Establishing PDK1-based prognostic biomarkers and identifying targeted inhibitors for glioma prognosis and therapy

Glioma patients face a poor prognosis with limited therapeutic benefits from conventional treatments. PDK1, has emerged as a critical molecular target for glioma-specific therapy. We investigated PDK1’s role in glioma progression, developed a prognostic model (PDK1_PS) for survival prediction, and identified Taxiresinol as a novel PDK1 inhibitor with potent anti-tumor activity, while Glycerol tribenzoate was identified as a potential binder requiring further structural optimization. RNA-seq and clinical data of 160 glioblastoma samples were obtained from TCGA and stratified by PDK1 expression. Immune-related signatures were quantified by ssGSEA, and downstream differentially expressed genes were identified for functional enrichment. A PDK1-associated prognostic signature (PDK1_PS) was constructed using LASSO Cox regression and validated in the CGGA cohort. Structure-based virtual screening was performed against the ATP-binding pocket of PDK1, followed by ADME/TOPKAT evaluation, molecular docking, pharmacophore characterization, and 100 ns molecular dynamics simulations using Discovery Studio 2019 and Gromacs. Candidate compounds were assessed in vitro experiments. PDK1 stratification was associated with distinct immune programs and transcriptional patterns. A five-gene PDK1_PS showed prognostic value in the training cohort and maintained performance in CGGA validation. Virtual screening nominated Taxiresinol (ZINC000034189841) and glycerol tribenzoate (ZINC000001577210) as promising binders, supported by docking and dynamic stability analyses. In vitro, Taxiresinol showed a clear dose-dependent anti-proliferative effect in U87 cells, whereas glycerol tribenzoate showed limited cytotoxicity within the tested range and warrants further evaluation. This study establishes a PDK1-related prognostic signature and identifies Taxiresinol and glycerol tribenzoate as candidate PDK1-targeting compounds supported by in silico binding analyses. Further mechanistic validation (e.g., kinase activity and downstream phosphorylation) is needed to confirm on-target effects and advance translational potential.