Department of Bio and Brain Engineering, KAIST, S Korea.
BMC Bioinformatics. 2011 Feb 15;12 Suppl 1(Suppl 1):S23. doi: 10.1186/1471-2105-12-S1-S23.
Allosteric communication in proteins can be induced by the binding of effective ligands, mutations or covalent modifications that regulate a site distant from the perturbed region. To understand allosteric regulation, it is important to identify the remote sites that are affected by the perturbation-induced signals and how these allosteric perturbations are transmitted within the protein structure. In this study, by constructing a protein structure network and modeling signal transmission with a Markov random walk, we developed a method to estimate the signal propagation and the resulting effects. In our model, the global perturbation effects from a particular signal initiation site were estimated by calculating the expected visiting time (EVT), which describes the signal-induced effects caused by signal transmission through all possible routes. We hypothesized that the residues with high EVT values play important roles in allosteric signaling. We applied our model to two protein structures as examples, and verified the validity of our model using various types of experimental data. We also found that the hot spots in protein binding interfaces have significantly high EVT values, which suggests that they play roles in mediating signal communication between protein domains.
蛋白质中的变构通讯可以通过有效配体的结合、突变或共价修饰来诱导，这些修饰可以调节远离受扰区域的位点。为了理解变构调节，识别受扰动诱导信号影响的远程位点以及这些变构扰动如何在蛋白质结构内传递是很重要的。在这项研究中，我们通过构建蛋白质结构网络并使用马尔可夫随机游走对信号传输进行建模，开发了一种估计信号传播和由此产生的效应的方法。在我们的模型中，通过计算描述通过所有可能路径传输信号引起的信号诱导效应的期望访问时间 (EVT)，来估计来自特定信号起始位点的全局扰动效应。我们假设具有高 EVT 值的残基在变构信号传递中起重要作用。我们将我们的模型应用于两个蛋白质结构作为示例，并使用各种类型的实验数据验证了我们模型的有效性。我们还发现蛋白质结合界面中的热点具有显著高的 EVT 值，这表明它们在介导蛋白质域之间的信号通讯中起作用。
