Department of Chemical Engineering, Bogazici University, 34342 Istanbul, Turkey; Polymer Research Center, Bogazici University, 34342 Istanbul, Turkey.
Polymer Research Center, Bogazici University, 34342 Istanbul, Turkey.
J Mol Biol. 2022 Sep 15;434(17):167644. doi: 10.1016/j.jmb.2022.167644. Epub 2022 May 26.
Allostery is a key biological control mechanism, and dynamic information flow provides a perspective to describe allosteric interactions in causal relationships. Here, as a novel implementation of the Gaussian Network Model (GNM) based Transfer Entropy (TE) calculations, we show that the dissection of dynamic information into subsets of slow dynamic modes discloses different layers of multi-directional allosteric pathways inherent in a given protein structure. In these subsets of slow modes, the degree of collectivity (Col) in the information transfer of residues with their TE values (TECol score) identifies distinct residues as powerful effectors, global information sources; showing themselves with a high dynamic capacity to collectively disseminate information to others. As exemplified on aspartate transcarbamoylase (ATCase), Na/K-adenosine triphosphatase (Na/K-ATPase), and human transient receptor potential melastatin 2 (TRPM2) along with a dataset of 20 proteins, these specific residues are associated with known active and allosteric sites. These information source residues, which collectively control others and lead allosteric communication pathways, hint at plausible binding sites for structure-based rational drug design.
变构作用是一种关键的生物控制机制,而动态信息流提供了一种描述变构相互作用因果关系的视角。在这里,作为基于高斯网络模型(GNM)的转移熵(TE)计算的一种新实现,我们表明,将动态信息分解为慢动态模式的子集,可以揭示给定蛋白质结构中固有的多向变构途径的不同层次。在这些慢模式的子集中,残基的信息传递的集合程度(Col)及其 TE 值(TECol 得分)确定了不同的残基作为强大的效应物和全局信息源;它们表现出很高的动态能力,能够将信息集体传播给其他残基。以天冬氨酸转氨甲酰酶(ATCase)、钠/钾-三磷酸腺苷酶(Na/K-ATPase)和人瞬时受体电位 melastatin 2(TRPM2)为例,并结合 20 个蛋白质的数据集,这些特定的残基与已知的活性和变构位点相关联。这些信息源残基共同控制其他残基并引导变构通讯途径,暗示了基于结构的合理药物设计的可能结合位点。