Liu Zhu, Gong Zhou, Cao Yong, Ding Yue-He, Dong Meng-Qiu, Lu Yun-Bi, Zhang Wei-Ping, Tang Chun
CAS Key Laboratory of Magnetic Resonance in Biological Systems, State Key Laboratory of Magnetic Resonance and Atomic Molecular Physics, and National Center for Magnetic Resonance at Wuhan, Wuhan Institute of Physics and Mathematics of the Chinese Academy of Sciences , Wuhan, Hubei 430071, China.
Department of Pharmacology, Institute of Neuroscience, Key Laboratory of Medical Neurobiology of Ministry of Health of China, and Zhejiang Province Key Laboratory of Mental Disorder's Management, Zhejiang University School of Medicine , Hangzhou, Zhejiang 310058, China.
Biochemistry. 2018 Jan 23;57(3):305-313. doi: 10.1021/acs.biochem.7b00817. Epub 2017 Oct 2.
A protein dynamically samples multiple conformations, and the conformational dynamics enables protein function. Most biophysical measurements are ensemble-based, with the observables averaged over all members of the ensemble. Though attainable, the decomposition of the observables to the constituent conformational states can be computationally expensive and ambiguous. Here we show that the incorporation of single-molecule fluorescence resonance energy transfer (smFRET) data resolves the ambiguity and affords protein ensemble structures that are more precise and accurate. Using K63-linked diubiquitin, we characterize the dynamic domain arrangements of the model system, with the use of chemical cross-linking coupled with mass spectrometry (CXMS), small-angle X-ray scattering (SAXS), and smFRET techniques. CXMS allows the modeling of protein conformational states that are alternatives to the crystal structure. SAXS provides ensemble-averaged low-resolution shape information. Importantly, smFRET affords state-specific populations, and the FRET distances validate the ensemble structures obtained by refining against CXMS and SAXS restraints. Together, the integrative use of bulk and single-molecule techniques affords better insight into protein dynamics and shall be widely implemented in structural biology.
蛋白质会动态地采样多种构象,而构象动力学赋予蛋白质功能。大多数生物物理测量都是基于总体的,观测值是对总体中所有成员进行平均得到的。虽然可以实现,但将观测值分解为组成构象状态在计算上可能代价高昂且具有模糊性。在此我们表明,纳入单分子荧光共振能量转移(smFRET)数据可解决这种模糊性,并提供更精确准确的蛋白质总体结构。使用K63连接的双泛素,我们利用化学交联结合质谱(CXMS)、小角X射线散射(SAXS)和smFRET技术对模型系统的动态结构域排列进行了表征。CXMS允许对作为晶体结构替代物的蛋白质构象状态进行建模。SAXS提供总体平均的低分辨率形状信息。重要的是,smFRET可提供特定状态的丰度,并且FRET距离验证了通过针对CXMS和SAXS限制进行优化而获得的总体结构。总之,综合使用大量和单分子技术能更好地洞察蛋白质动力学,并且应在结构生物学中广泛应用。