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解决结构蛋白质组学中的内在无序瓶颈问题。

Addressing the intrinsic disorder bottleneck in structural proteomics.

作者信息

Oldfield Christopher J, Ulrich Eldon L, Cheng Yugong, Dunker A Keith, Markley John L

机构信息

Center for Eukaryotic Structural Genomics, Biochemistry Department, University of Wisconsin, Madison, Wisconsin 53706, USA.

出版信息

Proteins. 2005 May 15;59(3):444-53. doi: 10.1002/prot.20446.

Abstract

The Center for Eukaryotic Structural Genomics (CESG), as part of the Protein Structure Initiative (PSI), has established a high-throughput structure determination pipeline focused on eukaryotic proteins. NMR spectroscopy is an integral part of this pipeline, both as a method for structure determinations and as a means for screening proteins for stable structure. Because computational approaches have estimated that many eukaryotic proteins are highly disordered, about 1 year into the project, CESG began to use an algorithm (the Predictor of Naturally Disordered Regions, PONDR to avoid proteins that were likely to be disordered. We report a retrospective analysis of the effect of this filtering on the yield of viable structure determination candidates. In addition, we have used our current database of results on 70 protein targets from Arabidopsis thaliana and 1 from Caenorhabditis elegans, which were labeled uniformly with nitrogen-15 and screened for disorder by NMR spectroscopy, to compare the original algorithm with 13 other approaches for predicting disorder from sequence. Our study indicates that the efficiency of structural proteomics of eukaryotes can be improved significantly by removing targets predicted to be disordered by an algorithm chosen to provide optimal performance.

摘要

作为蛋白质结构计划(PSI)的一部分,真核生物结构基因组学中心(CESG)建立了一个专注于真核生物蛋白质的高通量结构测定流程。核磁共振波谱法是该流程不可或缺的一部分,既是一种结构测定方法,也是一种筛选具有稳定结构蛋白质的手段。由于计算方法估计许多真核生物蛋白质高度无序,在项目开展约一年后,CESG开始使用一种算法(天然无序区域预测器,PONDR)来避免使用可能无序的蛋白质。我们报告了对这种筛选对可行结构测定候选物产量影响的回顾性分析。此外,我们利用目前来自拟南芥的70个蛋白质靶点和秀丽隐杆线虫的1个蛋白质靶点的结果数据库,这些靶点均用氮-15均匀标记,并通过核磁共振波谱法筛选无序情况,以将原始算法与其他13种从序列预测无序的方法进行比较。我们的研究表明,通过去除经选择以提供最佳性能的算法预测为无序的靶点,真核生物结构蛋白质组学的效率可显著提高。

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