ABSTRACT The NLRP3 inflammasome is a multi‐protein complex that plays a crucial role in inflammatory processes mediated by the innate immune system. Dysregulated NLRP3 activation has been implicated in age‐related inflammatory diseases, making it a promising therapeutic target. Here, we report that the synthetic membrane‐active antimicrobial peptide Pep19‐2.5 directly inhibits NLRP3 inflammasome activation. Through cellular, biophysical, and biochemical analyses, we find that Pep19‐2.5 suppresses NLRP3 inflammasome signaling downstream of NLRP3 activation. Pep19‐2.5 interacts with macrophage membranes, supporting a membrane‐targeting mechanism for its anti‐inflammatory effects. Mechanistically, Pep19‐2.5 binds to phosphatidylinositol (PI)‐containing lipid membranes and dispersed trans‐Golgi network (dTGN) structures, which could potentially affect NLRP3 recruitment to the dTGN. We demonstrate a strong and NLRP3‐dependent induction of IL‐1β secretion from human macrophages by house dust mite (HDM) extract, which can be inhibited by Pep19‐2.5. In line with these findings, therapeutic application of Pep19‐2.5 via the nasal aerosol route reduces IL‐1β levels, eosinophil infiltration in bronchoalveolar lavage and significantly improved lung function in an in vivo HDM‐mouse model of allergic airway inflammation. Our findings highlight the therapeutic potential of targeting NLRP3 activation by the small membrane‐active peptide Pep19‐2.5 for the treatment of NLRP3‐driven inflammatory diseases.
Jonas Engelhardt, Nico Kirsch, Aileen Kerfin et al.· Advancement of science· 0 citations
Experimental validation and functional optimization remain bottlenecks in AI-based protein design. We present a scalable workflow for developing AI-designed minibinders against cancer-associated surface proteins. Screening thousands of designs using mammalian cell-surface display identifies several high-affinity PD-L1 minibinders but far fewer for CD276 (B7-H3) and VTCN1 (B7-H4), highlighting substantial target dependence. Interface predicted template modeling (ipTM) scores generated by Chai-1 with ESM embeddings correlate with binding success and capture deleterious effects of interface mutations. Fluorophore-labeled AI-minibinders enable flow-cytometric staining comparable to conventional antibodies. However, when incorporated into chimeric antigen receptors (CAR), some show poor cell-surface trafficking and limited functionality. Redesign through a genetic algorithm-based diversification strategy that preserves the binding interface while changing non-binding surfaces experimentally reveals an isoelectric point (pI) window that improves CAR expression and enhances target-selective tumor cell killing. Our findings identify biochemical optimization beyond the binding interface as a critical requirement for translating AI-minibinders into functional applications. In this work the authors present a scalable mammalian cell-display workflow to identify AI-designed minibinders against cancer surface targets. AI-guided optimization beyond the binding interface improves their expression as chimeric antigen receptors and target-selective killing.
B. Broske, B. McEnroe, S. C. Frechen et al.· Nature Communications· 0 citations
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