变构调节
共同进化
计算机科学
相互信息
信息流
传递熵
信息传递
序列(生物学)
熵(时间箭头)
信息论
人工智能
计算生物学
高斯分布
最大熵原理
完整信息
领域(数学分析)
动态网络分析
信息结构
人工神经网络
理论计算机科学
控制(管理)
进化动力学
进化生物学
作者
Kemal Demirtaş,Burak Erman,Türkan Haliloǧlu
标识
DOI:10.1073/pnas.2612667123
摘要
The relationship between evolution and allostery is inherently intertwined. While structural studies have elucidated allosteric mechanisms, the extent to which evolutionary sequence information encodes these dynamic networks remains underexplored. Here, we introduce Sequence-based GNM-TE, a framework that integrates coevolutionary information with Gaussian Network Model (GNM) based Transfer Entropy (TE) calculations. This approach translates evolutionary constraints, shaped by both structural and functional requirements, into functionally meaningful allosteric dynamic information. Across 29 cases, we identify binding sites as dynamic hubs of collective information transfer and reveal mode-dependent, directional information flows between these sites. These findings overall indicate that evolutionary constraints embed the architecture of allosteric regulation within protein sequences, preserving binding site communication within layered dynamic ensembles that enable robust functional control and adaptation.
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