What question did this study set out to answer?

The aim is to identify dual inhibitors targeting TOP1 and TOP2A to address resistance in triple-negative breast cancer.

April 24, 2026Open Access

Pharmacophore based discovery of dual inhibitors targeting TOP1 and TOP2A in resistant triple negative breast cancer

EOEnayi OnajiAhmadu Bello University GAGrace AdajiAhmadu Bello University CAChukwunenye Christopher AzubuikeUniversity of Benin

Key Points

The aim is to identify dual inhibitors targeting TOP1 and TOP2A to address resistance in triple-negative breast cancer.
Developed a structure-based pharmacophore model for inhibitor discovery.
Conducted virtual screening of compounds and molecular docking to assess binding affinities.
Performed ADMET profiling and molecular dynamics simulations to evaluate drug-like properties.
Identified 475 potential inhibitors, narrowing down to 15 with superior binding affinities.
Selected two candidate compounds with favorable drug-like properties and low toxicity predictions.
Confirmed potent inhibitory activity and complex stability through QSAR and molecular dynamics.

Abstract

Triple-negative breast cancer (TNBC) is an aggressive malignancy characterized by the absence of conventional hormonal receptors, leading to intrinsic resistance to standard therapies and poor clinical outcomes. Topoisomerase I (TOP1) and Topoisomerase II alpha (TOP2A), essential enzymes for DNA replication and transcription, have emerged as promising co-targets to overcome this therapeutic resistance. This study employed an integrated in-silico pipeline to discover novel dual-targeting inhibitors against both TOP1 and TOP2A. A structure-based pharmacophore model (AAHRR₇) was developed and rigorously validated, demonstrating high predictive power. Subsequent virtual screening of a ZINC in-trial compound library identified 475 hits, which were advanced to molecular docking against the crystal structures of TOP1 (PDB: 1T8I) and TOP2A (PDB: 4FM9). This process yielded 15 top-ranked compounds with significantly superior predicted binding affinities compared to reference inhibitors. MM/GBSA refinement and systematic ADMET profiling further prioritized two in-silico candidate molecules ZINC13740825 and ZINC00586527 which exhibited robust binding free energies and favorable drug-like properties with low predicted toxicity. Quantitative structure-activity relationship (QSAR) models and Molecular Dynamics Simulation studies confirmed their potent predicted inhibitory activity and complex stability against both targets. These findings highlight the potential of these identified compounds as promising dual TOP1/TOP2A inhibitors for TNBC therapy, offering a strategic avenue to combat resistance mechanisms. Further experimental validation is warranted to translate these computational insights into therapeutic candidates.

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