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This Zenodo record contains processed data files, supplementary result tables, analysis scripts, docking validation files, machine-learning validation files, and environment information associated with the manuscript: “Transcriptomics-Guided Computational Prioritization of CCR5 and NNMT Ligands in Bladder Cancer: Docking Validation, Activity Modeling, and Chemical Space Analysis”. The archive is intended to support transparency and computational reproducibility of the analyses described in the manuscript. The archived analyses include:(1) resistance signature construction from public datasets,(2) projection of resistance signatures onto TCGA-BLCA transcriptomic profiles,(3) resistance-axis scoring and quadrant assignment,(4) Hallmark ssGSEA analysis,(5) effect size-based pathway and gene prioritization,(6) target-specific compound prioritization,(7) molecular docking,(8) docking protocol validation by redocking and retrospective benchmark analyses,(9) target-specific machine-learning validation including Y-scrambling for the CCR5 random forest model,(10) Pareto-based multi-objective prioritization, and(11) chemical-space visualization. The record includes:- scripts for resistance score calculation- scripts for effect-size prioritization- scripts for docking-related prioritization workflows- scripts for docking protocol validation- scripts for machine-learning sanity checks- scripts for chemical-space visualization- processed transcriptomic and prioritization datasets- supplementary screening and validation tables- supplementary chemical-space and Y-scrambling support data- redocking, retrospective benchmark, and Y-scrambling summary files- Conda environment information- archive-level README files CCR5 prioritization in this archive is based on an internally validated target-specific machine-learning workflow combined with docking analyses supported by redocking and retrospective benchmark evaluation. For CCR5, the final adopted docking protocol used a revised search space after redocking-based box recentering. An additional Y-scrambling analysis further supported that the observed CCR5 random forest model performance was unlikely to arise from chance correlation. NNMT prioritization is retained as an exploratory target context based on archived screening scores from the original NNMT branch of the study. In the manuscript, NNMT docking is interpreted as exploratory structural support rather than as strongly validated ranking evidence. During peer review, the record metadata are publicly available, whereas the files are under restricted access. Access to the restricted files can be provided to editors and reviewers upon request or via a private review link.