Structure-Guided Discovery of CHI3L1 Inhibitors from Ultralarge Chemical Spaces for Glioblastoma Therapy

Insights

Researchers identified a novel compound, 9e, that effectively inhibits Chitinase 3-like 1 (CHI3L1) in glioblastoma models. This discovery offers a promising new therapeutic strategy for aggressive brain tumors by targeting the CHI3L1-STAT3 pathway.

Area of Science:

  • Oncology
  • Pharmacology
  • Biochemistry

Background:

  • Glioblastoma (GBM) is an aggressive brain tumor with poor prognosis and limited treatment options.
  • Chitinase 3-like 1 (CHI3L1) is implicated in GBM progression and immune evasion, making it a potential therapeutic target.
  • Targeting CHI3L1 offers a novel strategy to overcome GBM's therapeutic resistance.

Purpose of the Study:

  • To identify novel inhibitors of Chitinase 3-like 1 (CHI3L1) for glioblastoma treatment.
  • To explore the efficacy of identified inhibitors in preclinical GBM models.
  • To validate the potential of structure-guided virtual screening for drug discovery in oncology.

Main Methods:

  • Utilized an in-house structure-based virtual screening platform (SpaceDock) to analyze 377 billion compounds.
  • Employed a reaction-aware ligand design approach for hit identification.
  • Synthesized and tested compounds using microscale thermophoresis (MST) and surface plasmon resonance (SPR) assays.
  • Evaluated compound efficacy in a 3D GBM spheroid model, assessing viability and STAT3 signaling.

Main Results:

  • Identified compound 9e as a potent CHI3L1 inhibitor with a Kd of 19.11 µM.
  • Compound 9e demonstrated significant dose-dependent reduction in GBM spheroid viability.
  • 9e effectively inhibited downstream STAT3 signaling in the 3D GBM model.
  • Structure-guided, reactivity-aware virtual screening proved effective for targeting complex proteins.

Conclusions:

  • Compound 9e is a promising drug candidate for targeting the CHI3L1-STAT3 axis in glioblastoma.
  • The study validates the utility of ultralarge virtual screening for discovering novel cancer therapeutics.
  • This approach holds potential for targeting non-enzymatic, dynamic proteins in complex disease models.