Computational and Experimental Identification of WEE1-Binding Compounds for Cancer Research
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Cancer is a significant global health challenge, highlighting the need for more effective therapies. Due to genomic instability, cancer cells typically depend on cell cycle checkpoints to survive and evade apoptosis. WEE1-like protein kinase (WEE1) is a key regulator of the cell cycle, controlling the G2/M checkpoint by inhibiting cyclin-dependent kinase 1 and preventing progression to mitosis in the presence of DNA damage. Inhibition of WEE1 can disrupt this control, forcing DNA-damaged cells into premature mitosis and leading to mitotic catastrophe and cell death. However, selective and biologically compatible WEE1 inhibitors remain limited, emphasising the need for novel candidates.
This study aimed to identify and validate WEE1-binding ligands using computer-aided drug discovery approaches. In the in silico part, potential WEE1-binding small molecule compounds were identified from commercial compound databases using similarity search, molecular docking, pose filtering, molecular dynamics simulations and visual inspection. In the in vitro part, the binding and affinity of selected ligands were evaluated using microscale thermophoresis and differential scanning fluorimetry. As a result of the in silico part, 33 ligands were identified as potential WEE1 binders and were selected for experimental testing. Of these, three potential WEE1-binding ligands were identified in the in vitro studies. These compounds may serve as reference compounds for future studies, although their binding affinity remains limited for further development. These findings emphasise the importance of computer-aided drug discovery approaches in early-stage drug development and demonstrate their applicability in WEE1 inhibitor research.