Machine learning accelerates the discovery of epitope-based dual-bioactive peptides against skin infections.

Journal: International journal of antimicrobial agents
PMID: 39486466

Abstract

OBJECTIVES: Skin injuries and infections are an inevitable part of daily human life, particularly with chronic wounds, becoming an increasing socioeconomic burden. In treating skin infections and promoting wound healing, bioactive peptides may hold significant potential, particularly those possessing antimicrobial and anti-inflammatory properties. However, obtaining these peptides solely through traditional wet laboratory experiments is costly and time-consuming, and peptides identified by current computer-assisted predictive models largely lack validation of their effects via wet laboratory experiments. Consequently, this study aimed to integrate computer-assisted methods and traditional wet laboratory experiments to identify anti-inflammatory and antimicrobial peptides.

Authors

  • Le Fu
    Department of Radiology, Shanghai First Maternity and Infant Hospital, Tongji University School of Medicine, Shanghai, China. Electronic address: fule0125@qq.com.
  • Xu Zheng
    Department of Orthopaedic Surgery, Shanghai Sixth People's Hospital Affiliated to Shanghai Jiao Tong University School of Medicine, Shanghai, China.
  • Jiawen Luo
  • Yiyu Zhang
    School of Computer and Control Engineering, Yantai University, No. 30, Qingquan Road, Laishan District, Yantai City, 264005, Shandong Province, China.
  • Xue Gao
    Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China.
  • Li Jin
    State Key Laboratory of Genetic Engineering and Innovation Center of Genetics and Development, School of Life Sciences, Fudan University, Shanghai, China.
  • Wenting Liu
    Human Genetics, Genome Institute of Singapore, Singapore, Singapore. liuwenting@ucla.edu.
  • Chaoqun Zhang
    Department of Critical Care Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, PR China.
  • Dongyu Gao
    Department of Critical Care Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, PR China.
  • Bocheng Xu
    ZJU-Hangzhou Global Science and Technology Innovation Center, Zhejiang University, Hangzhou, 311215, China.
  • Qingru Jiang
    Department of Critical Care Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, PR China. Electronic address: jiangqr3@mail.sysu.edu.cn.
  • Shuli Chou
    Department of Critical Care Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, PR China.
  • Liang Luo
    Department of Critical Care Medicine, The Seventh Affiliated Hospital, Sun Yat-Sen University, Shenzhen, PR China. Electronic address: luoliang@mail.sysu.edu.cn.

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