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Preprint: AI-Powered Identification of Inflammasome Inhibitors
June 17, 2024
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10 minutes
We are thrilled to announce the submission of our latest research paper, titled "A Combinatorial AI and Cell Biology Approach Identifies Mechanistically Distinct Inflammasome Inhibitors and Implicates the Raf Pathway in Inflammasome Signaling," to iScience. This cutting-edge study represents a significant advancement in the field of immunology and AI-powered drug discovery.
Inflammasomes are essential components of the innate immune system that convert danger signals into pro-inflammatory responses. These protein complexes are central to numerous biological pathways, and their dysregulation is linked to various acute and chronic diseases. Given the diverse nature of these conditions, there is a critical need for therapeutic strategies that are adaptable to disease variability.
Our research team has developed a physiologically relevant, high-content imaging assay using human peripheral blood mononuclear cells (PBMCs) to investigate different stages of inflammasome signaling. Due to limitations in image analysis, identifying the complex cellular morphologies tied to imflammasome signaling has been challenging. By integrating modern supervised and unsupervised machine-learning methods, we created a series of novel, biologically interpretable analytical readouts. These readouts enabled us to identify and characterize various cellular states within inflammasome pathways.
Scaling our methods into a phenotypic screen, we evaluated an annotated bioactive library of 12,000 compounds, ultimately classifying and validating over 100 potent and mechanistically distinct inflammasome inhibitors. Our findings highlighted compounds targeting known inflammasome components, such as P2X7 and HSP90, as well as compounds that interact with the Raf pathway, a novel discovery in the context of inflammasome signaling.
This study exemplifies how AI-based analyses of high-content imaging data can uncover new insights into complex biological pathways and facilitate the discovery of novel therapeutic compounds and targets. We are excited about the wide-reaching potential implications of our methods for the discovery and development of new treatments for diseases.
Stay tuned for more updates as we await peer review!
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