Combinatorial Virtual Screening Revealed a Novel Scaffold for TNKS Inhibition to Combat Colorectal Cancer

Abstract

The abnormal Wnt signaling pathway leads to a high expression of β-catenin, which causes several types of cancer, particularly colorectal cancer (CRC). The inhibition of tankyrase (TNKS) activity can reduce cancer cell growth, invasion, and resistance to treatment by blocking the Wnt signaling pathway. A pharmacophore search and pharmacophore docking were performed to identify potential TNKS inhibitors in the training databases. The weighted MM/PBSA binding free energy of the docking model was calculated to rank the databases. The reranked results indicated that 26.98% of TNKS inhibitors that were present in the top 5% of compounds in the database and near an ideal value ranked 28.57%. The National Cancer Institute database was selected for formal virtual screening, and 11 potential TNKS inhibitors were identified. An enzyme-based experiment was performed to demonstrate that of the 11 potential TNKS inhibitors, NSC295092 and NSC319963 had the most potential. Finally, Wnt pathway analysis was performed through a cell-based assay, which indicated that NSC319963 is the most likely TNKS inhibitor (pIC₅₀ = 5.59). The antiproliferation assay demonstrated that NSC319963 can decrease colorectal cancer cell growth; therefore, the proposed method successfully identified a novel TNKS inhibitor that can alleviate CRC.

Keywords: TNKS inhibitor; Wnt signaling pathway; docking; pharmacophore; virtual screening; β-catenin.

Figure 1

The critical residues of ligand binding sites on TNKS-1 and TNKS-2. (a) The seven critical residues determined of TNKS-1 and TNKS-2 are His1184, His1031, Gly1185, Gly1032, Tyr1213, Tyr1060, Ala1215, Ala1062, Lys1220, Lys1067, Ser1221, Ser1068, Tyr1224, Tyr1071, respectively. (b) Co-crystal ligand of TNKS-1 (4U6A) interact with the seven critical residues.

Figure 2

The defined pharmacophore model of TNKS protein. (a) 10 crystal structures and co-crystal ligands were superposed. (b) The purple is F1 donor, the cyan is F2 acceptor, the orange is F3 aromatic, and the two greens are F4 and F5 aromatic or hydrophobic. The F2 and F3 are defined as essential ligand features.

Figure 3

The validation of different methods for virtual screening. The black line is random module. The purple line is ideal module. The red line is pharmacophore docking module. The green line is the module of binding energy calculation from pharmacophore docked structure. The blue line is the module of weighted binding energy calculation from pharmacophore docked structure.

Figure 4

The relationships between the experimental pIC₅₀ of TNKS-1 inhibitors and binding free energy (kJ/mol) calculations (a) column A from single-point minimization; column B from NPT-based simulation; column C from MD-based simulation; column D from weighted binding energy calculation. (b,c) The relationship of all experimental pIC₅₀ of TNKS-1 inhibitors and binding free energy. (b) from single-point minimization (c) from weighted binding energy calculation.

Figure 5

The workflow of proposed combinatorial virtual screening in this study. From NCI database, 6,299,757 conformations were generated. A total 11,932 compounds were hit after pharmacophore search and 3198 compounds were hit by the followed pharmacophore docking. These compounds were rescored by the weighted binding free energy calculation and top 15 compounds were selected for further validation by using enzyme and cell-based assays. The blue arrow just meant the progress direction of the workflow (from top to down).

Figure 6

The similarity of screened compounds NSC319963 and NSC295092. (a) The structure similarity of NSC319963, NSC295092 and know TNKSs inhibitors. (b) The most similar compounds and their structures.

Figure 7

The docking modes of NSC319963 and NSC295092. (a) Docking model of NSC295092 and 2D interaction map. (b) Docking model of NSC319963 and 2D interaction map.

Figure 8

Inhibition of cell growth in APC colorectal cancer cells. (a) DLD-1 (b) HCT-116 and (c) SW403 cells were incubated with various concentrations of NSC319963 for 10 to 12 days. Colony formation was assessed to detect the effect of NSC319963 on cell growth. Colony formation was counted and presented as bar graphs. Each column represents the mean ± SD with triplicate experiments. * p < 0.05, compared to DMSO group.

Figure 9

NSC319963 enhances the chemosensitivity of 5-FU in DLD-1 cells. DLD-1 cells were treated with different concentrations of NSC319963 and 5-FU for 12 days. Colony formation was counted and presented as bar graphs. Each column represents the mean ± SD with triplicate experiments.