Biochimica et Biophysica Acta (BBA) - General Subjects ( IF 2.8 ) Pub Date : 2019-07-19 , DOI: 10.1016/j.bbagen.2019.07.008 Lindy Astl 1 , Gennady M Verkhivker 2
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Background
Computational studies of allosteric interactions have witnessed a recent renaissance fueled by the growing interest in modeling of the complex molecular assemblies and biological networks. Allosteric interactions in protein structures allow for molecular communication in signal transduction networks.
Methods
In this work, we performed a large scale comprehensive and multi-faceted analysis of >300 diverse allosteric proteins and complexes with allosteric modulators. By modeling and exploring coarse-grained dynamics, residue coevolution, and residue interaction networks for allosteric proteins, we have determined unifying molecular signatures shared by allosteric systems.
Results
The results of this study have suggested that allosteric inhibitors and allosteric activators may differentially affect global dynamics and network organization of protein systems, leading to diverse allosteric mechanisms. By using structural and functional data on protein kinases, we present a detailed case study that that included atomic-level analysis of coevolutionary networks in kinases bound with allosteric inhibitors and activators.
Conclusions
We have found that coevolutionary networks can form direct communication pathways connecting functional regions and can recapitulate key regulatory sites and interactions responsible for allosteric signaling in the studied protein systems. The results of this computational investigation are compared with the experimental studies and reveal molecular signatures of known regulatory hotspots in protein kinases.
General significance
This study has shown that allosteric inhibitors and allosteric activators can have a different effect on residue interaction networks and can exploit distinct regulatory mechanisms, which could open up opportunities for probing allostery and new drug combinations with broad range of activities.
中文翻译：
通过探索蛋白质动力学、残基协同进化和残基相互作用网络对变构蛋白质进行数据驱动的计算分析
背景
由于人们对复杂分子组装体和生物网络建模的兴趣日益浓厚，变构相互作用的计算研究最近出现了复兴。蛋白质结构中的变构相互作用允许信号转导网络中的分子通讯。
方法
在这项工作中，我们对超过 300 种不同的变构蛋白和变构调节剂复合物进行了大规模、全面、多方面的分析。通过建模和探索变构蛋白的粗粒度动力学、残基协同进化和残基相互作用网络，我们确定了变构系统共享的统一分子特征。
结果
这项研究的结果表明，变构抑制剂和变构激活剂可能对蛋白质系统的整体动力学和网络组织产生不同的影响，从而导致不同的变构机制。通过使用蛋白激酶的结构和功能数据，我们提出了详细的案例研究，其中包括对与变构抑制剂和激活剂结合的激酶中的共同进化网络进行原子水平分析。
结论
我们发现共同进化网络可以形成连接功能区域的直接通讯途径，并且可以概括负责所研究的蛋白质系统中变构信号传导的关键调控位点和相互作用。这项计算研究的结果与实验研究进行了比较，揭示了蛋白激酶中已知调控热点的分子特征。
一般意义
这项研究表明，变构抑制剂和变构激活剂可以对残基相互作用网络产生不同的影响，并且可以利用不同的调节机制，这可以为探索变构和具有广泛活性的新药物组合开辟机会。
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