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In silico-prediction of protein–protein interactions network about MAPKs and PP2Cs reveals a novel docking site variants in Brachypodium distachyon

机译:对MAPKs和PP2Cs的蛋白质-蛋白质相互作用网络进行计算机模拟预测揭示了Brachypodium distachyon中一个新的停靠位点变体

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摘要

Protein-protein interactions (PPIs) underlie the molecular mechanisms of most biological processes. Mitogen-activated protein kinases (MAPKs) can be dephosphorylated by MAPK-specific phosphatases such as PP2C, which are critical to transduce extracellular signals into adaptive and programmed responses. However, the experimental approaches for identifying PPIs are expensive, time-consuming, laborious and challenging. In response, many computational methods have been developed to predict PPIs. Yet, these methods have inherent disadvantages such as high false positive and negative results. Thus, it is crucial to develop in silico approaches for predicting PPIs efficiently and accurately. In this study, we identified PPIs among 16 BdMAPKs and 86 BdPP2Cs in B. distachyon using a novel docking approach. Further, we systematically investigated the docking site (D-site) of BdPP2C which plays a vital role for recognition and docking of BdMAPKs. D-site analysis revealed that there were 96 pairs of PPIs including all BdMAPKs and most BdPP2Cs, which indicated that BdPP2C may play roles in other signaling networks. Moreover, most BdPP2Cs have a D-site for BdMAPKs in our prediction results, which suggested that our method can effectively predict PPIs, as confirmed by their 3D structure. In addition, we validated this methodology with known Arabidopsis and yeast phosphatase-MAPK interactions from the STRING database. The results obtained provide a vital research resource for exploring an accurate network of PPIs between BdMAPKs and BdPP2Cs.
机译:蛋白质-蛋白质相互作用(PPI)是大多数生物过程的分子机制的基础。丝裂原激活的蛋白激酶(MAPK)可以被MAPK特异性磷酸酶(如PP2C)去磷酸化,这对于将细胞外信号转化为适应性和程序化反应至关重要。但是,用于识别PPI的实验方法昂贵,费时,费力且具有挑战性。作为响应,已经开发出许多计算方法来预测PPI。然而,这些方法具有固有的缺点,例如高的假阳性和阴性结果。因此,开发有效,准确地预测PPI的计算机方法至关重要。在这项研究中,我们使用新颖的对接方法在狄氏酵母中鉴定了16个BdMAPK和86个BdPP2C之间的PPI。此外,我们系统地研究了BdPP2C的停靠位点(D-位点),它对BdMAPKs的识别和停靠起着至关重要的作用。 D-位点分析显示,共有96对PPI,包括所有BdMAPK和大多数BdPP2C,这表明BdPP2C可能在其他信号网络中发挥作用。此外,在我们的预测结果中,大多数BdPP2C都有一个BdMAPKs的D位点,这表明我们的方法可以有效地预测PPI,正如其3D结构所证实的那样。此外,我们用来自STRING数据库的已知拟南芥和酵母磷酸酶-MAPK相互作用验证了该方法。获得的结果为探索BdMAPK和BdPP2C之间的PPI的精确网络提供了重要的研究资源。

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