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Background <p>TNBC is an aggressive form of breast cancer with heterogeneous tumour differentiation, metastatic potential, and ineffective targeted therapies, making the identification of new molecular targets and treatment strategies a high priority.</p> Aim <p>This study aimed to discover potential phytobased inhibitors for selected TNBC targets by an AI-assisted integrated computational biology pipeline with chemoinformatics, molecular docking, advanced MD simulations, and free energy estimations.</p> Methods <p>Based on the functional relevance, two transcriptional cofactors, namely EYA1 and TFAP2A, were identified as potential molecular targets. The structure of TFAP2A was available in its native form; however, no 3D structure for EYA1 is available, thus computationally predicted. Hundred phytocompounds from the COCUNUT database were screened for drug likeliness and pharmacokinetic features, and Andrograpanin, a compound found in Andrographis paniculata, was identified as a potential lead.</p> Results <p>When Andrograpanin docked against the targets, the interactions with EYA1 and TFAP2A were stabilized by BE of -8.0 kcal/mol and − 6.8 kcal/mol, respectively, compared to the BE of the methodological reference, Olaparib, and its usual target, PARP1 (BE-6.1 kcal/mol). The MD simulation revealed that the binding of Andrograpanin with the targets remained stable throughout the MD trajectories, as indicated by RMSD, RMSF, Rg, SASA, and HB analysis. The PCA, FEL, and DCCM analyses revealed that Andrograpanin stabilizes EYA1 and enhances dynamic allosteric signaling with TFAP2A, demonstrating the strongest binding affinity. The binding free energy estimation by MMBGSA and MMPBSA demonstrated that Andrograpanin binds better to TFAP2A (ΔGbind − 119.79 kcal/mol) and EYA1 (ΔGbind -50.46 ± 12.64 kcal/mol) than Olaparib to PARP1 (ΔGbind − 37.86 kcal/mol).</p> Conclusion <p>The present in silico hypothesis driven study suggested that Andrograpanin is a potent EYA1 and TFAP2A multitarget inhibitor, and this theoretical model offers substantial insights for future experimentation and discovery of multitarget natural inhibitors for TNBC.</p>

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Integrative AI and Molecular Simulation Reveal Andrograpanin as a Potent Dual Inhibitor of EYA1 and TFAP2A in Triple-Negative Breast Cancer

  • 期刊论文

  • 发表日期：

    2026年5月11日

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  • Sinosh Skariyachan,
  • Aryalakshmi Gangadharan Sreenilayam Nair,
  • Denoj Sebastian,
  • Sreejith K

摘要

Background

TNBC is an aggressive form of breast cancer with heterogeneous tumour differentiation, metastatic potential, and ineffective targeted therapies, making the identification of new molecular targets and treatment strategies a high priority.

Aim

This study aimed to discover potential phytobased inhibitors for selected TNBC targets by an AI-assisted integrated computational biology pipeline with chemoinformatics, molecular docking, advanced MD simulations, and free energy estimations.

Methods

Based on the functional relevance, two transcriptional cofactors, namely EYA1 and TFAP2A, were identified as potential molecular targets. The structure of TFAP2A was available in its native form; however, no 3D structure for EYA1 is available, thus computationally predicted. Hundred phytocompounds from the COCUNUT database were screened for drug likeliness and pharmacokinetic features, and Andrograpanin, a compound found in Andrographis paniculata, was identified as a potential lead.

Results

When Andrograpanin docked against the targets, the interactions with EYA1 and TFAP2A were stabilized by BE of -8.0 kcal/mol and − 6.8 kcal/mol, respectively, compared to the BE of the methodological reference, Olaparib, and its usual target, PARP1 (BE-6.1 kcal/mol). The MD simulation revealed that the binding of Andrograpanin with the targets remained stable throughout the MD trajectories, as indicated by RMSD, RMSF, Rg, SASA, and HB analysis. The PCA, FEL, and DCCM analyses revealed that Andrograpanin stabilizes EYA1 and enhances dynamic allosteric signaling with TFAP2A, demonstrating the strongest binding affinity. The binding free energy estimation by MMBGSA and MMPBSA demonstrated that Andrograpanin binds better to TFAP2A (ΔGbind − 119.79 kcal/mol) and EYA1 (ΔGbind -50.46 ± 12.64 kcal/mol) than Olaparib to PARP1 (ΔGbind − 37.86 kcal/mol).

Conclusion

The present in silico hypothesis driven study suggested that Andrograpanin is a potent EYA1 and TFAP2A multitarget inhibitor, and this theoretical model offers substantial insights for future experimentation and discovery of multitarget natural inhibitors for TNBC.