Biologyarticle2026-09-05

COCaDA-web: an interactive web server for exploratory analysis of interatomic contacts in proteins

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Abstract

Protein contacts often serve as prerequisites for characterizing molecular interactions and bonds. Traditional implementations remain computationally expensive, posing significant scalability and usability challenges. We present COCaDA-web, an interactive and user-friendly Web Server that allows users to dynamically explore and visualize protein contact data, building upon the COCaDA (COntact search pruning by C \(\alpha \) Distance Analysis) command-line tool, which is aimed for large-scale protein interatomic contact detection. Users can submit their own queries, or explore precomputed data for over 240,000 proteins in the Protein Data Bank. COCaDA-web includes novel features like pH value customization for protonation-aware analysis and biological assembly support, and takes less than a second to process proteins up to 1000 residues. Detailed results are provided for each entry in a dynamic table, alongside an interactive 3D visualization, annotated PyMOL sessions, and step-by-step usage guides. We demonstrate our tool by performing two comparative analyses of the interatomic contacts of Transthyretin and 5-Hydroxyisourate Hydrolase, two evolutionarily and structurally related proteins yet known to perform distinct biological functions associated with amyloidogenesis and gout. COCaDA-web reveals important differences, especially in their central cavities, that help explain the functional divergence of these proteins. At the moment, the COCaDA-web database contains approximately 746 million contacts, divided into 690 million intra-chain and 55 million inter-chain. COCaDA-web provides a fast, interactive, and scalable platform for protein interatomic contact analysis, combining efficient large-scale contact detection with intuitive visualization and exploration tools. COCaDA-web is freely accessible at https://bioinfo.dcc.ufmg.br/cocada-web , and there are no login requirements.

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View paper (DOI)Open access versionOpenAlexBMC BioinformaticsPublished 2026-09-05

Authors: Rafael Pereira Lemos, Diego Mariano, Ana Luísa Araújo Bastos, Sabrina de Azevedo Silveira, Raquel Cardoso de Melo-Minardi

Institutions: Universität Hamburg, Universidade Federal de Viçosa, Universidade Federal de Minas Gerais