AI-driven identification of a selective dual function inhibitor blocking HK2 activity and HK2-VDAC1 interaction displaying enhanced anticancer efficacy under hypoxia.

Selective inhibition of hexokinase 2 (HK2) represents a promising therapeutic strategy due to the pivotal role of HK2 in the Warburg effect, enhancement of glycolysis and anti-apoptosis via HK2-Voltage-Dependent Anion Channel 1 (VDAC1) protein-protein interaction. Moreover, HK2 initiates glycolysis to generate lactate, hence this central enzyme can be pharmacologically targeted to enhance therapy outcomes. Currently, no HK2 inhibitors (HK2is) exist in the clinic. Herein, we employed GCVec, an artificial intelligence (AI)-based compound-protein interaction (CPI) prediction tool, along with molecular docking, to identify the HK2i, 106. This compound exhibited an IC of 0.79 ± 0.07 μM and a consistent K of 0.41 ± 0.03 μM against HK2 enzyme. It also apparently blocked HK2-VDAC1 interaction as indicated by the disrupted colocalization of HK2-GFP and VDAC1-mCherry. Furthermore, 106 demonstrated enhanced anticancer efficacy under hypoxia in tumor cells with elevated HIF-1α/HK2 and VDAC1 levels. Compound 106 selectively targeted SW480 colorectal cancer cells with high HK2 expression, achieving a growth inhibition IC value of 5.00 ± 0.94 μM. Consistently, knockout of HK2 in these tumor cells significantly rescued the IC values and eliminated the glycolytic inhibition induced by 106. We further showed that 106 reduced lactate and ATP levels and induced markers of apoptosis, including increased p-AMPK/AMPK ratio and increased Bax levels, as well as decreased Bcl2 levels. Collectively, our findings highlight the potential of GCVec in identifying 106, a first in class dual-function HK2i which emerges as a promising lead compound for further development into a possible anticancer therapeutic agent.