Honorable Mention in the EuroVis Best Paper Category

Exploratory analysis of the chemical space is an important task in the field of cheminformatics. For example, in drug discovery research, chemists investigate sets of thousands of chemical compounds in order to identify novel yet structurally similar synthetic compounds to replace natural products. Manually exploring the chemical space inhabited by all possible molecules and chemical compounds is impractical, and therefore presents a challenge. To fill this gap, we present ChemoGraph, a novel visual analytics technique for interactively exploring related chemicals. In ChemoGraph, we formalize a chemical space as a hypergraph and apply novel machine-learning models to compute related chemical compounds. It uses a database to find related compounds from a known space and a machine learning model to generate new ones, which helps enlarge the known space. Moreover, ChemoGraph highlights interactive features that support users in viewing, comparing, and organizing computationally identified related chemicals. With a drug discovery usage scenario and initial expert feedback from a case study, we demonstrate the usefulness of ChemoGraph.

Keywords: chemical space exploration, cheminformatics, multipartite graphs, data visualization

CCS Concepts: Applied computing → Chemistry

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Kale, B., Clyde, A., Sun, M., Ramanathan, A., Stevens, R., Papka, M. E., ChemoGraph: Interactive Visual Exploration of the Chemical Space, Eurographics Conference on Visualization (EuroVis) 2023, vol 42, no 3, Leipzig, Germany, The Eurographics Association and John Wiley & Sons Ltd., June 12th, 2023. https://doi.org/10.1111/cgf.14807