ArticleScientific data2025
HCDT 2.0: A Highly Confident Drug-Target Database for Experimentally Validated Genes, RNAs, and Pathways.
Article in Scientific data, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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14 authors.
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Abstract
Drug-target interactions constitute the fundamental basis for understanding drug action mechanisms and advancing therapeutic discovery. While existing drug-target databases have contributed valuable resources, they exhibit structural and functional fragmentation due to heterogeneous data sources and annotation standards. Building upon the high-confidence drug-gene interactions curated in HCDT 1.0, we present HCDT 2.0, a comprehensive and standardized resource that expands the scope through multiomics data integration. This update incorporates three-dimensional interactions including drug-gene, drug-RNA and drug-pathway interactions. The current version contains 1,284,353 curated interactions: 1,224,774 drug-gene pairs (678,564 drugs × 5,692 genes), 11,770 drug-RNA mappings (316 drugs × 6,430 RNAs), and 47,809 drug-pathway links (6,290 drugs × 3,143 pathways), alongside 16,317 drug-disease associations. To enhance biological interpretability, we further integrated pathway-gene and RNA-gene regulatory relationships. In addition, we integrated 38,653 negative DTIs covering 26,989 drugs and 1,575 genes. This integrative framework not only addresses critical gaps in cross-scale data representation but also establishes a robust foundation for systems pharmacology applications, including drug repurposing, adverse event prediction, and precision oncology strategies.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.