ArticleFoods (Basel, Switzerland)2026
Proteomic Insights into Effects of a Camel Milk-Derived Peptide on Insulin Resistance: Modulation of Metabolic, Oxidative, and Signaling Pathways.
Article in Foods (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Insulin resistance is a multifactorial cellular state involving coordinated alterations in protein homeostasis and organelle function; however, its proteome-wide organization and response to bioactive peptides remain incompletely defined. In this study, we employed DIA-based quantitative proteomics to characterize global protein abundance changes associated with insulin resistance in HepG2 cells and to examine proteomic remodeling following treatment with a camel milk-derived peptide (P2). Comparative proteomic profiling revealed that insulin-resistant cells exhibit extensive reorganization of protein networks linked to redox regulation, endoplasmic reticulum protein processing, mitochondrial metabolism, lysosomal function, and extracellular matrix-associated components. Gene Ontology, KEGG pathway, protein domain, and subcellular localization enrichment analyses consistently indicated disruption of organelle-associated proteomic architecture rather than isolated pathway perturbations. Peptide TYYPPQ treatment was associated with selective, rather than global, proteomic shifts, prominently affecting mitochondrial and peroxisome-associated protein groups as well as extracellular and secretory proteins. Enrichment and localization analyses suggest that peptide exposure reshapes organelle-linked protein representation patterns without implying direct activation of signaling pathways or physiological restoration. Collectively, these results define insulin resistance and peptide responsiveness at a systems-level proteomic resolution and establish an organelle-resolved framework for interpreting peptide-induced proteomic remodeling in insulin-resistant hepatocyte models. This dataset provides a foundation for future targeted functional validation of candidate pathways identified through proteomic association.
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