G proteincoupled receptors (GPCRs) represent the largest group of membrane receptors for transmembrane signal transduction. Ligandinduced activation of GPCRs triggers G protein activation followed by various signaling cascades. Understanding the structural and energetic determinants of ligand binding to GPCRs and GPCRs to G proteins is crucial to the design of pharmacological treatments targeting specific conformations of these proteins to precisely control their signaling properties. In this study, we focused on interactions of a prototypical GPCR, beta2 adrenergic receptor (β 2 AR), with its endogenous agonist, norepinephrine (NE), and the stimulatory G protein (G s ). Using molecular dynamics (MD) simulations, we demonstrated the stabilization of cationic NE, NE(+), binding to β 2 AR by G s protein recruitment, in line with experimental observations. We also captured the partial dissociation of the ligand from β 2 AR and the conformational interconversions of G s between closed and open conformations in the NE(+)–β 2 AR–G s ternary complex while it is still bound to the receptor. The variation of NE(+) binding poses was found to alter G s α subunit (G s α) conformational transitions. Our simulations showed that the interdomain movement and the stacking of G s α α1 and α5 helices are significant for increasing the distance between the G s α and β 2 AR, which may indicate a partial dissociation of G s α The distance increase commences when G s α is predominantly in an open state and can be triggered by the intracellular loop 3 (ICL3) of β 2 AR interacting with G s α, causing conformational changes of the α5 helix. Our results help explain molecular mechanisms of ligand and GPCRmediated modulation of G protein activation.
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HardyMuckenhoupt Bounds for Laplacian Eigenvalues
We present two graph quantities Psi(G, S) and Psi_2(G) which give constant factor estimates to the
Dirichlet and Neumann eigenvalues, Lambda(G, S) and Lambda_2(G), respectively. Our techniques make use of a discrete Hardytype inequality due to Muckenhoupt.
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 Award ID(s):
 1729478
 NSFPAR ID:
 10210186
 Date Published:
 Journal Name:
 Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques
 Volume:
 145
 Format(s):
 Medium: X
 Sponsoring Org:
 National Science Foundation
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