再生医学
肽
计算生物学
皮肤老化
干细胞
细胞
虚拟筛选
小分子
生物
生物信息学
计算机科学
化学
细胞生物学
生物化学
药物发现
医学
皮肤病科
作者
Wang Feifei,Su Wenrou,Kang Sining,Zhu Siyu,Fu Xiaolei,Junxiang Li,Congfen He,Xuhui Li
出处
期刊:Peptides
[Elsevier BV]
日期:2023-08-12
卷期号:169: 171078-171078
被引量:1
标识
DOI:10.1016/j.peptides.2023.171078
摘要
Skin aging refers to a degenerative process that can be affected and regulated by intrinsic and extrinsic factors. The mesenchymal stem cell secretome covers a considerable number of regenerative molecules with anti-aging effects in a wide variety of circumstances. However, it is complex, time-consuming, and costly to identify specific compounds from thousands of natural molecules using conventional methods. With the development of computational biology and machine learning, an efficient workflow was generated to identify novel peptides with anti-aging and skin restoration potential. One of the candidate peptides was discovered and subsequently truncated to a novel peptide named EQ-9, with promising anti-aging effects for topical applications at a concentration of 10 ppm validated by experimental validation. The above-described paradigm is expected to be further applied to the virtual screening of novel peptide molecules targeting specific biological functions from a wide variety of natural resources.
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