Design and molecular mechanism investigation of ALK inhibitors based on virtual screening and structural descriptor modeling.

Journal: Journal of receptor and signal transduction research
Published Date: May 11, 2025

Abstract

To address the challenges of target specificity and drug resistance in Anaplastic lymphoma kinase (ALK) inhibition, this study conducted a virtual screening of the BindingDB database, yielding 711 potential ALK inhibitors. Four QSAR models were established using structural clustering and machine learning to elucidate structure-activity relationships. Through substituent fragment optimization, 72 highly active compounds were designed, among which four promising candidates were identified based on ADMET predictions, retrosynthetic analyses and molecular docking analyses. Molecular dynamics simulations and binding free energy calculations further characterized their binding mechanisms. These findings provide a theoretical framework for the rational design of next-generation ALK inhibitors.

Authors

  • Ya-Kun Zhang
    College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, People's Republic of China.
  • Jian-Bo Tong
    College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, People's Republic of China.
  • Yue Sun
    Department of Rheumatology, The First Affiliated Hospital of Anhui University of Chinese Medicine, Hefei, Anhui, China.
  • Jia-Le Li
    College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, People's Republic of China.
  • Qi Hou
    College of Chemistry and Chemical Engineering, Shaanxi University of Science and Technology, Xi'an, People's Republic of China.

Keywords

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