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

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 <i>K</i><sub>d</sub> = 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<sub>2</sub>O<sub>2</sub> 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.

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Publication Details

Journal
Journal of Agricultural and Food Chemistry
Published
2026-02-03
DOI
https://doi.org/10.1021/acs.jafc.5c14216
Primary Topic
Machine Learning in Bioinformatics
Type
article
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article

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

Kai Na, Li Zhang, Xia Guo, T. Hu et al.
Journal of Agricultural and Food Chemistry
Machine Learning in Bioinformatics
article

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

Kai Na, Li Zhang, Xia Guo, T. Hu, M. Yu, Qian Lin, Hua Xie, Shujing Chen, Tianfei Yu
article en

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 <i>K</i><sub>d</sub> = 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<sub>2</sub>O<sub>2</sub> 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.

Journal of Agricultural and Food ChemistryVol. 74(5)
Minzu University of China (CN)
Industry, innovation and infrastructure
Openalex Percentile: Top 69%
Machine Learning in Bioinformatics
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Discovery of High-Affinity Glutamine-Derived Peptides from Wheat Gliadin Targeting CaSR: a Computational Approach Integrating Deep Learning and Molecular Dynamics — Kai Na, Li Zhang, et al. · Journal of Agricultural and Food Chemistry (2026) | TGRS Research Map | TGRS