等温滴定量热法
费斯特共振能量转移
生物
连接器
生物物理学
跨膜结构域
配体(生物化学)
单分子微动
ATP结合盒运输机
跨膜蛋白
构象变化
生物化学
蛋白质结构
转运蛋白
血浆蛋白结合
运输机
氨基酸
荧光
物理
受体
量子力学
计算机科学
基因
操作系统
作者
Evelyn Ploetz,Gea K. Schuurman‐Wolters,Niels Zijlstra,Amarins W. Jager,Douglas A. Griffith,Albert Guskov,Giorgos Gouridis,Bert Poolman,Thorben Cordes
出处
期刊:Open Biology
[Royal Society]
日期:2021-04-01
卷期号:11 (4)
被引量:11
摘要
The ATP-binding cassette transporter GlnPQ is an essential uptake system that transports glutamine, glutamic acid and asparagine in Gram-positive bacteria. It features two extra-cytoplasmic substrate-binding domains (SBDs) that are linked in tandem to the transmembrane domain of the transporter. The two SBDs differ in their ligand specificities, binding affinities and their distance to the transmembrane domain. Here, we elucidate the effects of the tandem arrangement of the domains on the biochemical, biophysical and structural properties of the protein. For this, we determined the crystal structure of the ligand-free tandem SBD1-2 protein from Lactococcus lactis in the absence of the transporter and compared the tandem to the isolated SBDs. We also used isothermal titration calorimetry to determine the ligand-binding affinity of the SBDs and single-molecule Förster resonance energy transfer (smFRET) to relate ligand binding to conformational changes in each of the domains of the tandem. We show that substrate binding and conformational changes are not notably affected by the presence of the adjoining domain in the wild-type protein, and changes only occur when the linker between the domains is shortened. In a proof-of-concept experiment, we combine smFRET with protein-induced fluorescence enhancement (PIFE–FRET) and show that a decrease in SBD linker length is observed as a linear increase in donor-brightness for SBD2 while we can still monitor the conformational states (open/closed) of SBD1. These results demonstrate the feasibility of PIFE–FRET to monitor protein–protein interactions and conformational states simultaneously.
科研通智能强力驱动
Strongly Powered by AbleSci AI