Constellation Plots in KNIME: An Automated Scaffold‐Based Workflow for Interactive Chemical Space Visualization
Year: 2026
Type: article
Abstract: Chemical space analysis is extensively used in different chemistry areas, ranging from the study of natural products to drug discovery projects. Its versatility stems from the ability to integrate continuous properties with molecular representations. This data is used to generate visualizations through dimensionality reduction algorithms. Constellation Plots have been proposed as a general approach to the visual representation of chemical space by encoding structural similarity, scaffold contents, frequency, and continuous properties into a single coordinate-based map. Thus, Constellation Plots provide a high-density visual representation of the chemical space of compound datasets with complex relations. Despite the versatility of Constellation Plots, there remains a significant lack of intuitive, user-friendly, or low-code protocols to automate the generation of these plots for non-computational experts. Herein, we present an interactive and automated scaffold-based Constellation Plot workflow developed within the open-source platform KNIME, facilitating chemical space visualization and analysis. To illustrate the application of the workflow, we used a dataset of 5,211 compounds that inhibit Tau protein, a key therapeutic target for Alzheimer's disease. The KNIME workflow is a general resource that can be used to analyze virtually any data set annotated with a property, including biological activity. The workflow is freely available at: https://github.com/Daniphantom99/KNIME_Constellation_plots.
Source: Molecular Informatics
DOI: 10.1002/minf.70035
Institutions: Universidad Nacional Autónoma de México, Uppsala University
Language: English
Subfield: Computational Theory and Mathematics
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $3,800
OpenAlex ID: W7159117438
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