Issue 5, 2022

Combining in silico and in vitro approaches to identify endogenous hypoglycemic peptides from human milk

Abstract

Potential endogenous hypoglycemic peptides derived from breast milk were screened by in silico approaches against intestinal glucose absorption- and metabolism-related membrane proteins (i.e., SGLT1, ATPase, and GPR40), and their inhibitory effects on glucose uptake were compared using the human intestinal epithelial Caco-2 cell model. A total of 762 endogenous peptides were obtained from breast milk, and 5 peptides (YPFVEPIPYGFL, LLNQELLLNPTHQIYPV, SPTIPFFDPQIPK, QHWSYGLRPG, and YPVTQPLAPVHNPIS) were shortlisted based on PeptideRanker and HPEPDOCK scores. Further flow cytometer analysis of 2-NBDG uptake showed the remarkable ability of these five peptides to inhibit glucose uptake, in particular YPVTQPLAPVHNPIS. More importantly, the in silico and in vitro gastrointestinal digestion of YPVTQPLAPVHNPIS combined with LC-QTOF-MS/MS demonstrated that the resulting hexapeptide PVTQPL had strong inhibitory activity on glucose uptake and transport (57% and 13% inhibition, respectively). Molecular docking indicated that PVTQPL bound to SGLT1 by forming two hydrogen bonds with Trp257 through the NH2 group and Ile253 through the carbonyl group, ATPase with Phe139 via one arene-H interaction, and GPR40 with Thr39, Ser41, Arg104, Arg2218 and Arg2221 residues through eight hydrogen interactions of its carbonyl groups and hydroxyl groups. The findings of this work open up the possibility of employing endogenous peptides from human milk as the hypoglycemic compounds for the prevention and treatment of diabetes.

Graphical abstract: Combining in silico and in vitro approaches to identify endogenous hypoglycemic peptides from human milk

Supplementary files

Article information

Article type
Paper
Submitted
21 Oct 2021
Accepted
09 Feb 2022
First published
15 Feb 2022

Food Funct., 2022,13, 2899-2912

Combining in silico and in vitro approaches to identify endogenous hypoglycemic peptides from human milk

T. Xiao, J. Zeng, L. Qiu, R. Wang, N. Li, Z. Deng and L. Zheng, Food Funct., 2022, 13, 2899 DOI: 10.1039/D1FO03537A

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