Support By : Li-lab
HCDT 2.0 is a comprehensive database that provides validated associations between drugs and targets (genes, RNAs, and pathways). In HCDT 2.0, 1,284,353 high-confidence drug-target interactions were identified, encompassing 1,224,774 interactions between 678,564 drugs and 5,692 genes, 11,770 interactions between 316 drugs and 6,430 RNAs, and 47,809 drug-pathway interactions between 6,290 drugs and 3,143 pathways.
Additionally, 16,317 drug-disease associations were included. Regarding target interactions, there were 2,639 pathway-gene interactions, and for RNA-gene interactions, two methods were employed: RNA-gene (Cis-regulatory-based method calculating distances between RNA and gene) with 11,509 interactions and RNA-target gene (target-gene-based method directly analyzing RNA and target gene relationships) with 110,294 interactions.
Furthermore, we integrated 38,653 negative DTIs from BindingDB, ChEMBL, GtoPdb, PubChem, and TTD, defined by Ki/Kd/IC50/EC50/AC50/Potency > 100 μM, covering 26,989 drugs, 1,575 target genes,which provides reliable negative samples for DTI prediction, enhancing model accuracy and reliability.
HCDT 2.0 is offered to the public as a freely available resource. Use and re-distribution of the data, in whole or in part, for commercial purposes (including internal use) requires a license.
Please contact HCDT 2.0 for feedback, suggestions, or to report errors or bugs.
Email: lijin@muhn.edu.cn
Xinying Liu, Dehua Feng, Jiaqi Chen, Tianyi Li, Xuefeng Wang, Ruijie Zhang, Jian Chen, Xingjun Cai, Huirui Han, Lei Yu, Xia Li, Bing Li, Limei Wang , Jin Li, HCDT 2.0: A Highly Confident Drug-Target Database for Experimentally Validated Genes, RNAs, and Pathways. Scientific Data, 2025. https://doi.org/10.1038/s41597-025-04981-2
Jiaqi Chen, Zhengxin Chen, Rufei Chen, Dehua Feng, Tianyi Li, Huirui Han, Xiaoman Bi, Zhenzhen Wang, Kongning Li, Yongsheng Li, Xia Li, Limei Wang, Jin Li, HCDT: an integrated highly confident drug–target resource, Database, 2022, https://doi.org/10.1093/database/baac101