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ActivityFinder: Toward the Fully Automatic Integration of Structural and Binding Affinity Data.

Emanuel S R Ehmki1, Torben Gutermuth1, Tobias Harren1

  • 1ZBH - Center for Bioinformatics, University of Hamburg, Albert Einstein Ring 8-10, 22761 Hamburg, Germany.

Journal of Chemical Information and Modeling
|January 2, 2026
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Summary
This summary is machine-generated.

ActivityFinder is a new automated method that reliably links protein structures to bioactivity data. This computational chemistry tool integrates PDB files and ChEMBL database information, overcoming key integration challenges.

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Area of Science:

  • Computational chemistry and cheminformatics
  • Structural biology
  • Drug discovery

Background:

  • Integrating structural (PDB) and bioactivity (ChEMBL) data is complex.
  • Existing methods struggle with data heterogeneity and lack of direct integration.
  • A fully automated solution is needed for proprietary and unpublished datasets.

Purpose of the Study:

  • To introduce ActivityFinder, an automated method for linking protein-ligand crystal structures to bioactivity assay data.
  • To provide a solution that works with PDB files and SQL databases like ChEMBL without external services.
  • To enable reliable integration of structural and bioactivity data for pharmaceutical research.

Main Methods:

  • ActivityFinder uses sequence alignments and detailed chemical structure matching.
  • The method requires only PDB files and a structured SQL database (e.g., ChEMBL).
  • It addresses ligand heterogeneity, sequence variants, and binding-site mutations at an atomistic level.

Main Results:

  • Successfully linked 20,197 PDB structures and 13,734 ligands with 17,829 unique ChEMBL ligands across 2,585 targets.
  • Covered over one million bioactivity data points, demonstrating broad applicability.
  • Reproduced existing links and expanded data linkage by handling structural variations.

Conclusions:

  • ActivityFinder offers a reliable and automated solution for integrating structural and bioactivity data.
  • The method is suitable for proprietary datasets common in the pharmaceutical industry.
  • ActivityFinder is accessible via the ProteinsPlus platform API and as a PostgreSQL database dump.