Biology subjects

Fortney, K.

Publications and source records attributed to Fortney, K..

5 recordsLinked to original sources

bioRxiv2025

Inhibition of NLRP3 by a CNS-penetrating indazole scaffold

Low-grade inflammation is a hallmark of ageing and a key cause of age-related impairments and diseases1. The NOD-like receptor NLRP3 senses a variety of danger signals and environmental insults, resulting in pro-inflammatory response, inflammasome formation and pyroptosis2,3. Its aberrant activation has been linked to many acute and chronic diseases ranging from atherosclerosis to Alzheimers disease and cancer, making NLRP3 an attractive therapeutic target4,5. Here we report the discovery, characterization, and structure of an indazole-based NLRP3 antagonist, BAL-1516, which potently inhibits inflammasome formation in monocytes and microglia. The cryo-electron microscopy structure of BAL-1516 bound to NLRP3 reveals a previously undescribed compound binding site at a surface groove of the nucleotide-binding domain with contacts to the FISNA and WHD subdomains. The characteristic feature of BAL compound binding is the formation of three hydrogen bonds to the peripheral {beta}-strand of the triple-ATPase; two from the indazoles nitrogen atoms and a third from the compounds linker region. Additional phenyl and thiazole moieties render the compound hydrophobic, allowing excellent blood-brain barrier penetration. The compound binding site is highly specific for NOD-like receptors, and the optimized compound BAL-1516 is able to directly bind mouse NLRP3 despite two conservative residue changes in the binding interface. The BAL compounds represent a first-in-class family of NLRP3 inhibitors, providing a broad design space, including covalent and degradative properties, for the development of NLRP3-directed therapeutics. The innate immune system contains cytosolic proteins that sense cellular stress caused by bacterial, viral and fungal infections or sterile inflammation, to control cellular integrity2. NLRP3 is a well-studied member of the nucleotide-binding oligomerization domain (NOD)-like receptors (NLRs) that is involved in the activation of the inflammasome, a multiprotein complex that mediates inflammation6. Upon detection of stress or pathogen-associated signals, NLRP3 triggers the activation of caspase-1, which leads to the production of pro-inflammatory cytokines such as IL-1{beta} and IL-18, driving inflammatory responses and ultimately pyroptotic cell death. In the context of neuroinflammation, NLRP3 plays a significant role in the pathogenesis of various neurodegenerative diseases, including Alzheimers disease, Parkinsons disease, and multiple sclerosis7. Research into targeting NLRP3 signalling with CNS-penetrating molecules holds potential for developing therapeutic strategies to alleviate neuroinflammatory conditions and to slow the progression of neurodegenerative diseases.

immunology↗

bioRxiv2024

Discovery of a Potent and Selective Inhibitor of Human NLRP3 with a Novel Binding Modality and Mechanism of Action

The NLRP3 inflammasome is an intracellular protein complex that causes inflammation via the release of IL-1{beta} and pyroptosis. NLRP3 activation is associated with many age-related inflammatory diseases, and NLRP3 inhibition is a promising therapeutic strategy. We previously performed a DNA encoded library screen to identify novel NLRP3 binding molecules. Herein we describe the characterization of BAL-0028 as a potent and specific inhibitor of NLRP3 signaling. Notably, BAL-0028 is a poor inhibitor of mouse NLRP3 but inhibits human and primate NLRP3 with nanomolar potency. Using cellular and biochemical analyses we demonstrate that BAL-0028 binds to the NLRP3 NACHT domain at a site that is distinct from the MCC950 binding pocket. Using humanized NLRP3 mice we show that a derivative of BAL-0028 inhibits NLRP3 activation in vivo in a peritonitis model. Finally, we demonstrate that BAL-0028 inhibits select hyperactive NLRP3 mutations associated with autoinflammatory diseases more potently than does MCC950. BAL-0028 thus represents a new modality for NLRP3 inhibition in inflammatory diseases. SUMMARYNLRP3 is a target for anti-inflammatory therapies and can be inhibited by the tool compound MCC950. We describe the characterization of a new small molecule inhibitor of NLRP3 BAL-0028 that has a distinct mechanism of action and binding site.

immunology↗

bioRxiv2021

Eicosanoid signaling as a therapeutic target in middle-aged mice with severe COVID-19

Coronavirus disease 2019 (COVID-19) is especially severe in aged populations1. Resolution of the COVID-19 pandemic has been advanced by the recent development of SARS-CoV-2 vaccines, but vaccine efficacy is partly compromised by the recent emergence of SARS-CoV-2 variants with enhanced transmissibility2. The emergence of these variants emphasizes the need for further development of anti-SARS-CoV-2 therapies, especially in aged populations. Here, we describe the isolation of a new set of highly virulent mouse-adapted viruses and use them to test a novel therapeutic drug useful in infections of aged animals. Initially, we show that many of the mutations observed in SARS-CoV-2 during mouse adaptation (at positions 417, 484, 501 of the spike protein) also arise in humans in variants of concern (VOC)2. Their appearance during mouse adaptation indicates that immune pressure is not required for their selection. Similar to the human infection, aged mice infected with mouse-adapted SARS-CoV-2 develop more severe disease than young mice. In murine SARS, in which severity is also age-dependent, we showed that elevated levels of an eicosanoid, prostaglandin D2 (PGD2) and of a phospholipase, PLA2G2D, contributed to poor outcomes in aged mice3,4. Using our virulent mouse-adapted SARS-CoV-2, we show that infection of middle-aged mice lacking expression of DP1, a PGD2 receptor, or PLA2G2D are protected from severe disease. Further, treatment with a DP1 antagonist, asapiprant, protected aged mice from a lethal infection. DP1 antagonism is one of the first interventions in SARS-CoV-2-infected animals that specifically protects aged animals, and demonstrates that the PLA2G2D-PGD2/DP1 pathway is a useful target for therapeutic interventions. (Words: 254)

microbiology↗

bioRxiv2019

Integrating untargeted metabolomics, genetically informed causal inference, and pathway enrichment to define the obesity metabolome

BackgroundObesity and its associated diseases are major health problems characterized by extensive metabolic disturbances. Understanding the causal connections between these phenotypes and variation in metabolite levels can uncover relevant biology and inform novel intervention strategies. Recent studies have combined metabolite profiling with genetic instrumental variable (IV) analyses to infer the direction of causality between metabolites and obesity, but often omitted a large portion of untargeted profiling data consisting of unknown, unidentified metabolite signals.\n\nMethodsWe expanded upon previous research by identifying body mass index (BMI)-associated metabolites in multiple untargeted metabolomics datasets, and then performing bidirectional IV analysis to classify these metabolites based on their inferred causal relationships with BMI. Meta-analysis and pathway analysis of both known and unknown metabolites across datasets were enabled by our recently developed bioinformatics suite, PAIRUP-MS.\n\nResultsWe identified 10 known metabolites that are more likely to be the causes (e.g. alpha-hydroxybutyrate) or effects (e.g. valine) of BMI, or may have more complex bidirectional cause-effect relationships with BMI (e.g. glycine). Importantly, we also identified about 5 times more unknown than known metabolites in each of these three categories. Pathway analysis incorporating both known and unknown metabolites prioritized 40 enriched (p < 0.05) metabolite sets for the cause versus effect groups, providing further support that these two metabolite groups are linked to obesity via distinct biological mechanisms.\n\nConclusionsThese findings demonstrate the potential utility of our approach to uncover causal connections with obesity from untargeted metabolomics datasets. Combining genetically informed causal inference with the ability to map unknown metabolites across datasets provides a path to jointly analyze many untargeted datasets with obesity or other phenotypes. This approach, applied to larger datasets with genotype and untargeted metabolite data, should generate sufficient power for robust discovery and replication of causal biological connections between metabolites and various human diseases.

bioinformatics↗

bioRxiv2017

PAIRUP-MS: Pathway Analysis and Imputation to Relate Unknowns in Profiles from Mass Spectrometry-based metabolite data

Metabolomics is a powerful approach for discovering biomarkers and metabolic quantitative trait loci. While untargeted profiling methods can measure up to thousands of metabolite signals in a single experiment, many signals cannot be readily identified as known metabolites or compared across datasets, making it difficult to infer biology and to conduct well-powered meta-analyses across studies. To deal with these challenges, we developed a suite of computational methods, PAIRUP-MS, to match metabolite signals across mass spectrometry-based profiling datasets using an imputation-based approach and to generate pathway annotations for these signals. We performed meta and pathway analyses for both known and unknown signals in multiple datasets and then validated the results using genetic associations. Finally, we applied the methods to detect metabolite signals and pathways associated with body mass index, demonstrating that our framework is useful for analyzing unknown signals in a robust and biologically meaningful manner and for improving the power of untargeted metabolomics studies.

bioinformatics↗