蛋白質結構對於維持其功能是互相影響的，但在特定條件下，蛋白質會產生變性，進而誘發一些疾病，因此研究蛋白質早期變性的過程是非常重要的，本篇研究，利用低濃度的尿素(Urea)使泛素(Ubiquitin) 結構不穩定，產生早期展開之結構，之後我們使用一系列NMR光譜技術去研究蛋白質在早期展開狀態中的蛋白質骨幹動態。
首先，分析T1, T2,弛豫以及NOE數值之測量，將其測量結果套用至無模型分析(ModelFree method)方法，結果顯示發現泛素(Ubiquitin)在早期展開條件之下，特定區域的S2 (Order Parameter) 數值下降，顯示區域性的動態增加，同時構型交換(Rex)也在更多的胺基酸被偵測到，同時我們也利用新型NMR光譜技術，場循環核磁共振(Field cycling NMR)，去測量從磁場範圍20 Telsa (850 Hz)~1 Telsa (42.5 Hz)中個別骨幹的縱向弛豫 (T1)，結果反應出內分子運動的時間尺度，而此結果與T1, T2, NOE弛豫之測量與無模型方法(ModelFree method)互補，可以提供更精準的測量。接著我們也做了泛素(Ubiquitin)在早期展開條件之下，二級結構預測以及氫鍵實驗，其結果顯示結構並無太大改變。
總結上述，藉由NMR技術搭配場循環核磁共振(Field cycling NMR)技術可以精準反映內分子運動的尺度，提供蛋白質早期展開時，更完整的結構以及動態描述。

The protein unfolding is highly related with the maintenance of protein structures and functions in certain content. Therefore, to study protein early-stage unfolding process would be critical in understanding the diseases induced by protein unfolding. Here, low Urea concentration (< 1.5 M) is used to destabilize Ubiquitin and derive a structure representing the early-unfolding state. We used a series of NMR methods to detect protein backbone dynamics at the early-unfolding state.
In the first examination, we measured T1, T2, NOE of individual residues and employed ModelFree method to analyze the dynamic parameters. Low concentration Urea led reduced S2 and increased number of residues with conformational exchange (Rex). Meanwhile, we also use a modern field-cycling NMR (FCNMR) method to detect the longitudinal relaxation rates (T1) of the individual Ubiquitin backbone amides under the magnetic field strengths from 20 Telsa (850 MHz) to ~1 Telsa (42.5 MHz). The field-dependent relaxations precisely reported backbone internal motion with wider time scale (nanosecond to picosecond). The result well corresponded the result derived from T1, T2, NOE measurements and ModelFree analysis. We also performed secondary structure prediction and hydrogen bond detection by NMR and the results showed less significant change in structure.
In summary, NMR approaches including FCNMR technology could report a wider range of time-scale for molecular dynamics, providing a more complete insight and dynamic description for studying protein early-stage unfolding process.

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