Molecular Mechanisms of Diverse Activation Stimulated by Different Biased Agonists for the β2-Adrenergic Receptor

Abstract

β2AR is an important drug target protein involving many diseases. Biased drugs induce specific signaling and provide additional clinical utility to optimize β2AR-based therapies. However, the biased signaling mechanism has not been elucidated. Motivated by the issue, we chose four agonists with divergent bias (balanced agonist, G-protein-biased agonist, and β-arrestin-biased agonists) and utilized Gaussian accelerated molecular dynamics simulation coupled with a dynamic network to probe the molecular mechanisms of distinct biased activation induced by the structural differences between the four agonists. Our simulations reveal that the G-protein-biased agonist induces an open conformation with the outward shifts of TM6 and TM7 for the intracellular domain, which will be beneficial to couple G protein. In contrast, the β-arrestin-biased agonists regulate an occluded conformation with a slightly outward movement of TM6 and an inward shift of TM7, which should favor β-arrestin signaling. The balanced agonist does not induce an observable outward shift for TM6 but, along with a slight tilt for TM7, leads to an inactive-like conformation. In addition, our results reveal the first time that ICL3 presents specific conformations with different agonists. The G-protein-biased agonist drives ICL3 to open so that the G protein-binding pocket can be available, while the β-arrestin-biased agonists induce ICL3 to form a closed conformation with a stable local α-helix. MM/PBSA analysis further reveals that the hydroxyl groups in the resorcinol of the G-protein-biased agonist form strong interactions with Y5.38 and S5.42, thus preventing tilting of the TM5 extracellular end. The catechol of the balanced agonist and the β-arrestin-biased ones induces the rearrangement of two hydrophobic residues F6.52 and W6.48. However, different from the balanced agonist, the ethyl substituent of β-arrestin-biased agonists forms additional hydrophobic interactions with W6.48 and F6.51 after the rearrangement, which should contribute to the β-arrestin bias. The shortest pathway analysis further reveals that the three residues Y7.43, N7.45, and N7.49 are crucial for allosterically regulating G-protein-biased signaling, while the two residues W6.48 and F6.44 make an important contribution to regulate β-arrestin-biased signaling. For the balanced agonist NE, the allosteric regulation pathway simultaneously involves the residue associated with G-protein-biased signaling like S5.46 and the residues related to β-arrestin-biased signaling like W6.48 and F6.44, thus producing unbiased signaling. The observations could advance our understanding of the biased activation mechanism on class A GPCRs and provide a useful guideline for the design of biased drugs.

In Silico Study of Allosteric Communication Networks in GPCR Signaling Bias

“…For instance, the betweenness centrality analysis detects the influence of an individual node/connection on the information flow in a receptor network [ 27 ]. On the other hand, the shortest pathway is considered the biologically most relevant pathway [ 28 ]. Finally, community analysis allows us to detect sets of densely connected nodes.…”

“…In a similar study on the β 2 -adrenergic receptor, Chen et al focused on the molecular mechanism of different biased agonists [ 28 ]. For this, the authors computed movement correlation networks combined with the shortest pathway analysis between the binding pocket and the intracellular coupling domain.…”

Molecular Insights into the Heterotropic Allosteric Mechanism in Cytochrome P450 3A4-Mediated Midazolam Metabolism

“…Combining the above information, we can see that the F′–F loop may play an important role in the allosteric effect of the MDZ metabolism, and reducing the flexibility of the F′–F loop may have a negative effect on the allosteric regulation. As we all know that RIN analysis can effectively decipher residue–residue interaction and elucidate allosteric communication, ,,− thus, we performed it to gain insights into the effect of TST 1 on MDZ binding. Comparing the RIN results of the CYP3A4-MDZ and CYP3A4-MDZ-TST 1 systems (Figure and Table S1), we can see that the presence of TST 1 in Site 1 weakens the connections between the “sandwich” structure (L216, P218, and L482) and MDZ by the communication pathway consisting of TST 1 , F219, F220, F213, and F215.…”

Recognition of the ligand-induced spatiotemporal residue pair pattern of β2-adrenergic receptors using 3-D residual networks trained by the time series of protein distance maps

“…Phe240 in ICL3 showed some patterns with the residues in TM3, TM4 and extracellular loop 2 (ECL2). Since the conformation of ICL3 is highly correlated with the bias signal of β2AR [63] , ICL3-associated dynamics might be one of the key patterns to classify the signals. However, the 14 residues in ICL3 were omitted in this work, and the ICL3-associated patterns might be artificial in this model.…”