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核磁共振结构测定和模型驱动的序列归属中的直接方法及残基类型特异性同位素标记。

Direct methods and residue type specific isotope labeling in NMR structure determination and model-driven sequential assignment.

作者信息

Schedlbauer Andreas, Auer Renate, Ledolter Karin, Tollinger Martin, Kloiber Karin, Lichtenecker Roman, Ruedisser Simon, Hommel Ulrich, Schmid Walther, Konrat Robert, Kontaxis Georg

机构信息

Institute of Biomolecular Structural Chemistry, Max F. Perutz Laboratories, University of Vienna, Campus Vienna Biocenter 5/1, Vienna, Austria.

出版信息

J Biomol NMR. 2008 Oct;42(2):111-27. doi: 10.1007/s10858-008-9268-9. Epub 2008 Sep 2.

Abstract

Direct methods in NMR based structure determination start from an unassigned ensemble of unconnected gaseous hydrogen atoms. Under favorable conditions they can produce low resolution structures of proteins. Usually a prohibitively large number of NOEs is required, to solve a protein structure ab-initio, but even with a much smaller set of distance restraints low resolution models can be obtained which resemble a protein fold. One problem is that at such low resolution and in the absence of a force field it is impossible to distinguish the correct protein fold from its mirror image. In a hybrid approach these ambiguous models have the potential to aid in the process of sequential backbone chemical shift assignment when (13)C(beta) and (13)C' shifts are not available for sensitivity reasons. Regardless of the overall fold they enhance the information content of the NOE spectra. These, combined with residue specific labeling and minimal triple-resonance data using (13)C(alpha) connectivity can provide almost complete sequential assignment. Strategies for residue type specific labeling with customized isotope labeling patterns are of great advantage in this context. Furthermore, this approach is to some extent error-tolerant with respect to data incompleteness, limited precision of the peak picking, and structural errors caused by misassignment of NOEs.

摘要

基于核磁共振的结构测定中的直接方法始于一组未连接的气态氢原子的未分配集合。在有利条件下,它们可以产生蛋白质的低分辨率结构。通常,从头开始解析蛋白质结构需要数量多到令人望而却步的核Overhauser效应(NOE),但即使使用数量少得多的距离约束集,也可以获得类似于蛋白质折叠的低分辨率模型。一个问题是,在如此低的分辨率下且没有力场时,无法将正确的蛋白质折叠与其镜像区分开来。在一种混合方法中,当由于灵敏度原因无法获得(13)C(β)和(13)C′化学位移时,这些模糊模型有可能有助于进行连续主链化学位移归属。无论整体折叠如何,它们都能增加NOE谱的信息含量。这些与残基特异性标记以及使用(13)C(α)连接性的最少三共振数据相结合,可以提供几乎完整的连续归属。在这种情况下,采用定制同位素标记模式进行残基类型特异性标记的策略具有很大优势。此外,这种方法在一定程度上对数据不完整、峰挑选精度有限以及由NOE误归属导致的结构错误具有容错能力。

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