ArticlePloS one2025
Structural stability-guided scaffold hopping and computational modeling of tankyrase inhibitors targeting colorectal cancer.
Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Computational Phenotypic Drug Discovery for Anticancer Chemotherapy: PTML Modeling of Multi-Cell Inhibitors of Colorectal Cancer Cell Lines.International journal of molecular sciences · 2025Article
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Abstract
Colorectal cancer is one of the leading causes of cancer-related deaths worldwide, mainly due to aberrant Wnt/β-catenin signaling resulting from APC mutations. Tankyrase is a key regulator of this pathway and plays a crucial role in stabilizing AXIN, a negative regulator of β-catenin, and hence an attractive therapeutic target. The present study describes a comprehensive computational approach to discovering novel tankyrase inhibitors for CRC therapy. The reference (RK-582) for ligand-based screening and comparative analysis was taken from the crystal structure of tankyrase. A similarity search in the PubChem, applying an 80% cutoff, yielded 533 structurally similar compounds. These compounds were subjected to virtual screening using a drug-likeness filter. The top-ranking binding poses of three selected compounds (PubChem CIDs: 138594346, 138594730, and 138594428) were selected for DFT calculation and re-docking. DFT calculations revealed that compound 138594428 had the largest HOMO-LUMO gap (4.979 eV), indicating high electronic stability, while 138594346 exhibited a strong balance of stability and reactivity (4.473 eV). The MD simulations were conducted on all ns protein-ligand complexes for 500 ns, exploring their stability. MD simulations confirmed the conformational stability of these compounds, with 138594346 showing the lowest RMSD and RMSF fluctuations. Additionally, a machine learning model trained on 236 known Tankyrase inhibitors accurately predicted pIC₅₀ values, with compound 138594346 (pIC₅₀ = 7.70) closely matching the reference inhibitor (pIC₅₀ = 7.71), and 138594428 also exhibiting strong predicted activity (pIC₅₀ = 7.41). Collectively, these results highlight 138594346 and 138594428 as promising candidates for further experimental validation in the development of targeted CRC therapeutics.
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