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Network pattern of residue packing in helical membrane proteins and its application in membrane protein structure prediction.

机译:螺旋膜蛋白残基堆积的网络模式及其在膜蛋白结构预测中的应用。

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摘要

De novo protein structure prediction plays an important role in studies of helical membrane proteins as well as structure-based drug design efforts. Developing an accurate scoring function for protein structure discrimination and validation remains a current challenge. Network approaches based on overall network patterns of residue packing have proven useful in soluble protein structure discrimination. It is thus of interest to apply similar approaches to the studies of residue packing in membrane proteins. In this work, we first carried out such analysis on a set of diverse, non-redundant and high-resolution membrane protein structures. Next, we applied the same approach to three test sets. The first set includes nine structures of membrane proteins with the resolution worse than 2.5 A; the other two sets include a total of 101 G-protein coupled receptor models, constructed using either de novo or homology modeling techniques. Results of analyses indicate the two criteria derived from studying high-resolution membrane protein structures are good indicators of a high-quality native fold and the approach is very effective for discriminating native membrane protein folds from less-native ones. These findings should be of help for the investigation of the fundamental problem of membrane protein structure prediction.
机译:从头蛋白质结构预测在螺旋膜蛋白质研究以及基于结构的药物设计工作中起着重要作用。开发准确的评分功能以识别和验证蛋白质结构仍然是当前的挑战。已证明基于残渣堆积的整体网络模式的网络方法可用于可溶性蛋白质结构的判别。因此,有兴趣将类似方法应用于膜蛋白中残基堆积的研究。在这项工作中,我们首先对一组多样化,非冗余和高分辨率的膜蛋白结构进行了此类分析。接下来,我们将相同的方法应用于三个测试集。第一组包括九个膜蛋白结构,分辨率低于2.5 A;其他两组包括使用从头或同源性建模技术构建的总共101个G蛋白偶联受体模型。分析结果表明,从研究高分辨率膜蛋白结构中得出的两个标准是高质量天然折叠的良好指标,该方法对于区分天然膜蛋白折叠与非天然折叠非常有效。这些发现应有助于调查膜蛋白结构预测的基本问题。

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