Effective discrimination between biologically relevant contacts and crystal packing contacts using new determinants

Effective discrimination between biologically relevant contacts and crystal packing contacts using new determinants
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使用新的决定因素有效区分生物相关接触和晶体堆积接触

DOI:
10.1002/prot.24670
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发表时间:
2014-11-01
影响因子:
2.9
通讯作者:
Li, Menglong
Li, Menglong
中科院分区:
生物学4区
文献类型:
--
作者:
Luo, Jiesi;Guo, Yanzhi;Li, Menglong

文献摘要

被引文献

相似文献

在X射线结晶学确定的结构模型中,分子间的接触可分为两类:生物相关接触和晶体堆积接触。随着可利用的大晶体填充接触结构的数量和质量的增长,区分晶体填充接触和生物相关接触仍然是一项困难的任务,这可能导致对结构模型的错误解释。在本研究中,我们对生物相关接触和晶体填充接触进行了系统的分析。分析结果表明,生物接触比晶体填充接触更紧密。生物接触的这种特性可能有助于它们界面核心区的形成。同时,生物接触的核心区和表面区在氨基酸组成和进化度量上的差异比晶体填充接触更显著,这些差异似乎有助于区分这两类接触。基于我们分析得到的特征,我们开发了一个随机森林模型来分类生物相关接触和晶体填充接触。在5次交叉验证中,我们的方法可以获得高达0.923的接收器工作曲线,对于两个不同的测试集,准确率分别为91.4%和91.7%。此外,在比较研究中,我们的模型优于其他现有的方法,如DiMoVo、PITA、PISA和EPPIC。我们相信,这项研究将为低聚蛋白质和蛋白质复合体的验证提供有用的帮助。本文中使用的模型和所有数据都可以在上免费获得。蛋白质2014;82:3090-3100。(C)2014年威利期刊公司。
In the structural models determined by X-ray crystallography, contacts between molecules can be divided into two categories: biologically relevant contacts and crystal packing contacts. With the growth in the number and quality of available large crystal packing contacts structures, distinguishing crystal packing contacts from biologically relevant contacts remains a difficult task, which can lead to wrong interpretation of structural models. In this study, we performed a systematic analysis on the biologically relevant contacts and crystal packing contacts. The analysis results reveal that biologically contacts are more tightly packed than crystal packing contacts. This property of biologically contacts may contribute to the formation of their interfacial core region. Meanwhile, the differences between the core and surface region of biologically contacts in amino acid composition and evolutionary measure are more dramatic than crystal packing contacts and these differences appear to be useful in distinguishing these two categories of contacts. On the basis of the features derived from our analysis, we developed a random forest model to classify biological relevant contacts and crystal packing contacts. Our method can achieve a high receiver operating curve of 0.923 in the 5-fold cross-validation and accuracies of 91.4% and 91.7% for two different test sets. Moreover, in a comparison study, our model outperforms other existing methods, such as DiMoVo, Pita, Pisa, and Eppic. We believe that this study will provide useful help in the validation of oligomeric proteins and protein complexes. The model and all data used in this paper are freely available at . Proteins 2014; 82:3090-3100. (c) 2014 Wiley Periodicals, Inc.