Identification of the therapeutic potential of novel TIGIT/PVR interaction blockers based advanced computational

Xudong Lü1, Xiyu Wei1, Chenyu Wang2

  • 1Institute of Medicinal Biotechnology, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100050, China.

Biophysical Chemistry
|December 27, 2024
PubMed

Insights

Researchers identified a novel small molecule, MCULE-5547257859, that effectively blocks the TIGIT/PVR interaction. This compound enhances immune cell activity, offering a promising new avenue for cancer therapy.

Area of Science:

  • Immunology
  • Computational Chemistry
  • Pharmacology

Background:

  • The TIGIT/PVR pathway plays a crucial role in immune regulation and cancer progression.
  • Inhibiting TIGIT/PVR interaction enhances cytotoxic activity of natural killer (NK) and CD8+ T cells, showing anticancer potential.
  • Development of small molecule inhibitors targeting TIGIT remains a challenge.

Purpose of the Study:

  • To identify novel small molecules capable of inhibiting the TIGIT/PVR interaction.
  • To evaluate the therapeutic potential of identified compounds in cancer treatment.

Main Methods:

  • Utilized a computational screening process combining XGBOOST machine learning and molecular docking to identify potential TIGIT inhibitors.
  • Validated candidate molecules through in vitro blocking assays.
  • Performed molecular dynamics simulations and binding free energy analyses to assess binding affinity and stability.

Main Results:

  • A computational approach efficiently reduced the chemical space for inhibitor screening.
  • Compound MCULE-5547257859 demonstrated the most potent inhibition of the TIGIT/PVR interaction in blocking assays.
  • Molecular dynamics simulations confirmed a thermodynamically stable conformation and strong binding affinity of MCULE-5547257859 to TIGIT.

Conclusions:

  • Compound MCULE-5547257859 effectively inhibits the TIGIT/PVR interaction.
  • This compound represents a promising novel therapeutic candidate for oncological applications.
  • The study highlights the potential of computational methods in accelerating drug discovery for cancer immunotherapy.