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GSP4PDB: a web tool to visualize, search and explore protein-ligand structural patterns

Angles, Renzo; Arenas-Salinas, Mauricio; García, Roberto; Reyes-Suarez, Jose Antonio; Pohl, Ehmke

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Renzo Angles

Mauricio Arenas-Salinas

Roberto García

Jose Antonio Reyes-Suarez


Background: In the field of protein engineering and biotechnology, the discovery and characterization of structural patterns is highly relevant as these patterns can give fundamental insights into protein-ligand interaction and protein function. This paper presents GSP4PDB, a bioinformatics web tool that enables the user to visualize, search and explore protein-ligand structural patterns within the entire Protein Data Bank. Results: We introduce the notion of graph-based structural pattern (GSP) as an abstract model for representing protein-ligand interactions. A GSP is a graph where the nodes represent entities of the protein-ligand complex (amino acids and ligands) and the edges represent structural relationships (e.g. distances ligand - amino acid). The novel feature of GSP4PDB is a simple and intuitive graphical interface where the user can “draw” a GSP and execute its search in a relational database containing the structural data of each PDB entry. The results of the search are displayed using the same graph-based representation of the pattern. The user can further explore and analyse the results using a wide range of filters, or download their related information for external post-processing and analysis. Conclusions: GSP4PDB is a user-friendly and efficient application to search and discover new patterns of protein-ligand interaction.


Angles, R., Arenas-Salinas, M., García, R., Reyes-Suarez, J. A., & Pohl, E. (2020). GSP4PDB: a web tool to visualize, search and explore protein-ligand structural patterns. BMC Bioinformatics, 21(S2), Article 85.

Journal Article Type Article
Online Publication Date Mar 11, 2020
Publication Date 2020
Deposit Date Apr 1, 2020
Publicly Available Date Apr 2, 2020
Journal BMC Bioinformatics
Publisher BioMed Central
Peer Reviewed Peer Reviewed
Volume 21
Issue S2
Article Number 85


Published Journal Article (3.1 Mb)

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This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated.

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