least 98% of the tryptic peptides were successfully identified via the site-unspecified method, demonstrating that the site-unspecified method shows promising reliability. Moreover, the site-unspecified method identified more peptides than the site-specified method, including those from the low-frequency site-unspecific hydrolysis of trypsin, suggesting that the method has strong capabilities for peptide mapping. The results indicate the applicability of the site-unspecified peptide identification method in the study of site-unspecific industrial proteases.

Graphical abstract: Evaluation of the site-unspecified peptide identification method for proteolytic peptide mapping

Article information

Article type
Paper
Submitted
12 May 2020
Accepted
18 Sep 2020
First published
07 Oct 2020
This article is Open Access
Creative Commons BY-NC license

RSC Adv., 2020,10, 37182-37186

Evaluation of the site-unspecified peptide identification method for proteolytic peptide mapping

H. B. Wang, F. Zeng, Y. Y. Wang, X. Li, S. H., Y. M. Li, Y. F. Wang, Y. H. Liu and F. P. Lu, RSC Adv., 2020, 10, 37182 DOI: 10.1039/D0RA04226A

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