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