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Target Engagement Analysis and Link to Pharmacodynamic Endpoint for a Novel Class of CNS-penetrant and Efficacious p38α MAPK Inhibitors

Overview of attention for article published in Journal of Neuroimmune Pharmacology, May 2014
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Title
Target Engagement Analysis and Link to Pharmacodynamic Endpoint for a Novel Class of CNS-penetrant and Efficacious p38α MAPK Inhibitors
Published in
Journal of Neuroimmune Pharmacology, May 2014
DOI 10.1007/s11481-014-9543-3
Pubmed ID
Authors

Adam D. Bachstetter, D. Martin Watterson, Linda J. Van Eldik

Abstract

The protein kinase, p38α MAPK, is a key intracellular transducer of stressor-induced neuroinflammatory responses and, as such, is of high interest as a potential therapeutic target. We recently reported the synthesis and evaluation of first-in-class CNS-penetrant and highly specific p38 MAPK inhibitors that avoid target crossover issues seen in popular small molecule p38 MAPK inhibitors used in hundreds of previous reports. The novel p38 MAPK inhibitors, represented in this study by MW181, are efficacious in vivo. Pharmacodynamic actions include attenuation of stressor-induced increases in brain proinflammatory cytokine levels. We report here more detailed analyses of MW181 target engagement and specific linkage to the downstream increase in glia proinflammatory cytokine production. In vivo validation included demonstration that oral administration of MW181 suppresses lipopolysaccharide-induced increases in mouse brain IL-1β, TNFα, IL-6, IL-10, and CXCL1 but not in a drug-resistant p38α MAPK mutant mouse.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 20%
Student > Ph. D. Student 2 13%
Other 2 13%
Student > Doctoral Student 1 7%
Unknown 7 47%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 27%
Pharmacology, Toxicology and Pharmaceutical Science 2 13%
Computer Science 1 7%
Neuroscience 1 7%
Unknown 7 47%