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<p>Polo-like kinase 1 (PLK1) is a serine/threonine kinase critically involved in mitotic progression and is frequently overexpressed in breast cancer, making it an attractive therapeutic target. An integrated in silico approach combining molecular docking, activity prediction, molecular dynamics (MD) simulation, and Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) calculations was employed to identify potential PLK1 inhibitors. An initial library of 59 drug-like phytochemicals from <i>Clausena anisata</i> was screened against the kinase domain of PLK1, yielding 13 hits (docking ΔG ≤ − 8.6&#xa0;kcal/mol), all of which interacted with key hinge and pocket residues, including Cys133, Leu59, and Phe183. All hits were predicted to exhibit apoptotic and antineoplastic properties with a probability of active (Pa) value &gt; 0.3 and sub-micromolar to low-nanomolar IC₅₀ values. MD simulation revealed that the top 6 lead compounds exhibited the most favorable dynamic stability and compactness. MM-PBSA binding free energies ranked CID 5315947 (–96.1 ± 16&#xa0;kJ/mol), CID 10448976 (–95.8 ± 9.5&#xa0;kJ/mol), and CID 6439823 (–94.9 ± 14.2&#xa0;kJ/mol) as the strongest binders, driven predominantly by van der Waals interactions. Per-residue energy decomposition revealed that Glu69 is a novel critical modulator of selectivity and kinase inactivation. Collectively, our multi-tiered computational approach identifies promising natural scaffolds for PLK1 inhibition and provides a robust framework for lead optimization in breast cancer therapy.</p> Graphical Abstract <p></p>

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Structure-Guided Discovery of Potent Polo-Like Kinase 1 Inhibitors for Breast Cancer Therapy

  • 期刊论文

  • 发表日期：

    2026年1月24日

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  • Michael Afiadenyo,
  • Sherif Hamidu,
  • Dorcas Obiri-Yeboah,
  • Seth Kwabena Amponsah,
  • Kwabena Dankwah,
  • Latif Adams

摘要

Polo-like kinase 1 (PLK1) is a serine/threonine kinase critically involved in mitotic progression and is frequently overexpressed in breast cancer, making it an attractive therapeutic target. An integrated in silico approach combining molecular docking, activity prediction, molecular dynamics (MD) simulation, and Molecular Mechanics/Poisson Boltzmann Surface Area (MM/PBSA) calculations was employed to identify potential PLK1 inhibitors. An initial library of 59 drug-like phytochemicals from Clausena anisata was screened against the kinase domain of PLK1, yielding 13 hits (docking ΔG ≤ − 8.6 kcal/mol), all of which interacted with key hinge and pocket residues, including Cys133, Leu59, and Phe183. All hits were predicted to exhibit apoptotic and antineoplastic properties with a probability of active (Pa) value > 0.3 and sub-micromolar to low-nanomolar IC₅₀ values. MD simulation revealed that the top 6 lead compounds exhibited the most favorable dynamic stability and compactness. MM-PBSA binding free energies ranked CID 5315947 (–96.1 ± 16 kJ/mol), CID 10448976 (–95.8 ± 9.5 kJ/mol), and CID 6439823 (–94.9 ± 14.2 kJ/mol) as the strongest binders, driven predominantly by van der Waals interactions. Per-residue energy decomposition revealed that Glu69 is a novel critical modulator of selectivity and kinase inactivation. Collectively, our multi-tiered computational approach identifies promising natural scaffolds for PLK1 inhibition and provides a robust framework for lead optimization in breast cancer therapy.

Graphical Abstract