International journal of cosmetic science · 2026
Mechanistic understanding and peptide ingredient screening for type III collagen via biological knowledge graph and molecular docking.
СтатьяНазвание и аннотация: Перевод в очереди
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Zang Shanshan, Chen Zhiqiang, Qiu Jie, Gu Yao, Li Nan, Zhang Liang, Wang Wanze, Chen Xinxin, Ma Yuan, Pan Amiao, Lan Wei, Yu Lun, Wang Meijie, Wang Shaohua
Аннотация
OBJECTIVE: Type III collagen plays a key role in maintaining skin elasticity and dermal resilience, yet its decline is associated with visible signs of skin ageing. This study aimed to establish a data-driven approach to identify cosmetic peptides with potential to enhance type III collagen through multi-target regulation.
METHODS: A combined strategy integrating natural language processing (NLP) and knowledge graph (KG) analysis was applied to systematically identify targets associated with type III collagen regulation. Peptides listed in the Inventory of Existing Cosmetic Ingredients in China (IECIC) were screened based on structure-based molecular docking with multiple targets. Candidate peptides were selected for experimental evaluation using human dermal fibroblasts and ex vivo skin models.
RESULTS: By integrating large-scale literature mining with NLP and KG-based gene interaction analysis, we constructed a comprehensive network of genes involved in type III collagen regulation, covering processes such as collagen synthesis, degradation and extracellular matrix (ECM) organization. Based on this network, candidate peptides with predicted multi-target interactions were prioritized through structure-based screening. In vitro, four selected peptides-palmitoyl tetrapeptide-7, acetyl hexapeptide-8, palmitoyl tripeptide-1 and palmitoyl tetrapeptide-10-significantly increased type III collagen levels following UV exposure, without detectable cytotoxicity. The combination of these peptides exhibited a greater effect than individual components. In ex vivo skin tissues, the peptide combination further enhanced the levels of type I, III and IV collagens, indicating a broader modulatory effect on dermal ECM components.
CONCLUSION: This study provides a practical framework for the identification of cosmetic peptides targeting collagen regulation. The findings support a multi-target approach and suggest that peptide combinations may enhance collagen-related outcomes relevant to skin ageing applications.
METHODS: A combined strategy integrating natural language processing (NLP) and knowledge graph (KG) analysis was applied to systematically identify targets associated with type III collagen regulation. Peptides listed in the Inventory of Existing Cosmetic Ingredients in China (IECIC) were screened based on structure-based molecular docking with multiple targets. Candidate peptides were selected for experimental evaluation using human dermal fibroblasts and ex vivo skin models.
RESULTS: By integrating large-scale literature mining with NLP and KG-based gene interaction analysis, we constructed a comprehensive network of genes involved in type III collagen regulation, covering processes such as collagen synthesis, degradation and extracellular matrix (ECM) organization. Based on this network, candidate peptides with predicted multi-target interactions were prioritized through structure-based screening. In vitro, four selected peptides-palmitoyl tetrapeptide-7, acetyl hexapeptide-8, palmitoyl tripeptide-1 and palmitoyl tetrapeptide-10-significantly increased type III collagen levels following UV exposure, without detectable cytotoxicity. The combination of these peptides exhibited a greater effect than individual components. In ex vivo skin tissues, the peptide combination further enhanced the levels of type I, III and IV collagens, indicating a broader modulatory effect on dermal ECM components.
CONCLUSION: This study provides a practical framework for the identification of cosmetic peptides targeting collagen regulation. The findings support a multi-target approach and suggest that peptide combinations may enhance collagen-related outcomes relevant to skin ageing applications.