Computational screening identifies terniflorin and bismahanine as natural inhibitors of Bcl-xL, suggesting novel scaffolds for overcoming therapeutic resistance in breast cancer.
Breast cancer remains a leading cause of cancer-related mortality worldwide, with dysregulation of apoptosis contributing to tumour progression and therapeutic resistance. The anti-apoptotic protein Bcl-xL is a key regulator of apoptotic evasion and an attractive therapeutic target; however, currently available Bcl-xL inhibitors are associated with dose-limiting toxicities, highlighting the need for alternative molecular scaffolds. In this study, an integrated computational workflow was employed to prioritize potential natural Bcl-xL inhibitors from a curated library of 3,987 natural compounds from the COCONUT, IMPPAT, and FooDB databases. Molecular docking, molecular dynamics simulations, MM-GBSA binding free energy calculations, principal component analysis, dynamical cross-correlation matrix analysis, free energy landscape analysis, density functional theory, and toxicity prediction were performed using ABT-737 as the reference inhibitor. Ten compounds exhibited docking scores comparable to or better than ABT-737 and were subsequently subjected to 200 ns MD simulations. Comparative analyses prioritized Bismahanine and Terniflorin based on their stable binding behaviour within the Bcl-xL BH3-binding groove, persistent interaction networks, and favourable estimated MM-GBSA binding free energies. Terniflorin additionally exhibited a predicted acute toxicity profile comparable to that of ABT-737, whereas Bismahanine showed comparatively higher predicted acute toxicity. Collectively, these computational findings prioritize Bismahanine and Terniflorin as promising natural leads for further investigation as potential Bcl-xL inhibitors and provide a rational basis for experimental validation and lead optimization.
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Gopakumar et al. (2026) studied this question.
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