In Silico Screening and Identification of Functional Peptides from Yak Bone Collagen Hydrolysates: Antioxidant and Osteoblastic Activities

Collagen peptides are recognized for their diverse bioactivities; however, efficiently screening potent peptides from hydrolysates remains challenging. This study employed an integrated strategy that combined in silico antioxidant activity prediction and molecular docking to myeloperoxidase (MPO) to screen active peptides derived from yak bone collagen hydrolysates. Focusing on low molecular weight peptides, containing motifs such as GVM, GLP, GPM, and GPQ, we identified nine antioxidant peptides (KC1-KC9). Their activities were validated through in vitro free radical scavenging assays, with peptide KC7 demonstrating superior performance. Furthermore, peptide KC7 promoted proliferation, differentiation, and mineralization in MC3T3-E1 cells by upregulating osteogenic markers such as Runx2 and osteocalcin, modulating the Wnt/β-catenin and PI3K/Akt pathways, and reducing the Bax/Bcl-2 ratio. These results highlight KC7's dual capacity to mitigate oxidative stress and potentially reduce apoptotic susceptibility, thereby stimulating osteogenesis. This positions peptide KC7 as a promising candidate for bone regeneration and oxidative stress-related disorders. Moreover, this study underscores the effectiveness of integrating computational and experimental approaches for the discovery of multifunctional natural peptides.

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Publication Details

Journal
International Journal of Molecular Sciences
Published
2025-05-10
DOI
https://doi.org/10.3390/ijms26104570
Citations
1
Primary Topic
Protein Hydrolysis and Bioactive Peptides
Type
article
Field-Weighted Citation Impact
0.81

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article

In Silico Screening and Identification of Functional Peptides from Yak Bone Collagen Hydrolysates: Antioxidant and Osteoblastic Activities

Yousi Fu, Yali Wang, Yue Wang, Baishan Fang
1 citations
International Journal of Molecular Sciences
Protein Hydrolysis and Bioactive Peptides
0.81
article

In Silico Screening and Identification of Functional Peptides from Yak Bone Collagen Hydrolysates: Antioxidant and Osteoblastic Activities

Yousi Fu, Yali Wang, Yue Wang, Baishan Fang
article en
1 citations

Abstract

Collagen peptides are recognized for their diverse bioactivities; however, efficiently screening potent peptides from hydrolysates remains challenging. This study employed an integrated strategy that combined in silico antioxidant activity prediction and molecular docking to myeloperoxidase (MPO) to screen active peptides derived from yak bone collagen hydrolysates. Focusing on low molecular weight peptides, containing motifs such as GVM, GLP, GPM, and GPQ, we identified nine antioxidant peptides (KC1-KC9). Their activities were validated through in vitro free radical scavenging assays, with peptide KC7 demonstrating superior performance. Furthermore, peptide KC7 promoted proliferation, differentiation, and mineralization in MC3T3-E1 cells by upregulating osteogenic markers such as Runx2 and osteocalcin, modulating the Wnt/β-catenin and PI3K/Akt pathways, and reducing the Bax/Bcl-2 ratio. These results highlight KC7's dual capacity to mitigate oxidative stress and potentially reduce apoptotic susceptibility, thereby stimulating osteogenesis. This positions peptide KC7 as a promising candidate for bone regeneration and oxidative stress-related disorders. Moreover, this study underscores the effectiveness of integrating computational and experimental approaches for the discovery of multifunctional natural peptides.

International Journal of Molecular SciencesVol. 26(10)
United States Department of Energy (US), Xiamen University (CN), Michigan State University (US)
National Natural Science Foundation of China
Openalex Percentile: Top 28%
Protein Hydrolysis and Bioactive Peptides
0.81
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In Silico Screening and Identification of Functional Peptides from Yak Bone Collagen Hydrolysates: Antioxidant and Osteoblastic Activities — Yousi Fu, Yali Wang, et al. · International Journal of Molecular Sciences (2025) | TGRS Research Map | TGRS