Recently, it has been showed that cancer missense mutations selectively target the neighborhood of hinge residues, which are key sites in protein dynamics. Here, we show that this approach can be extended to find previously unknown candidate mutations and genes. To this aim, we developed a computational pipeline to detect significantly enriched three‐dimensional (3D) clustering of missense mutations around hinge residues. The hinge residues were detected by applying a Gaussian network model. By systematically analyzing the PanCancer compendium of somatic mutations in nearly 10 000 tumors from the Cancer Genome Atlas, we identified candidate genes and mutations in addition to well known ones. For instance, we found significantly enriched 3D clustering of missense mutations in known cancer genes including CDK4, CDKN2A, TCL1A, and MAPK1. Beside these known genes, we also identified significantly enriched 3D clustering of missense mutations around hinge residues in PLA2G4A, which may lead to excessive phosphorylation of the extracellular signal‐regulated kinases. Furthermore, we demonstrated that hinge‐based features improves pathogenicity prediction for missense mutations. Our results show that the consideration of clustering around hinge residues can help us explain the functional role of the mutations in known cancer genes and identify candidate genes.

中文翻译：

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蛋白质动力学分析确定了 TCGA 数据中的候选癌症驱动基因和突变

最近，已经表明癌症错义突变选择性地靶向铰链残基附近，这是蛋白质动力学中的关键位点。在这里，我们展示了这种方法可以扩展到找到以前未知的候选突变和基因。为此，我们开发了一个计算管道来检测铰链残基周围错义突变的显着丰富的三维 (3D) 聚类。通过应用高斯网络模型检测铰链残基。通过系统地分析来自癌症基因组图谱的近 10 000 个肿瘤的体细胞突变的 PanCancer 纲要，除了众所周知的基因和突变外，我们还确定了候选基因和突变。例如，我们发现已知癌症基因（包括 CDK4、CDKN2A、TCL1A 和 MAPK1）中错义突变的 3D 聚类显着丰富。除了这些已知基因之外，我们还发现了 PLA2G4A 中铰链残基周围错义突变的显着丰富的 3D 聚类，这可能导致细胞外信号调节激酶的过度磷酸化。此外，我们证明了基于铰链的特征改善了对错义突变的致病性预测。我们的结果表明，考虑铰链残基周围的聚类可以帮助我们解释已知癌症基因中突变的功能作用并确定候选基因。