Measurement of Receptor Signaling Bias

Probing phosphorylation events in biological membranes: The transducer function

The extracellular environment is sensed by receptors in the plasma membrane. Some of these receptors initiate cytoplasmic signaling cascades involving phosphorylation: the addition of a phosphate group to a specific amino acid, such as tyrosine, in a protein. Receptor Tyrosine Kinases (RTKs) are one large class of membrane receptors that can directly initiate signaling cascades through their intracellular kinase domains, which both catalyze tyrosine phosphorylation and get phosphorylated. In the first step of signaling, the ligands stabilize phosphorylation-competent RTK dimers and oligomers, which leads to the phosphorylation of specific tyrosine residues in the activation loop of the kinases. Here we discuss quantitative measurements of tyrosine phosphorylation efficiencies for RTKs, described by the "transducer function". The transducer function links the phosphorylation (the response) and the binding of the activating ligand to the receptor (the stimulus). We overview a methodology that allows such measurements in direct response to ligand binding. We discuss experiments which demonstrate that EGF is a partial agonist, and that two tyrosines in the intracellular domain of EGFR, Y1068 and Y1173, are differentially phosphorylated in the EGF-bound EGFR dimers.

Ligand bias underlies differential signaling of multiple FGFs via FGFR1

The differential signaling of multiple FGF ligands through a single fibroblast growth factor (FGF) receptor (FGFR) plays an important role in embryonic development. Here, we use quantitative biophysical tools to uncover the mechanism behind differences in FGFR1c signaling in response to FGF4, FGF8, and FGF9, a process which is relevant for limb bud outgrowth. We find that FGF8 preferentially induces FRS2 phosphorylation and extracellular matrix loss, while FGF4 and FGF9 preferentially induce FGFR1c phosphorylation and cell growth arrest. Thus, we demonstrate that FGF8 is a biased FGFR1c ligand, as compared to FGF4 and FGF9. Förster resonance energy transfer experiments reveal a correlation between biased signaling and the conformation of the FGFR1c transmembrane domain dimer. Our findings expand the mechanistic understanding of FGF signaling during development and bring the poorly understood concept of receptor tyrosine kinase ligand bias into the spotlight.

Quantification of ligand and mutation-induced bias in EGFR phosphorylation in direct response to ligand binding

Signaling bias is the ability of a receptor to differentially activate downstream signaling pathways in response to different ligands. Bias investigations have been hindered by inconsistent results in different cellular contexts. Here we introduce a methodology to identify and quantify bias in signal transduction across the plasma membrane without contributions from feedback loops and system bias. We apply the methodology to quantify phosphorylation efficiencies and determine absolute bias coefficients. We show that the signaling of epidermal growth factor receptor (EGFR) to EGF and TGFα is biased towards Y1068 and against Y1173 phosphorylation, but has no bias for epiregulin. We further show that the L834R mutation found in non-small-cell lung cancer induces signaling bias as it switches the preferences to Y1173 phosphorylation. The knowledge gained here challenges the current understanding of EGFR signaling in health and disease and opens avenues for the exploration of biased inhibitors as anti-cancer therapies.

Quantitative assessment of ligand bias from bias plots: The bias coefficient "kappa"

The current methods for quantifying ligand bias involve the construction of bias plots and the calculations of bias coefficients that can be compared using statistical methods. However, widely used bias coefficients can diverge in their abilities to identify ligand bias and can give false positives. As the empirical bias plots are considered the most reliable tools in bias identification, here we develop an analytical description of bias plot trajectories and introduce a bias coefficient, kappa, which is calculated from these trajectories. The new bias coefficient complements the tool-set in ligand bias identification in cell signaling research.

The efficacy of receptor tyrosine kinase EphA2 autophosphorylation increases with EphA2 oligomer size

The receptor tyrosine kinase (RTK) EphA2 is expressed in epithelial and endothelial cells and controls the assembly of cell-cell junctions. EphA2 has also been implicated in many diseases, including cancer. Unlike most RTKs, which signal predominantly as dimers, EphA2 readily forms high-order oligomers upon ligand binding. Here, we investigated if a correlation exists between EphA2 signaling properties and the size of the EphA2 oligomers induced by multiple ligands, including the widely used ephrinA1-Fc ligand, the soluble monomeric m-ephrinA1, and novel engineered peptide ligands. We used fluorescence intensity fluctuation (FIF) spectrometry to characterize the EphA2 oligomer populations induced by the different ligands. Interestingly, we found that different monomeric and dimeric ligands induce EphA2 oligomers with widely different size distributions. Our comparison of FIF brightness distribution parameters and EphA2 signaling parameters reveals that the efficacy of EphA2 phosphorylation on tyrosine 588, an autophosphorylation response contributing to EphA2 activation, correlates with EphA2 mean oligomer size. However, we found that other characteristics, such as the efficacy of AKT inhibition and ligand bias coefficients, appear to be independent of EphA2 oligomer size. Taken together, this work highlights the utility of FIF in RTK signaling research and demonstrates a quantitative correlation between the architecture of EphA2 signaling complexes and signaling features.

Ligand bias in receptor tyrosine kinase signaling

Ligand bias is the ability of ligands to differentially activate certain receptor signaling responses compared with others. It reflects differences in the responses of a receptor to specific ligands and has implications for the development of highly specific therapeutics. Whereas ligand bias has been studied primarily for G protein-coupled receptors (GPCRs), there are also reports of ligand bias for receptor tyrosine kinases (RTKs). However, the understanding of RTK ligand bias is lagging behind the knowledge of GPCR ligand bias. In this review, we highlight how protocols that were developed to study GPCR signaling can be used to identify and quantify RTK ligand bias. We also introduce an operational model that can provide insights into the biophysical basis of RTK activation and ligand bias. Finally, we discuss possible mechanisms underpinning RTK ligand bias. Thus, this review serves as a primer for researchers interested in investigating ligand bias in RTK signaling.

Conformational Basis of G Protein-Coupled Receptor Signaling Versatility

G protein-coupled receptors (GPCRs) are privileged structural scaffolds in biology that have the versatility to regulate diverse physiological processes. Interestingly, many GPCR ligands exhibit significant 'bias' - the ability to preferentially activate subsets of the many cellular pathways downstream of these receptors. Recently, complementary information from structural and spectroscopic approaches has made significant inroads into understanding the mechanisms of these biased ligands. The consistently emerging theme is that GPCRs are highly dynamic proteins, and ligands with varying pharmacological properties differentially modulate the equilibrium among multiple conformations. Biased signaling and other recently appreciated complexities of GPCR signaling thus appear to be a natural consequence of the conformational heterogeneity of GPCRs and GPCR-transducer complexes.

A tetrapeptide class of biased analgesics from an Australian fungus targets the µ-opioid receptor

An Australian estuarine isolate of Penicillium sp. MST-MF667 yielded 3 tetrapeptides named the bilaids with an unusual alternating LDLD chirality. Given their resemblance to known short peptide opioid agonists, we elucidated that they were weak (Ki low micromolar) μ-opioid agonists, which led to the design of bilorphin, a potent and selective μ-opioid receptor (MOPr) agonist (Ki 1.1 nM). In sharp contrast to all-natural product opioid peptides that efficaciously recruit β-arrestin, bilorphin is G protein biased, weakly phosphorylating the MOPr and marginally recruiting β-arrestin, with no receptor internalization. Importantly, bilorphin exhibits a similar G protein bias to oliceridine, a small nonpeptide with improved overdose safety. Molecular dynamics simulations of bilorphin and the strongly arrestin-biased endomorphin-2 with the MOPr indicate distinct receptor interactions and receptor conformations that could underlie their large differences in bias. Whereas bilorphin is systemically inactive, a glycosylated analog, bilactorphin, is orally active with similar in vivo potency to morphine. Bilorphin is both a unique molecular tool that enhances understanding of MOPr biased signaling and a promising lead in the development of next generation analgesics.

Serotonergic Psychedelics: Experimental Approaches for Assessing Mechanisms of Action

Recent, well-controlled - albeit small-scale - clinical trials show that serotonergic psychedelics, including psilocybin and lysergic acid diethylamide, possess great promise for treating psychiatric disorders, including treatment-resistant depression. Additionally, fresh results from a deluge of clinical neuroimaging studies are unveiling the dynamic effects of serotonergic psychedelics on functional activity within, and connectivity across, discrete neural systems. These observations have led to testable hypotheses regarding neural processing mechanisms that contribute to psychedelic effects and therapeutic benefits. Despite these advances and a plethora of preclinical and clinical observations supporting a central role for brain serotonin 5-HT2A receptors in producing serotonergic psychedelic effects, lingering and new questions about mechanisms abound. These chiefly pertain to molecular neuropharmacology. This chapter is devoted to illuminating and discussing such questions in the context of preclinical experimental approaches for studying mechanisms of action of serotonergic psychedelics, classic and new.