Artificial intelligence-based identification of octenidine as a Bcl-xL inhibitor

Abstract

Apoptosis plays an essential role in maintaining cellular homeostasis and preventing cancer progression. Bcl-xL, an anti-apoptotic protein, is an important modulator of the mitochondrial apoptosis pathway and is a promising target for anticancer therapy. In this study, we identified octenidine as a novel Bcl-xL inhibitor through structural feature-based deep learning and molecular docking from a library of approved drugs. The NMR experiments demonstrated that octenidine binds to the Bcl-2 homology 3 (BH3) domain-binding hydrophobic region that consists of the BH1, BH2, and BH3 domains in Bcl-xL. A structural model of the Bcl-xL/octenidine complex revealed that octenidine binds to Bcl-xL in a similar manner to that of the well-known Bcl-2 family protein antagonist ABT-737. Using the NanoBiT protein-protein interaction system, we confirmed that the interaction between Bcl-xL and Bak-BH3 domains within cells was inhibited by octenidine. Furthermore, octenidine inhibited the proliferation of MCF-7 breast and H1299 lung cancer cells by promoting apoptosis. Taken together, our results shed light on a novel mechanism in which octenidine directly targets anti-apoptotic Bcl-xL to trigger mitochondrial apoptosis in cancer cells.

Keywords: Anti-cancer effect; Artificial intelligence-based screening; Bcl-xL; NMR spectroscopy; Octenidine.