Department of Biomedical and Pharmaceutical Sciences, Chapman University School of Pharmacy, Irvine, CA 92618, United States; Department of Pharmacology, Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, 9500 Gilman Drive, La Jolla, CA 92093, USA.
Biochim Biophys Acta Gen Subj. 2019 Jan;1863(1):210-225. doi: 10.1016/j.bbagen.2018.10.009. Epub 2018 Oct 16.
In the current study, we have combined molecular simulations and energetic analysis with dynamics-based network modeling and perturbation response scanning to determine molecular signatures of mutational hotspot residues in the p53, PTEN, and SMAD4 tumor suppressor proteins. By examining structure, energetics and dynamics of these proteins, we have shown that inactivating mutations preferentially target a group of structurally stable residues that play a fundamental role in global propagation of dynamic fluctuations and mediating allosteric interaction networks. Through integration of long-range perturbation dynamics and network-based approaches, we have quantified allosteric potential of residues in the studied proteins. The results have revealed that mutational hotspot sites often correspond to high centrality mediating centers of the residue interaction networks that are responsible for coordination of global dynamic changes and allosteric signaling. Our findings have also suggested that structurally stable mutational hotpots can act as major effectors of allosteric interactions and mutations in these positions are typically associated with severe phenotype. Modeling of shortest inter-residue pathways has shown that mutational hotspot sites can also serve as key mediating bridges of allosteric communication in the p53 and PTEN protein structures. Multiple regression models have indicated that functional significance of mutational hotspots can be strongly associated with the network signatures serving as robust predictors of critical regulatory positions responsible for loss-of-function phenotype. The results of this computational investigation are compared with the experimental studies and reveal molecular signatures of mutational hotspots, providing a plausible rationale for explaining and localizing disease-causing mutations in tumor suppressor genes.
在当前的研究中，我们将分子模拟和能量分析与基于动力学的网络建模和扰动响应扫描相结合，以确定 p53、PTEN 和 SMAD4 肿瘤抑制蛋白中突变热点残基的分子特征。通过检查这些蛋白质的结构、能量和动力学，我们表明失活突变优先靶向一组结构稳定的残基，这些残基在动态波动的全局传播和介导变构相互作用网络中起着基本作用。通过整合远程扰动动力学和基于网络的方法，我们对研究蛋白中残基的变构潜力进行了量化。结果表明，突变热点位点通常对应于残基相互作用网络的高中心性介导中心，这些中心负责协调全局动态变化和变构信号。我们的研究结果还表明，结构稳定的突变热点可以作为变构相互作用的主要效应物，这些位置的突变通常与严重的表型相关。最短残基间路径的建模表明，突变热点也可以作为 p53 和 PTEN 蛋白质结构中变构通讯的关键介导桥。多元回归模型表明，突变热点的功能意义与网络特征密切相关，这些网络特征是负责功能丧失表型的关键调节位置的稳健预测因子。该计算研究的结果与实验研究进行了比较，揭示了突变热点的分子特征，为解释和定位肿瘤抑制基因中的致病突变提供了合理的依据。
