PROTAC-DB 4.0: an expanded knowledgebase of targeted protein degradation modalities with AI-powered knowledge discovery
7 affiliations
- 1College of Pharmaceutical Sciences, Zhejiang University , Hangzhou 310058 Zhejiang ,
- 2CarbonSilicon AI Technology Company, Ltd. , Hangzhou 310018 Zhejiang ,
- 3Department of Medicinal Chemistry, China Pharmaceutical University , Nanjing 210009 Jiangsu ,
- 4Innovation Center for AI and Drug Discovery, School of Pharmacy, East China Normal University , Shanghai 200062 ,
- 5Vollum Institute, Oregon Health and Science University , Portland, OR 97239 ,
- 6College of Computer Science and Technology, Zhejiang University-University of Illinois Urbana-Champaign Institute, Zhejiang University , Hangzhou, Zhejiang 310027 ,
- 7State Key Laboratory of Transvascular Implantation Devices of The Second Affiliated Hospital, School of Medicine and School of Public Health, Zhejiang University , Hangzhou 310003 ,
Abstract
Proteolysis-targeting chimeras (PROTACs) represent an emerging therapeutic modality that harnesses the ubiquitin-proteasome system to induce targeted protein degradation (TPD). Their event-driven and catalytic mechanisms provide new opportunities to target previously undruggable proteins. However, the rapid expansion of TPD technologies, including molecular glues (MGs) and X-functional targeting chimeras (XTACs), together with the increasing application of artificial intelligence (AI) in degrader design, highlights the need for comprehensive and continuously updated data resources. Here, we present PROTAC-DB 4.0, an expanded knowledgebase covering major targeted degradation and induced-proximity technologies. Compared with the previous version, PROTAC-DB 4.0 contains 15 502 PROTAC entries, together with 24 798 MG entries and 272 XTAC entries, with expanded experimental annotations, patent-derived compounds, and modality-specific data fields. A major advancement in PROTAC-DB 4.0 is the integration of a large language model and retrieval-augmented generation-based natural language query system, which connects structured database records with scientific literature to enable intuitive knowledge discovery across PROTACs, MGs, and XTACs. By combining comprehensive data curation with AI-assisted information retrieval, PROTAC-DB 4.0 provides an accessible platform to support degrader discovery, data-driven modeling, and rational design of next-generation targeted degradation and induced-proximity therapeutics. PROTAC-DB 4.0 is freely accessible at http://cadd.zju.edu.cn/protacdb/.
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BibTeX
@article{ge2026protacdb,
title = {{PROTAC-DB 4.0: an expanded knowledgebase of targeted protein degradation modalities with AI-powered knowledge discovery}},
author = {Jingxuan Ge and Chen Yin and Yurong Li and Shi Li and Kexin Xu and Rongfan Tang and Gaoqi Weng and Hao Luo and Lin Tang and Youqiao Qian and Shukai Gu and Chang-Yu Hsieh and Jian Wu and Dan Li and Huiyong Sun and Tingjun Hou},
journal = {Nucleic Acids Research},
year = {2026},
month = oct,
doi = {10.1093/nar/gkag1098},
url = {https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1098/9005752},
note = {CC BY-NC 4.0},
}
RIS
TY - JOUR
TI - PROTAC-DB 4.0: an expanded knowledgebase of targeted protein degradation modalities with AI-powered knowledge discovery
AU - Jingxuan Ge
AU - Chen Yin
AU - Yurong Li
AU - Shi Li
AU - Kexin Xu
AU - Rongfan Tang
AU - Gaoqi Weng
AU - Hao Luo
AU - Lin Tang
AU - Youqiao Qian
AU - Shukai Gu
AU - Chang-Yu Hsieh
AU - Jian Wu
AU - Dan Li
AU - Huiyong Sun
AU - Tingjun Hou
PY - 2026
DA - 2026/10/31
JO - Nucleic Acids Research
DO - 10.1093/nar/gkag1098
UR - https://academic.oup.com/nar/advance-article/doi/10.1093/nar/gkag1098/9005752
AB - Proteolysis-targeting chimeras (PROTACs) represent an emerging therapeutic modality that harnesses the ubiquitin-proteasome system to induce targeted protein degradation (TPD). Their event-driven and catalytic mechanisms provide new opportunities to target previously undruggable proteins. However, the rapid expansion of TPD technologies, including molecular glues (MGs) and X-functional targeting chimeras (XTACs), together with the increasing application of artificial intelligence (AI) in degrader design, highlights the need for comprehensive and continuously updated data resources. Here, we present PROTAC-DB 4.0, an expanded knowledgebase covering major targeted degradation and induced-proximity technologies. Compared with the previous version, PROTAC-DB 4.0 contains 15 502 PROTAC entries, together with 24 798 MG entries and 272 XTAC entries, with expanded experimental annotations, patent-derived compounds, and modality-specific data fields. A major advancement in PROTAC-DB 4.0 is the integration of a large language model and retrieval-augmented generation-based natural language query system, which connects structured database records with scientific literature to enable intuitive knowledge discovery across PROTACs, MGs, and XTACs. By combining comprehensive data curation with AI-assisted information retrieval, PROTAC-DB 4.0 provides an accessible platform to support degrader discovery, data-driven modeling, and rational design of next-generation targeted degradation and induced-proximity therapeutics. PROTAC-DB 4.0 is freely accessible at http://cadd.zju.edu.cn/protacdb/.
SN - 0305-1048
SN - 1362-4962
ER -