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<p>Telomerase is a pivotal target for oncological therapeutics. This study leverages cutting-edge computational methodologies to design and optimise tacrine analogues as telomerase inhibitors. Using the Schrödinger suite, we employed the PHASE module for 3D-QSAR modeling, Glide for molecular docking, and DESMOND for molecular dynamics (MD) simulations. Two series of dog-bone-shaped derivatives, namely <i>N</i>-benzoyl-<i>N</i>-(1,2,3,4-tetrahydroacridin-9-yl)benzamides and <i>N</i>-(1,2,3,4-tetrahydroacridin-9-yl)benzamides, were rationally designed to improve binding affinity and target specificity. Molecular docking studies revealed binding energies of − 10.45 and − 9.86&#xa0;kcal/mol for the lead compounds HB_01 and HB_02, surpassing the performance of standard inhibitors BIBR1532 and BRACO-19. MD simulations validated the stability of protein–ligand complexes, with root mean square deviation values consistently below 3 Å. Binding free energy analyses (MM/GBSA) highlighted thermodynamic favorability, with ΔG_bind values of − 71.189&#xa0;kcal/mol for HB_01 and − 71.7&#xa0;kcal/mol for HB_02. Principal component analysis and free energy landscape (FEL) analyses further corroborated the dynamic stability and conformational compactness of the complexes, showcasing the synergistic application of these computational techniques. By providing a comprehensive workflow from 3D-QSAR to FEL analysis, this work establishes a scalable framework for telomerase inhibitor development. Future studies will expand on these insights through experimental validation, leveraging computational precision for advanced anticancer therapeutics.</p>

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Mechanistic exploration of dog bone-shaped tacrine analogues as telomerase inhibitors via 3D-QSAR, MD simulations, and energy landscape analysis

  • 期刊论文

  • 发表日期：

    2026年1月10日

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  • Rajdeep Dey,
  • Nandan Dixit,
  • Saumya Patel,
  • Hardik Bhatt

摘要

Telomerase is a pivotal target for oncological therapeutics. This study leverages cutting-edge computational methodologies to design and optimise tacrine analogues as telomerase inhibitors. Using the Schrödinger suite, we employed the PHASE module for 3D-QSAR modeling, Glide for molecular docking, and DESMOND for molecular dynamics (MD) simulations. Two series of dog-bone-shaped derivatives, namely N-benzoyl-N-(1,2,3,4-tetrahydroacridin-9-yl)benzamides and N-(1,2,3,4-tetrahydroacridin-9-yl)benzamides, were rationally designed to improve binding affinity and target specificity. Molecular docking studies revealed binding energies of − 10.45 and − 9.86 kcal/mol for the lead compounds HB_01 and HB_02, surpassing the performance of standard inhibitors BIBR1532 and BRACO-19. MD simulations validated the stability of protein–ligand complexes, with root mean square deviation values consistently below 3 Å. Binding free energy analyses (MM/GBSA) highlighted thermodynamic favorability, with ΔG_bind values of − 71.189 kcal/mol for HB_01 and − 71.7 kcal/mol for HB_02. Principal component analysis and free energy landscape (FEL) analyses further corroborated the dynamic stability and conformational compactness of the complexes, showcasing the synergistic application of these computational techniques. By providing a comprehensive workflow from 3D-QSAR to FEL analysis, this work establishes a scalable framework for telomerase inhibitor development. Future studies will expand on these insights through experimental validation, leveraging computational precision for advanced anticancer therapeutics.