Improve the Prediction of RNA-Binding Residues Using Structural Neighbours
Improve the Prediction of RNA-Binding Residues Using Structural Neighbours
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DOI：
10.2174/092986610790780279
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发表时间：
2010-03-01
影响因子：
1.6
通讯作者：
Liu, Haiyan
中科院分区：
文献类型：
--
作者：
Li, Quan;Cao, Zanxia;Liu, Haiyan
RNA 结合蛋白 (RBP) 与 RNA 之间的相互作用在管理细胞的一些基本功能中发挥着关键作用。 RNA 结合位点的识别和预测对于理解 RNA 结合机制非常重要。人们正在开发计算方法来根据序列或结构衍生的特征来预测 RNA 结合残基。为了获得更高的预测精度，有必要对现有的预测方法进行改进。我们发现RNA结合残基和非RNA结合残基的结构邻居具有不同的氨基酸组成。将这种结构衍生的特征与进化（PSSM）和其他结构信息（二级结构和溶剂可及性）相结合，可以显着改善现有方法的预测。使用多元线性回归方法和 6 倍交叉验证，我们的最佳模型可以实现 87.8% 的总体正确率和 0.47 的 MCC，特异性为 93.4%，正确预测包含 107 个非同源 RNA 结合蛋白的数据集的 52.4% 的 RNA 结合残基。与现有方法相比，包括结构邻居的氨基酸组成导致明显的改进。开发了一个网络服务器来预测蛋白质序列（或结构）中的 RNA 结合残基，可从 http://jeele.go.3322.org/RNA/ 获取。
The interactions between RNA-binding proteins (RBPs) with RNA play key roles in managing some of the cell's basic functions. The identification and prediction of RNA binding sites is important for understanding the RNA-binding mechanism. Computational approaches are being developed to predict RNA-binding residues based on the sequence-or structure-derived features. To achieve higher prediction accuracy, improvements on current prediction methods are necessary. We identified that the structural neighbors of RNA-binding and non-RNA-binding residues have different amino acid compositions. Combining this structure-derived feature with evolutionary (PSSM) and other structural information (secondary structure and solvent accessibility) significantly improves the predictions over existing methods. Using a multiple linear regression approach and 6-fold cross validation, our best model can achieve an overall correct rate of 87.8% and MCC of 0.47, with a specificity of 93.4%, correctly predict 52.4% of the RNA-binding residues for a dataset containing 107 non-homologous RNA- binding proteins. Compared with existing methods, including the amino acid compositions of structure neighbors lead to clearly improvement. A web server was developed for predicting RNA binding residues in a protein sequence (or structure), which is available at http://jeele.go.3322.org/RNA/.