Table_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.

沉默调节酶是一类蛋白质去乙酰化酶，在心血管疾病（CVDs）以及其他多种疾病中发挥着保护性作用。沉默调节酶的缺失可能导致细胞核和线粒体蛋白质的过度乙酰化，进而引发代谢失调。蛋白质翻译后修饰（PTMs）之间的相互作用已被证实能够产生复杂的表型结果。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PTM信息，涵盖了1,251种与沉默调节酶相互作用的蛋白质，其中544种与心脏病相关。基于从沉默调节酶相互作用蛋白中获得的约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（每蛋白五种）均高于人类蛋白质组全局平均。我们观察到约60-70%的PTM位点位于有序区域。大约83%的沉默调节酶相互作用蛋白含有至少一个竞争性相互作用（原位）位点，其中一半位于与心血管疾病相关的蛋白中。大量识别的相互作用位点涉及乙酰化和泛素化竞争。我们鉴定出614种含有PTM热点（≥5 PTM位点）的蛋白质和133种含有相互作用热点（≥3相互作用位点）的蛋白质。我们发现，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。我们鉴定出七个含有PTM和相互作用热点疾病相关变异的蛋白质（TP53、LMNA、MAPT、ATP2A2、NCL、APEX1和HIST1H3A）。这是首次对沉默调节酶相互作用蛋白及其PTMs和相互作用进行的全面生物信息学分析。本研究为从大数据分析中获得或推断的更深入机制理解提供了平台。