Engineering Encodable Lanthanide-Binding Tags into Loop Regions of Proteins

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• 作者：Katja Barthelmes ; Anne M. Reynolds ; Ezra Peisach ; Hendrik R. A. Jonker ; Nicholas J. DeNunzio ; Karen N. Allen ; Barbara Imperiali ; Harald Schwalbe
• 刊名：Journal of the American Chemical Society
• 出版年：2011
• 出版时间：February 2, 2011
• 年：2011
• 卷：133
• 期：4
• 页码：808-819
• 全文大小：1312K
• 年卷期：v.133,no.4(February 2, 2011)
• ISSN：1520-5126

文摘

Lanthanide-binding tags (LBTs) are valuable tools for investigation of protein structure, function, and dynamics by NMR spectroscopy, X-ray crystallography, and luminescence studies. We have inserted LBTs into three different loop positions (denoted L, R, and S) of the model protein interleukin-1尾 (IL1尾) and varied the length of the spacer between the LBT and the protein (denoted 1鈭?). Luminescence studies demonstrate that all nine constructs bind Tb³⁺ tightly in the low nanomolar range. No significant change in the fusion protein occurs from insertion of the LBT, as shown by two X-ray crystallographic structures of the IL1尾-S1 and IL1尾-L3 constructs and for the remaining constructs by comparing the ¹H鈭?sup>15N heteronuclear single-quantum coherence NMR spectra with that of the wild-type IL1尾. Additionally, binding of LBT-loop IL1尾 proteins to their native binding partner in vitro remains unaltered. X-ray crystallographic phasing was successful using only the signal from the bound lanthanide. Large residual dipolar couplings (RDCs) could be determined by NMR spectroscopy for all LBT-loop constructs and revealed that the LBT-2 series were rigidly incorporated into the interleukin-1尾 structure. The paramagnetic NMR spectra of loop-LBT mutant IL1尾-R2 were assigned and the 螖蠂 tensor components were calculated on the basis of RDCs and pseudocontact shifts. A structural model of the IL1尾-R2 construct was calculated using the paramagnetic restraints. The current data provide support that encodable LBTs serve as versatile biophysical tags when inserted into loop regions of proteins of known structure or predicted via homology modeling.