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Toward The Recognition Code Of Protein-DNA Recognition

机译:朝向蛋白质-DNA识别识别码

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Discovering the "recognition code" governing protein-DNA interaction has been an important topic for decades in bioinformatics. While other studies have focused on analyzing the frequency of amino acid-base contacts, this study here attempts to discover the structural and physkochemical features of proteins that determine the specificity of amino acid-base contacts. For each amino acid that contacts with DNA, we attempt to predict the type of bases (purines or pyrimidines) that it contacts. We extract 8 structural and physicochemical features from proteins and use a bottom-up approach to search for the combination of features that can be used to predict the specificity of amino acid-base contacts. In the end, 4 features are selected. Using these features, a support vector machine method can achieve 67.1% accuracy with 0.329 MCC in predicting the type of base (purines or pyrimidines) that an amino acid contacts. Analyzing the selected features will provide insights into the "recognition code" of protein-DNA interaction
机译:发现“识别码”治疗蛋白质DNA互动一直是生物信息学的几十年的重要课题。虽然其他研究的重点是分析氨基酸基触点的频率,但本研究目前试图发现蛋白质的结构和物理化学特征,其确定氨基酸基触点的特异性。对于与DNA接触的每种氨基酸,我们试图预测它与其接触的碱(嘌呤或嘧啶)的类型。我们从蛋白质中提取8个结构和物理化学特征,并使用自下而上的方法来搜索可用于预测氨基酸基触点的特异性的特征的组合。最终,选择了4个功能。使用这些特征,支持向量机方法可以在预测氨基酸接触的基础(嘌呤或嘧啶)的类型中,实现67.1%的精度。分析所选功能将提供进入蛋白质DNA相互作用的“识别码”的见解

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