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Pan-Cancer Multi-Omics and Structure-Guided Drug Discovery Identify TUBG1 as a Clinically and Immunologically Relevant Target

Jul 2026 · Journal of Computational Biophysics and Chemistry · 0 citations

TL;DR

This pan-cancer study supports TUBG1 as a clinically and immunogenomically relevant candidate and nominates computationally prioritized inhibitors for experimental validation.

Abstract

TUBG1 (γ-tubulin 1) is a centrosome-associated tubulin essential for microtubule nucleation and mitotic spindle organization. Despite the role of cytoskeletal dysregulation in cancer, the pan-cancer clinical, immunogenomic, and druggability landscape of TUBG1 remains poorly defined. We characterized TUBG1 as a pan-cancer oncogenic candidate, assessed its prognostic and immune relevance, and identified novel small-molecule inhibitors through integrated in silico design and molecular modeling. Using public multi-omics resources, we evaluated TUBG1 expression across tumor types, disease states, and protein abundance using CPTAC data. Associations with grade, stage, and survival were assessed using correlation analyses and Kaplan-Meier plots. Genomic alterations, promoter methylation, and immune context (via purity-adjusted deconvolution, TMB, and MSI) were profiled. Pharmacogenomic correlations and single-cell analyses were performed. De novo ligand generation, docking, molecular dynamics, binding free-energy estimation, ADMET screening, and DFT prioritized candidate inhibitors. TUBG1 was significantly dysregulated across multiple tumors, with increased protein abundance in glioblastoma, hepatocellular carcinoma, and head and neck squamous cell carcinoma. Expression correlated with tumor grade, pathological stage, and poorer survival. Tumor-specific alteration and methylation patterns were observed. TUBG1 correlated with immune features and TMB/MSI in selected cancers. Two de novo compounds showed strong docking scores, stable dynamics, and favorable binding energies. This pan-cancer study supports TUBG1 as a clinically and immunogenomically relevant candidate and nominates computationally prioritized inhibitors for experimental validation.

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