Discovery of High-Affinity Glutamine-Derived Peptides from Wheat Gliadin Targeting CaSR: a Computational Approach Integrating Deep Learning and Molecular Dynamics

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Authors: Tianfei Yu, T. Hu, Kai Na, Qian Lin, Shujing Chen, Hua Xie, M. Yu, Li Zhang, Xiaohua Guo
Cited by: 3
References: 78

Abstract

Calcium-sensing receptor (CaSR)-targeting agonist peptides play a crucial role in maintaining intestinal homeostasis. In this study, we integrated deep learning, virtual screening, and molecular simulation to develop Peptide_MDI, an intelligent screening platform built on Nextflow. From 2798 candidate peptides derived from wheat gliadin, we identified RLSYQFPFYP (designated CaSR_TP_1) as the lead peptide, which binds CaSR with a dissociation constant K d = 74.4 nM. Functionally, CaSR_TP_1 upregulates tight junction proteins, promotes cell proliferation, enhances antioxidant defenses, and reduces the transcriptional levels of TNF-α, IL-8, and IL-6. Mechanistically, it attenuates H 2 O 2 induced oxidative stress by activating the CaSR/PLCγ1/Rac1/MAPK signaling cascade. In conclusion, the CaSR-targeting peptide RLSYQFPFYP was identified with high affinity (nanomolar range) using Peptide_MDI, establishing a scalable technological framework for discovering bioactive peptides that promote gut homeostasis and for designing next-generation smart peptide therapeutics.

Fields of Study & Subjects

Machine Learning in Bioinformatics Computational Drug Discovery Methods Protein Hydrolysis and Bioactive Peptides

Publication details

Journal / source
Journal of Agricultural and Food Chemistry
Publisher
American Chemical Society (ACS)
Volume
74
Issue
5
Pages
4486–4501
Publication date
3 February 2026
Language
EN