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

The reliable integration of structural and bioactivity data remains a significant bottleneck in computational chemistry and cheminformatics. While curated databases such as PDBbind and ChEMBL provide valuable resources, integrating structural data in the form of, for example, PDB files and bioactivity assays in the form of structured data, like ChEMBL, is inherently complex, and no fully integrated solution has been published so far. This work introduces ActivityFinder, a fully automated method for linking protein-ligand crystal structures to bioactivity assay data without relying on external services or continuous data connections. The method solely requires structural information in the form of PDB files and a structured SQL database such as ChEMBL, making it highly suitable for proprietary or unpublished data sets typically used within the pharmaceutical industry or early research in general. ActivityFinder utilizes sequence alignments and detailed chemical structure matching. Its accuracy is showcased for the task of associating PDB entries with corresponding data in ChEMBL. Applying this method, we linked 20197 PDB structures and 13734 ligands with 17829 unique ChEMBL ligands across 2585 targets, covering over one million bioactivity data points. Compared to existing approaches based on identifier mapping, ActivityFinder reproduces reported links but also broadens the set of linked data by explicitly addressing ligand heterogeneity, sequence variants, and binding-site mutations at an atomistic level. ActivityFinder is available via the Rest API of the ProteinsPlus platform, and the data is published as a PostgreSQL database dump, enabling scientists to integrate and explore structural and bioactivity data reliably.

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Publication Details

Journal
Journal of Chemical Information and Modeling
Published
2026-01-02
DOI
https://doi.org/10.1021/acs.jcim.5c02505
Citations
2
Primary Topic
Computational Drug Discovery Methods
Type
article
Field-Weighted Citation Impact
90.33
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article

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

Emanuel S. R. Ehmki, Tobias Harren, Torben Gutermuth, Stefan Kurtz et al.
2 citations
Journal of Chemical Information and Modeling
Computational Drug Discovery Methods
90.33
article

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

Emanuel S. R. Ehmki, Tobias Harren, Torben Gutermuth, Stefan Kurtz, Matthias Rarey
article en
2 citations

Abstract

The reliable integration of structural and bioactivity data remains a significant bottleneck in computational chemistry and cheminformatics. While curated databases such as PDBbind and ChEMBL provide valuable resources, integrating structural data in the form of, for example, PDB files and bioactivity assays in the form of structured data, like ChEMBL, is inherently complex, and no fully integrated solution has been published so far. This work introduces ActivityFinder, a fully automated method for linking protein-ligand crystal structures to bioactivity assay data without relying on external services or continuous data connections. The method solely requires structural information in the form of PDB files and a structured SQL database such as ChEMBL, making it highly suitable for proprietary or unpublished data sets typically used within the pharmaceutical industry or early research in general. ActivityFinder utilizes sequence alignments and detailed chemical structure matching. Its accuracy is showcased for the task of associating PDB entries with corresponding data in ChEMBL. Applying this method, we linked 20197 PDB structures and 13734 ligands with 17829 unique ChEMBL ligands across 2585 targets, covering over one million bioactivity data points. Compared to existing approaches based on identifier mapping, ActivityFinder reproduces reported links but also broadens the set of linked data by explicitly addressing ligand heterogeneity, sequence variants, and binding-site mutations at an atomistic level. ActivityFinder is available via the Rest API of the ProteinsPlus platform, and the data is published as a PostgreSQL database dump, enabling scientists to integrate and explore structural and bioactivity data reliably.

Journal of Chemical Information and ModelingVol. 66(2)
Universität Hamburg (DE)
Industry, innovation and infrastructure
Openalex Percentile: Top 0%
Computational Drug Discovery Methods
90.33
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ActivityFinder: Toward the Fully Automatic Integration of Structural and Binding Affinity Data — Emanuel S. R. Ehmki, Tobias Harren, et al. · Journal of Chemical Information and Modeling (2026) | TGRS Research Map | TGRS