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蛋白质二级结构含量与平均化学位移之间的经验相关性。

An empirical correlation between secondary structure content and averaged chemical shifts in proteins.

作者信息

Sibley Anaika B, Cosman Monique, Krishnan V V

机构信息

Molecular Biophysics Group, L-448 Biology and Biotechnology Research Program, Lawrence Livermore National Laboratory, Livermore, California 94551, USA.

出版信息

Biophys J. 2003 Feb;84(2 Pt 1):1223-7. doi: 10.1016/S0006-3495(03)74937-6.

Abstract

It is shown that the averaged chemical shift (ACS) of a particular nucleus in the protein backbone empirically correlates well to its secondary structure content (SSC). Chemical shift values of more than 200 proteins obtained from the Biological Magnetic Resonance Bank are used to calculate ACS values, and the SSC is estimated from the corresponding three-dimensional coordinates obtained from the Protein Data Bank. ACS values of (1)H(alpha) show the highest correlation to helical and sheet structure content (correlation coefficient of 0.80 and 0.75, respectively); (1)H(N) exhibits less reliability (0.65 for both sheet and helix), whereas such correlations are poor for the heteronuclei. SSC estimated using this correlation shows a good agreement with the conventional chemical shift index-based approach for a set of proteins that only have chemical shift information but no NMR or x-ray determined three-dimensional structure. These results suggest that even chemical shifts averaged over the entire protein retain significant information about the secondary structure. Thus, the correlation between ACS and SSC can be used to estimate secondary structure content and to monitor large-scale secondary structural changes in protein, as in folding studies.

摘要

研究表明,蛋白质主链中特定原子核的平均化学位移(ACS)与其二级结构含量(SSC)在经验上具有良好的相关性。从生物磁共振数据库获得的200多种蛋白质的化学位移值用于计算ACS值,而SSC则根据从蛋白质数据库获得的相应三维坐标进行估算。(1)H(α)的ACS值与螺旋结构和片状结构含量的相关性最高(相关系数分别为0.80和0.75);(1)H(N)的可靠性较低(片状和螺旋结构的相关系数均为0.65),而异核的此类相关性较差。对于一组仅具有化学位移信息但没有NMR或X射线确定的三维结构的蛋白质,使用这种相关性估算的SSC与基于传统化学位移指数的方法显示出良好的一致性。这些结果表明,即使是整个蛋白质上平均的化学位移也保留了有关二级结构的重要信息。因此,ACS与SSC之间的相关性可用于估算二级结构含量,并监测蛋白质中的大规模二级结构变化,如在折叠研究中。

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