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Related Experiment Video

Updated: Jun 26, 2025

Achieving Efficient Fragment Screening at XChem Facility at Diamond Light Source
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Exploring SureChEMBL from a drug discovery perspective.

Yojana Gadiya1,2,3, Simran Shetty4,5,6, Martin Hofmann-Apitius7,8

  • 1Fraunhofer Institute for Translational Medicine and Pharmacology (ITMP), Schnackenburgallee 114, 22525, Hamburg, Germany. Yojana.Gadiya@itmp.fraunhofer.de.

Scientific Data
|May 16, 2024
PubMed
Summary
This summary is machine-generated.

This study analyzes SureChEMBL patent data to identify potential drug candidates. We assess compounds for drug-likeness and development stage, aiding pharmaceutical drug discovery.

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Area of Science:

  • Pharmaceutical Chemistry
  • Medicinal Chemistry
  • Drug Discovery Informatics

Background:

  • Drug development is costly, making patent protection crucial.
  • Analyzing patent documents helps identify freedom-to-operate for new drug candidates.
  • Public repositories offer automated methods for extracting therapeutic agent information.

Purpose of the Study:

  • To provide a comprehensive overview of patent compounds in SureChEMBL.
  • To assess the relevance of these compounds for pharmaceutical drug discovery.
  • To evaluate compounds based on drug-likeness and clinical development stage.

Main Methods:

  • Explored SureChEMBL, a public patent database for life sciences.
  • Identified patent compounds across public chemical data resources.
  • Pinpointed chemical annotations within patent documents.
  • Evaluated compounds for drug-likeness criteria.
  • Examined reported drug development stages for clinical success.

Main Results:

  • Catalogued patent compounds from the SureChEMBL database.
  • Assessed the drug-likeness and potential of identified compounds.
  • Analyzed the clinical development status of these pharmaceutical compounds.
  • Provided insights into the relevance of SureChEMBL compounds for drug discovery.

Conclusions:

  • SureChEMBL is a valuable resource for identifying patent compounds in life sciences.
  • The study demonstrates a methodology for assessing drug candidate potential from patent data.
  • Findings contribute to understanding the landscape of compounds relevant to pharmaceutical drug discovery.