Structure-guided discovery of submicromolar 1,2,4-triazole-Schiff-base inhibitors of glutathione reductase

Abstract

Glutathione reductase (GR) plays a crucial role in maintaining cellular redox balance and is a promising target for ferroptosis-based cancer therapies. In this study, we report the design, synthesis, and comprehensive evaluation of a novel series of 1,2,4-triazole-Schiff base succinate derivatives (AUR-514-518) as potent GR inhibitors. In vitro Mannervik assays revealed vigorous submicromolar inhibitory activity, with AUR-517 emerging as the most effective (IC50 = 0.471 +/- 0.032 mu M), significantly surpassing quercetin (IC50 = 214.5 +/- 18.5 mu M). Antioxidant profiling revealed negligible radical scavenging activity; however, modest CUPRAC responses suggest a target-specific mechanism. To elucidate the molecular determinants of inhibition, we employed deeplearning-assisted protein-ligand affinity predictions, molecular dynamics simulations, MM/GBSA free-energy calculations, and dimensional reduction analyses. These computational studies revealed dual binding modes at both the catalytic site and dimer interface, with AUR-517 forming stable interactions with key catalytic residues, consistent with experimental potency rankings. The RMSD/RMSF profiles indicated enhanced conformational stability of GR-ligand complexes, while binding energy landscapes underscored the superior stability of AUR517. Consequently, these findings establish the AUR series as a new class of structurally validated GR inhibitors, with AUR-517 representing a lead scaffold for the rational development of ferroptosis-sensitizing agents with translational potential in oncology.Aurealcraft Therapeutics; Scientific Research Project Fund of Kafkas University [2018-FM-46]; TUBITAK ULAKBIM's High Performance and Grid Computing CenterAurealcraft Therapeutics supports this research under the project AUREXIS (ARF-500), which focuses on ferroptosis-potent research. Aurealcraft Therapeutics and collaborating academic partners provided high-performance computing and scientific infrastructure. In addition, this research is supported by the Scientific Research Project Fund of Kafkas University under project number 2018-FM-46. It was also supported by TUBITAK ULAKBIM's High Performance and Grid Computing Center (TRUBA resources)