Data_Sheet_1_Post-translational Modification Crosstalk and Hotspots in Sirtuin Interactors Implicated in Cardiovascular Diseases.xlsx

Sirtuins are protein deacetylases that play a protective role in cardiovascular diseases (CVDs), as well as many other diseases. Absence of sirtuins can lead to hyperacetylation of both nuclear and mitochondrial proteins leading to metabolic dysregulation. The protein post-translational modifications (PTMs) are known to crosstalk among each other to bring about complex phenotypic outcomes. Various PTM types such as acetylation, ubiquitination, and phosphorylation, and so on, drive transcriptional regulation and metabolism, but such crosstalks are poorly understood. We integrated protein–protein interactions (PPI) and PTMs from several databases to integrate information on 1,251 sirtuin-interacting proteins, of which 544 are associated with cardiac diseases. Based on the ∼100,000 PTM sites obtained for sirtuin interactors, we observed that the frequency of PTM sites (83 per protein), as well as PTM types (five per protein), is higher than the global average for human proteome. We found that ∼60–70% PTM sites fall into ordered regions. Approximately 83% of the sirtuin interactors contained at least one competitive crosstalk (in situ) site, with half of the sites occurring in CVD-associated proteins. A large proportion of identified crosstalk sites were observed for acetylation and ubiquitination competition. We identified 614 proteins containing PTM hotspots (≥5 PTM sites) and 133 proteins containing crosstalk hotspots (≥3 crosstalk sites). We observed that a large proportion of disease-associated sequence variants were found in PTM motifs of CVD proteins. We identified seven proteins (TP53, LMNA, MAPT, ATP2A2, NCL, APEX1, and HIST1H3A) containing disease-associated variants in PTM and crosstalk hotspots. This is the first comprehensive bioinformatics analysis on sirtuin interactors with respect to PTMs and their crosstalks. This study forms a platform for generating interesting hypotheses that can be tested for a deeper mechanistic understanding gained or derived from big-data analytics.

缢蛇蛋白作为一种蛋白质去乙酰化酶，在心血管疾病（CVDs）及其他多种疾病中扮演着保护性角色。缢蛇蛋白的缺失可能导致细胞核和线粒体蛋白的过度乙酰化，进而引发代谢失调。蛋白质翻译后修饰（PTMs）之间的相互作用已知可以导致复杂的表型结果。诸如乙酰化、泛素化和磷酸化等多种PTM类型驱动转录调控和代谢过程，然而，这种相互作用机制尚不明确。我们整合了来自多个数据库的蛋白质-蛋白质相互作用（PPI）和PTMs信息，涵盖了1,251种与缢蛇蛋白相互作用的蛋白质，其中544种与心脏病相关。基于对缢蛇蛋白相互作用蛋白所获得的约10万个PTM位点，我们发现PTM位点的频率（每蛋白83个）以及PTM类型（每蛋白5种）均高于人类蛋白质组全球平均水平。我们发现约60-70%的PTM位点位于有序区域。大约83%的缢蛇蛋白相互作用蛋白至少包含一个竞争性交叉对话（原位）位点，其中一半位于与心血管疾病相关的蛋白中。大量已识别的交叉对话位点与乙酰化和泛素化竞争相关。我们鉴定出含有PTM热点（≥5个PTM位点）的614种蛋白质和含有交叉对话热点（≥3个交叉对话位点）的133种蛋白质。我们观察到大量与疾病相关的序列变异出现在心血管蛋白的PTM基序中。我们鉴定出含有PTM和交叉对话热点中疾病相关变异的7种蛋白质（TP53、LMNA、MAPT、ATP2A2、NCL、APEX1和HIST1H3A）。这是首次关于缢蛇蛋白相互作用蛋白及其PTMs和交叉对话的全面生物信息学分析。本研究为生成有趣假设并可通过大数据分析验证以获得或推导出更深层次的机制理解提供了一个平台。