Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins

Highly accurate sequence-based prediction of half-sphere exposures of amino acid residues in proteins
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基于序列的高精度蛋白质氨基酸残基半球暴露预测

DOI：
10.1093/bioinformatics/btv665
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发表时间：
2016-03-15
期刊：
BIOINFORMATICS
影响因子：
5.8
通讯作者：
Yang, Yuedong
Yang, Yuedong
中科院分区：
生物学3区
文献类型：
--
作者：
Heffernan, Rhys;Dehzangi, Abdollah;Yang, Yuedong

文献摘要

被引文献

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动机 蛋白质氨基酸残基的溶剂暴露对于理解和预测蛋白质的结构、功能和相互作用具有重要作用。溶剂暴露可以通过几种测量来表征，包括溶剂可及表面积（阿萨）、残留深度（RD）和接触数（CN）。最近，通过分离根据Cα-Cβ（HSEβ）向量或相邻Cα-Cα向量（HSEα）定义的上半球和下半球内的接触，引入了称为半球暴露（HSE）的与方向相关的接触数。从蛋白质结构计算的HSEα被发现在许多应用中比阿萨、CN和RD更好地描述溶剂暴露。因此，基于序列的预测是可取的，因为大多数蛋白质不具有实验确定的结构。据我们所知，没有预测HSEα的方法，只有一种预测HSEβ的方法。 结果 该研究开发了一种新的方法来预测HSEα和HSEβ（SPIDER-HSE），该方法在10倍交叉验证和两个独立测试中实现了一致的性能。对于1199个蛋白质的独立测试集，预测的HSEβ与测量的HSEβ之间的相关系数（上球体为0.73，下球体为0.69，接触数为0.76）显著高于现有方法。此外，预测的HSEα与残基突变引起的稳定性变化的相关系数（0.46）高于预测的HSEβ（0.37）和阿萨（0.43）。结果，连同其简单的基于Cα原子的计算，突出了预测的HSEα蛋白质结构预测和改进以及功能预测的潜在有用性。 可用性和执行 该方法可在http://sparks-lab.org上获得 接触 yuedong. griffith.edu.au或yaoqi. griffith.edu.au 补充资料 补充数据可在Bioinformatics在线获得。
MOTIVATION Solvent exposure of amino acid residues of proteins plays an important role in understanding and predicting protein structure, function and interactions. Solvent exposure can be characterized by several measures including solvent accessible surface area (ASA), residue depth (RD) and contact numbers (CN). More recently, an orientation-dependent contact number called half-sphere exposure (HSE) was introduced by separating the contacts within upper and down half spheres defined according to the Cα-Cβ (HSEβ) vector or neighboring Cα-Cα vectors (HSEα). HSEα calculated from protein structures was found to better describe the solvent exposure over ASA, CN and RD in many applications. Thus, a sequence-based prediction is desirable, as most proteins do not have experimentally determined structures. To our best knowledge, there is no method to predict HSEα and only one method to predict HSEβ. RESULTS This study developed a novel method for predicting both HSEα and HSEβ (SPIDER-HSE) that achieved a consistent performance for 10-fold cross validation and two independent tests. The correlation coefficients between predicted and measured HSEβ (0.73 for upper sphere, 0.69 for down sphere and 0.76 for contact numbers) for the independent test set of 1199 proteins are significantly higher than existing methods. Moreover, predicted HSEα has a higher correlation coefficient (0.46) to the stability change by residue mutants than predicted HSEβ (0.37) and ASA (0.43). The results, together with its easy Cα-atom-based calculation, highlight the potential usefulness of predicted HSEα for protein structure prediction and refinement as well as function prediction. AVAILABILITY AND IMPLEMENTATION The method is available at http://sparks-lab.org CONTACT yuedong.yang@griffith.edu.au or yaoqi.zhou@griffith.edu.au SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.