Network analysis of circular permutations in multidomain proteins reveals functional linkages for uncharacterized proteins.
Network analysis of circular permutations in multidomain proteins reveals functional linkages for uncharacterized proteins.
复制标题
多域蛋白质循环排列的网络分析揭示了未表征蛋白质的功能联系
作者：
Adjeroh D;Jiang Y;Jiang BH;Lin J
不同的研究表明不同的多结构域蛋白与癌症有关。然而，关于环状多结构域蛋白在一般癌症问题或特定癌症类型中的作用的详细研究很少或根本没有。这项工作代表了一种初步的尝试，主要是基于循环排列(CP)关系来研究已知癌症相关蛋白与未表征或假想的多域蛋白之间的联系的可能性。首先，我们提出了一种快速识别多结构域蛋白质中精确和近似CP的有效算法。利用识别出的循环关系，我们构建了多结构域蛋白质之间的网络，并在此基础上对多结构域蛋白质进行了功能标注。然后，我们将该方法扩展到为选定的癌症亚型构建子网络，并对未表征的多结构域蛋白与选定的癌症类型之间的潜在链接年龄进行预测。我们给出的实际结果显示了所提出的方法的性能。
Various studies have implicated different multidomain proteins in cancer. However, there has been little or no detailed study on the role of circular multidomain proteins in the general problem of cancer or on specific cancer types. This work represents an initial attempt at investigating the potential for predicting linkages between known cancer-associated proteins with uncharacterized or hypothetical multidomain proteins, based primarily on circular permutation (CP) relationships. First, we propose an efficient algorithm for rapid identification of both exact and approximate CPs in multidomain proteins. Using the circular relations identified, we construct networks between multidomain proteins, based on which we perform functional annotation of multidomain proteins. We then extend the method to construct subnetworks for selected cancer subtypes, and performed prediction of potential link-ages between uncharacterized multidomain proteins and the selected cancer types. We include practical results showing the performance of the proposed methods.