Exploration into the Antitumor Potential of Chiral Oligopeptides: a Comprehensive Study Encompassing Design, Synthesis, In Silico Target Screening and Experimental Validation.

Journal: Journal of chemical information and modeling
Published Date: Jan 5, 2026

Abstract

Peptides are assuming an increasingly critical role in the fields of medicine and cosmetics. Artificial intelligence-assisted drug screening has significantly improved the efficiency and economic feasibility of drug development. Tryptophan and proline, two common natural chiral amino acids, are extensively utilized in peptide owing to their structural restrictive effects. d-type non-natural amino acids, which correspond to their natural counterparts, enhance the antienzymatic hydrolysis capability of peptides and enable unique target interactions. In this study, we designed and synthesized a series of chiral oligopeptides incorporating d-tryptophan and d-proline, and systematically identified their potential molecular targets through an integrated approach combining artificial intelligence-assisted in silico target prediction with experimental biophysical binding assays. In vitro biological activity assays demonstrated that these chiral compounds exhibited potent antitumor effects against human liver cancer BEL-7404 cells, potentially inducing autophagy and apoptosis. The potential targets of the oligopeptides were initially screened using pharmacophore mapping (PharmMapper) in conjunction with reverse molecular docking (GalaxySagittarius-AF), which revealed that poly(ADP-ribose) polymerase 1 (PARP1) is a key target for these compounds. The target was subsequently validated using biolayer interferometry (BLI, dose-response curves), enzyme-linked immunosorbent assay, molecular docking, and molecular dynamics simulations. The quantitative structure-activity relationship (QSAR) of the prepared peptides was analyzed using PaDEL-Descriptor to provide a rational basis for future peptide-based drug design. This study presents a straightforward, cost-effective, and rapid methodology for the chemical synthesis, biological activity validation, and AI-assisted target identification of antitumor chiral linear oligopeptides.

Authors

  • Yang Lv
  • Hongyu Xu
    Department of Gastroenterology, The First Affiliated Hospital of Harbin Medical University, Harbin, Heilongjiang, China.
  • Yue Lei
    Key Laboratory for Photonic and Electronic Bandgap Materials, Ministry of Education, College of Chemistry & Chemical Engineering, Harbin Normal University, Harbin 150025, China.
  • Zeyan Jiang
    Key Laboratory for Photonic and Electronic Bandgap Materials, Ministry of Education, College of Chemistry & Chemical Engineering, Harbin Normal University, Harbin 150025, China.
  • Tong Li
    School of Chinese Pharmacy, Beijing University of Chinese Medicine, Beijing 102488, China.
  • Rui Yan
    Neuromorphic Computing Research Center, College of Computer Science, Sichuan University, Chengdu, 610065, China. Electronic address: [email protected].
  • Xiaodan Wu
    Department of Nuclear Medicine, General Hospital of Northern Theater Command, Shenyang, Liaoning, 110016, China.
  • Yingxue Jin
    Key Laboratory for Photonic and Electronic Bandgap Materials, Ministry of Education, College of Chemistry & Chemical Engineering, Harbin Normal University, Harbin 150025, China.
  • Limin Zhang
    School of Information, University of Arizona, 1103 E. Second Street, Tucson, AZ 85705, USA.
  • ZhiQiang Wang
    The Affiliated Mental Health Center of Jiangnan University, Wuxi Mental Health Center, Wuxi 214151, Jiangsu, China.

Keywords

No keywords available for this article.

External Resources

Popular Topics
Recent Journals