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SH3 Domain-Peptide Binding Energy Calculations Based on Structural Ensemble and Multiple Peptide Templates

机译:基于结构整合和多肽模板的SH3域-肽结合能计算

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摘要

SH3 domains mediate signal transduction by recognizing short peptides. Understanding of the driving forces in peptide recognitions will help us to predict the binding specificity of the domain-peptide recognition and to understand the molecular interaction networks of cells. However, accurate calculation of the binding energy is a tough challenge. In this study, we propose three ideas for improving our ability to predict the binding energy between SH3 domains and peptides: (1) utilizing the structural ensembles sampled from a molecular dynamics simulation trajectory, (2) utilizing multiple peptide templates, and (3) optimizing the sequence-structure mapping. We tested these three ideas on ten previously studied SH3 domains for which SPOT analysis data were available. The results indicate that calculating binding energy using the structural ensemble was most effective, clearly increasing the prediction accuracy, while the second and third ideas tended to give better binding energy predictions. We applied our method to the five SH3 targets in DREAM4 Challenge and selected the best performing method.
机译:SH3结构域通过识别短肽来介导信号转导。了解肽识别中的驱动力将有助于我们预测域肽识别的结合特异性,并了解细胞的分子相互作用网络。然而,精确计算结合能是一个艰巨的挑战。在这项研究中,我们提出了三个想法,以提高我们预测SH3域与肽之间的结合能的能力:(1)利用从分子动力学模拟轨迹中采样的结构体,(2)利用多个肽模板,以及(3)优化序列结构映射。我们在十个以前研究过的SH3域中测试了这三个想法,这些域可以使用SPOT分析数据。结果表明,使用结构合奏计算结合能最有效,明显提高了预测准确性,而第二和第三种方法倾向于提供更好的结合能预测。我们将我们的方法应用于DREAM4 Challenge中的五个SH3目标,并选择了效果最好的方法。

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