five

Modeling stereospecific drug interactions with beta-adrenergic receptor

收藏
NIAID Data Ecosystem2026-05-02 收录
下载链接:
http://datadryad.org/dataset/doi%253A10.5061%252Fdryad.w0vt4b91z
下载链接
链接失效反馈
官方服务:
资源简介:
Beta-adrenergic receptors (βARs) are G protein-coupled receptors that regulate processes such as heart rhythm and vascular tone by binding agonists like norepinephrine, inducing downstream signaling pathways. Beta blockers antagonize βARs, reducing heart rate and lowering vascular tone. We developed a new Rosetta structural modeling protocol to create state-specific models of β1AR and investigated its atomistic-scale interactions with beta-blocker stereoisomers: d- and l-sotalol, as well as R- and S-propranolol. Our combined molecular dynamics (MD) simulations and docking protocol effectively captured the differences in stereoisomer specificity in binding to β1AR. Binding energetics results favored l-sotalol and S-propranolol, consistent with experimental findings showing d-sotalol has significantly lower affinity for beta-adrenergic receptors than l-sotalol. The entropy term was identified as the primary factor driving enantiomer binding specificity, with higher entropy costs for d-sotalol and R-propranolol due to their unfavorable chiral structures. Simulations demonstrated that subtle differences in enantiomers lead to distinct β1AR conformations, with d and R enantiomers causing larger structural changes than l and S enantiomers. Specifically, sotalol affects ICL2 and propranolol affects ICL1. The distance between TM4 and TM6 also exhibited different distributions among enantiomers, indicating varying strengths in stabilizing specific GPCR states. The outer vestibule of the receptor may play a crucial role in the stereoselectivity of small drugs, evidenced by fewer contacts between d-sotalol and ECL2 residues compared to l-sotalol. This study provides a foundation for understanding the stereospecificity of beta blockers for βARs, which are important pharmacological targets, and could be extended to other drug classes and receptor types. Methods The input files for structure modeling and MD simulations, output files, and MD simulation trajectories were collected and presented.
创建时间:
2025-04-21
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作