Biology subjects

Morgan, B. A.

Publications and source records attributed to Morgan, B. A..

4 recordsLinked to original sources

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

Individual cells traffic the Vasopressin 2 Receptor to their cell surface with different success

G protein coupled receptors (GPCRs) translate the actions of hormones into intracellular signalling events. Mutations in GPCRs can prevent their correct expression and trafficking to the cell surface and cause disease. We use single cell measurements in HEK293 cells to show that the balance between endoplasmic reticulum (ER) and cell surface localisation of the Vasopressin 2 receptor (V2R) varies significantly from cell to cell. We find that mutations in the V2R affect the proportion of cells able to send this GPCR to the cell surface but do not prevent all cells in the population from correctly trafficking the mutant receptors. These findings reveal that the ability of cells to correctly traffic V2R to the cell surface depends not only on the expressed V2R mutant but also on the individual cell environment. Significance statementMissense mutations in the Vasopressin 2 Receptor (V2R) cause Nephrogenic Diabetes Insipidus. Some of these mutations prevent correct expression and trafficking of V2R to the cell surface resulting in a loss-of-function. We show -using single cell measurements-that the balance between endoplasmic reticulum and cell surface localisation of the V2R varies significantly from cell to cell, independent from its expression level. Mutations affect the proportion of cells able to send V2R to the cell surface but do not prevent all cells in the population from correctly trafficking the mutant receptors. Hence, the ability of cells to correctly traffic V2R to the cell surface depends not only on expressed V2R mutant but also on the cell environment.

molecular biology↗

bioRxiv2021

Prediction of ligand-receptor pharmacological activities using a combined docking and machine learning approach

G protein coupled receptors (GPCRs) are valuable therapeutic targets for many diseases. A central question of GPCR drug discovery is to understand what determines the agonism or antagonism of ligands which bind them. Ligands exert their action via the interactions in the ligand binding pocket. We hypothesised that there is a common set of receptor interactions made by ligands of diverse structures that mediate their action and that among a large dataset of different ligands, the functionally important interactions will be over-represented. We computationally docked ~2700 known {beta}2AR ligands to multiple {beta}2AR structures, generating ca 75,000 docking poses and predicted all atomic interactions between the receptor and the ligand. We used machine learning (ML) techniques to identify specific interactions that correlate with the agonist or antagonist activity of these ligands. The interpretation of ML analysis in human understandable form allowed us to construct an exquisitely detailed structure-activity relationship that identifies small changes to the ligands that invert their activity and thus helps to guide the drug discovery process. This approach can be readily applied to any drug target.

bioinformatics↗

bioRxiv2018

Comparative evidence for the independent evolution of hair and sweat gland traits in primates

Humans differ in many respects from other primates, but perhaps no derived human feature is more striking than our naked skin. Long purported to be adaptive, humans unique external appearance is characterized by changes in both the patterning of hair follicles and eccrine sweat glands, producing decreased hair cover and increased sweat gland density. Despite the conspicuousness of these features and their potential evolutionary importance, there is a lack of clarity regarding how they evolved within the primate lineage. We thus collected and quantified the density of hair follicles and eccrine sweat glands from five regions of the skin in three species of primates: macaque, chimpanzee and human. Although human hair cover is greatly attenuated relative to that of our close relatives, we find that humans have a chimpanzee-like hair density that is significantly lower than that of macaques. In contrast, eccrine gland density is on average 10-fold higher in humans compared to chimpanzees and macaques, whose density is strikingly similar. Our findings suggest that a decrease in hair density in the ancestors of humans and apes was followed by an increase in eccrine gland density and a reduction in fur cover in humans. This work answers longstanding questions about the traits that make human skin unique and substantiates a model in which the evolution of expanded eccrine gland density was exclusive to the human lineage.

evolutionary biology↗