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Updated: Jun 22, 2025

Visualizing the Conformational Dynamics of Membrane Receptors Using Single-Molecule FRET
Published on: August 17, 2022
Effects of an external static EF on the conformational transition of 5-HT1A receptor: A molecular dynamics simulation
Lulu Guan1, Jingwang Tan1, Bote Qi1
1Department of Sport and Exercise Science, College of Education, Zhejiang University, 866 Yuhangtang Road, Hangzhou, Zhejiang 310058, PR China.
Abstract:
The serotonin receptor subtype 1A (5-HT1AR), one of the G-protein-coupled receptor (GPCR) family, has been implicated in several neurological conditions. Understanding the activation and inactivation mechanism of 5-HT1AR at the molecular level is critical for discovering novel therapeutics in many diseases. Recently there has been a growing appreciation for the role of external electric fields (EFs) in influencing the structure and activity of biomolecules. In this study, we used molecular dynamics (MD) simulations to examine conformational features of active states of 5-HT1AR and investigate the effect of an external static EF with 0.02 V/nm applied on the active state of 5-HT1AR. Our results showed that the active state of 5-HT1AR maintained the native structure, while the EF led to structural modifications in 5-HT1AR, particularly inducing the inward movement of transmembrane helix 6 (TM6). Furthermore, it disturbed the conformational switches associated with activation in the CWxP, DRY, PIF, and NPxxY motifs, consequently predisposing an inclination towards the inactive-like conformation. We also found that the EF led to an overall increase in the dipole moment of 5-HT1AR, encompassing TM6 and pivotal amino acids. The analyses of conformational properties of TM6 showed that the changed secondary structure and decreased solvent exposure occurred upon the EF condition. The interaction of 5-HT1AR with the membrane lipid bilayer was also altered under the EF. Our findings reveal the molecular mechanism underlying the transition of 5-HT1AR conformation induced by external EFs, which offer potential novel insights into the prospect of employing structure-based EF applications for GPCRs.
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