Department of Biotechnology, College of Life Science and Biotechnology, Yonsei University, Seoul, Korea.
Yonsei Biomedical Research Institute, Yonsei University College of Medicine, Seoul, Korea.
PLoS Comput Biol. 2019 May 10;15(5):e1007052. doi: 10.1371/journal.pcbi.1007052. eCollection 2019 May.
Protein domains are basic functional units of proteins. Many protein domains are pervasive among diverse biological processes, yet some are associated with specific pathways. Human complex diseases are generally viewed as pathway-level disorders. Therefore, we hypothesized that pathway-specific domains could be highly informative for human diseases. To test the hypothesis, we developed a network-based scoring scheme to quantify specificity of domain-pathway associations. We first generated domain profiles for human proteins, then constructed a co-pathway protein network based on the associations between domain profiles. Based on the score, we classified human protein domains into pathway-specific domains (PSDs) and non-specific domains (NSDs). We found that PSDs contained more pathogenic variants than NSDs. PSDs were also enriched for disease-associated mutations that disrupt protein-protein interactions (PPIs) and tend to have a moderate number of domain interactions. These results suggest that mutations in PSDs are likely to disrupt within-pathway PPIs, resulting in functional failure of pathways. Finally, we demonstrated the prediction capacity of PSDs for disease-associated genes with experimental validations in zebrafish. Taken together, the network-based quantitative method of modeling domain-pathway associations presented herein suggested underlying mechanisms of how protein domains associated with specific pathways influence mutational impacts on diseases via perturbations in within-pathway PPIs, and provided a novel genomic feature for interpreting genetic variants to facilitate the discovery of human disease genes.
蛋白质结构域是蛋白质的基本功能单元。许多蛋白质结构域普遍存在于各种生物过程中，但也有一些与特定途径相关。人类复杂疾病通常被视为途径水平的疾病。因此，我们假设途径特异性结构域可能对人类疾病具有高度信息性。为了验证这一假设，我们开发了一种基于网络的评分方案，用于量化结构域-途径关联的特异性。我们首先为人类蛋白质生成结构域谱，然后基于结构域谱之间的关联构建共途径蛋白质网络。根据得分，我们将人类蛋白质结构域分为途径特异性结构域（PSD）和非特异性结构域（NSD）。我们发现 PSD 包含的致病性变体比 NSD 多。PSD 还富集了破坏蛋白质-蛋白质相互作用（PPIs）的疾病相关突变，并且倾向于具有中等数量的结构域相互作用。这些结果表明，PSD 中的突变很可能破坏途径内的 PPIs，导致途径功能失效。最后，我们通过在斑马鱼中的实验验证证明了 PSD 对疾病相关基因的预测能力。综上所述，本文提出的基于网络的定量方法建模结构域-途径关联，提出了蛋白质结构域与特定途径相关如何通过干扰途径内的 PPI 影响疾病的突变影响的潜在机制，并为解释遗传变异提供了一种新的基因组特征，有助于发现人类疾病基因。
