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March 22, 2026Current Medicinal Chemistry0 citations

Ligand and Structure-Based Drug Design of Biphenyl 1,2,4-Triazole Derivatives as Dual Target Inhibitors of Aromatase and Steroidal Sulfatase as Anti-Breast Cancer Agents

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GVG VivekananthanVSV. Nathan SubramaniamNSNJ Sai Sruthi

Key Points

  • To analyze biphenyl 1,2,4-triazole derivatives as dual inhibitors of aromatase and steroidal sulfatase for breast cancer treatment.
  • Ligand-based screening of 172 biphenyl derivatives.
  • Utilization of 3D-QSAR modelling, ADMET analysis, molecular docking, and dynamics.
  • Statistical evaluation of models using q², r², and predictive parameters.
  • Significant binding affinities of -9.94 kcal/mol for aromatase and -9.41 kcal/mol for steroid sulfatase.
  • 3D-QSAR models showed strong prediction capabilities with high statistical parameters.
  • Compound 109 identified as the most promising dual inhibitor.

Abstract

Introduction:: Dual inhibitors of AROM and STS (DASIs), through their synergistic action, hold the potential to suppress estrogen biosynthesis at multiple points. It also overcomes limitations associated with single-enzyme inhibition and reduces the risk of resistance development. In order to potentially improve the clinical outcomes in hormone-dependent breast cancers, 1,2,4-triazole derivatives having similar structural characteristics to third-generation Aromatase Inhibitors (AIs), including exemestane, letrozole, and anastrozole, were subjected to ligand-based screening. This research study comparatively analyzes the drug candidates as DASIs that aim at the development of advanced therapeutic strategies for breast cancer treatment. Materials and Methods:: In this study, a set of 172 biphenyl 1,2,4-triazole derivatives with defined biological activity against AROM and STS enzymes was subjected to 3DQSAR modelling, followed by ADMET, molecular docking, and dynamics. results: Through 3D-QSAR significant statistical parameters of aromatase (q² = 0.8429, r² = 0.8874, r²pred = 0.8252) and steroidal sulfatase (q² = 0.8877, r² = 0.9402, r²pred = 0.9376) indicated the accuracy and reliability and its good prediction power of the model. The external validation set further claimed its capability in external predictions. Furthermore, molecular docking was found to be -9.94 for aromatase and -9.41 for STS, along with molecular dynamics at a time period of 100 ns elucidated the stability of the docked complexes. Results:: Through 3D-QSAR, significant statistical parameters of aromatase (q2 = 0.8429, r2 = 0.8874, r2pred = 0.8252) and steroidal sulfatase (q2 = 0.8877, r2 = 0.9402, r2pred = 0.9376) indicated the accuracy and reliability, and the good prediction power of the model. The external validation set further demonstrated its predictive capability. Furthermore, molecular docking, along with molecular dynamics at a time period of 100 ns, elucidated the stability of the docked complexes and found that Compound 109 emerged as the most promising dual inhibitor, exhibiting high binding affinities of -9.94 kcal/mol for Aromatase (AROM) and -9.41 kcal/mol for Steroid Sulfatase (STS). These values reflect a strong potential for dual enzyme inhibition. Discussion:: The structural features of triazole derivatives through QSAR modelling established a statistical correlation, establishing a relationship between functional groups and their biological activity. They are found to have dual inhibition efficiency in a target-based approach, accelerating for synthetic accessibility.

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Cite This Study

Vivekananthan et al. (2026) studied this question.

synapsesocial.com/papers/69bf3955c7b3c90b18b43da0https://doi.org/10.2174/0109298673445152260120111510
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