Code and data from: Multiscale analysis and optimal glioma therapeutic candidate discovery using the CANDO platform

This dataset accompanies our study and contains the computed resources used with the Computational Analysis of Novel Drug Opportunities (CANDO) platform for multiscale therapeutic discovery to predict new glioma therapies. It includes the compound–protein interaction scores used to generate proteome-scale interaction signatures; ranked similarity and consensus lists (generated by the accompanying scripts) that model compound behavior across targets; and all benchmarking outputs measuring recovery of approved drugs at multiple cutoffs with several metrics and random-control comparisons across all indications.

Compounds ranked highly by consensus but not previously associated with glioma are provided as new predictions together with literature corroboration tags, yielding 23 potential treatments (e.g., vitamin D, taxanes, vinca alkaloids, topoisomerase inhibitors, folic acid; investigational compounds include ginsenosides, chrysin, resiniferatoxin, cryptotanshinone). We also provide top-target tables and functional-annotation summaries highlighting proteins with the strongest predicted interactions to these compounds, including vitamin D3 receptor, thyroid hormone receptor, acetylcholinesterase, cyclin-dependent kinase 2, tubulin alpha chain, dihydrofolate reductase, and thymidylate synthase.