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PROTAC-PatentDB: A PROTAC Patent Compound Dataset.

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  • 1State Key Laboratory of Mechanism and Quality of Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macao SAR, China.

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|November 19, 2025
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Summary

This study compiles a large dataset of Proteolysis-targeting chimeras (PROTAC) compounds from patents, addressing a key data gap for computational drug discovery. The curated data and webserver accelerate AI-aided design of novel protein degradation therapeutics.

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Area of Science:

  • Medicinal Chemistry
  • Computational Drug Discovery
  • Biotechnology

Background:

  • Proteolysis-targeting chimeras (PROTAC) offer a novel therapeutic modality for targeted protein degradation, potentially overcoming limitations of traditional small molecules.
  • A significant barrier to advancing PROTAC research, particularly in computational and AI-aided drug discovery, is the limited availability of public molecular structure data.
  • Patents represent a rich, yet underexplored, repository of novel chemical entities relevant to medicinal chemistry.

Purpose of the Study:

  • To curate and provide a comprehensive dataset of PROTAC compounds and their associated targets from patent literature.
  • To facilitate computational drug discovery and AI-aided drug design (AIDD) by addressing the scarcity of public PROTAC structural data.
  • To establish a publicly accessible resource for researchers in the PROTAC field.

Main Methods:

  • Systematic collection and manual screening of PROTAC patents published between 2013 and 2023.
  • Expert curation to identify unique PROTAC compounds and their corresponding protein targets.
  • Utilized the ADMETlab 3.0 platform for predicting 120 physicochemical properties of the identified compounds.

Main Results:

  • Identified and curated 63,136 unique PROTAC compounds from 590 patent families.
  • Documented 252 distinct protein targets associated with the identified PROTAC compounds.
  • Generated a dataset encompassing physicochemical properties for all compounds, made publicly available on Figshare and via a dedicated webserver.

Conclusions:

  • The developed PROTAC patent database and webserver significantly enhance data accessibility for computational and AI-driven drug discovery.
  • This resource provides a valuable foundation for accelerating the design and development of novel PROTAC therapeutics.
  • The dataset's structure allows for future expansion as new PROTAC-related patents are published, ensuring continued relevance.