Comprehensive Modeling and Discovery of Mebendazole as a Novel TRAF2- and NCK-interacting Kinase Inhibitor

Area of Science:

• Medicinal Chemistry
• Computational Drug Discovery
• Oncology

Background:

• TRAF2- and NCK-interacting kinase (TNIK) is a key target in Wnt-activated colorectal cancer.
• Developing novel TNIK inhibitors with favorable biopharmaceutical properties is crucial for effective cancer therapy.

Purpose of the Study:

• To explore novel TNIK inhibitors using comprehensive computational modeling.
• To identify existing drugs with potential TNIK inhibitory activity.

Main Methods:

• Curated two datasets for quantitative structure-activity relationship (QSAR) modeling.
• Developed Comparative Molecular Similarity Indices Analysis (CoMSIA) and k-nearest neighbor (kNN) models.
• Screened 1,448 FDA-approved drugs using predictive CoMSIA-SIMCA models.

Main Results:

• Identified critical 3D-molecular fields and 2D-descriptors for TNIK inhibition.
• Mebendazole, an anthelmintic drug, demonstrated selective TNIK kinase inhibition (Kd ≈ 1 μM).
• Computational analyses confirmed mebendazole possesses favorable features for TNIK binding and inhibition.

Conclusions:

• Mebendazole is a promising candidate for TNIK-targeted colorectal cancer therapy.
• Computational modeling effectively identified repurposed drugs with potential therapeutic applications.
• The study provides insights into the structural requirements for potent TNIK inhibitors.