Allosteric communication occurs via networks of tertiary and quaternary motions in proteins.
Allosteric communication occurs via networks of tertiary and quaternary motions in proteins.
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DOI：
10.1371/journal.pcbi.1000293
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发表时间：
2009-02
影响因子：
4.3
通讯作者：
Gray JJ
中科院分区：
文献类型：
--
作者：
Daily MD;Gray JJ
变构蛋白在一个位点结合效应分子，导致第二个位点的功能变化。我们假设蛋白质中的变构通信依赖于四级（集体，刚体）和三级（残基-残基接触）运动的网络。我们认为，这些网络的环状拓扑结构是必要的变构通信。自动算法从非活性和活性结构之间的位移识别刚体，并从这些刚体和底物和效应配体构建“四元网络”。然后，我们将四元网络与粗粒度的接触重排表示，形成“全球通信网络”（GCN）。GCN揭示了18个多结构域和多聚体蛋白中的15个中的所有底物和效应位点之间的变构通信，而三级和四级网络分别仅在这些蛋白中的4个和3个中表现出这种通信。此外，在由GCN连接的15种蛋白质中的7种中，50%或更多的通过GCN的底物-效应物路径是不存在通过三级或四级网络的“相互依赖”路径。底物-效应物“途径”通常不是线性的，而是由刚性体的多环网络和重排残基接触簇组成。这些结果证明了基于结构变化的变构通信的广泛适用性，并证明了GCN的实用性。全球通信网络可以为变构蛋白的各种实验以及将变构设计成非变构蛋白提供信息。变构调节是许多生物过程中的主要控制机制，包括细胞信号传导、基因调节和代谢调节，并且功能失常的变构蛋白通常涉及癌症和其他疾病。在变构中，效应器结合信号通过蛋白质结构长距离传输，导致第二个位点的功能变化。虽然许多变构蛋白质的三维结构已被解决，但从非活性状态结构和活性状态结构之间的运动来看，变构通信机制通常不明显。此外，变构结构转变涉及氨基酸残基水平的小尺度运动和结构域水平的大尺度运动。在这里，为了解决变构机制，我们将上述蛋白质运动转化为多尺度的“全局通信网络”（GCN）表示，从中可以识别底物效应通路和其他重要的变构通信特性。GCN占15的18个蛋白质的底物效应途径调查，和GCN揭示，变构往往取决于小和大规模的运动之间的联系。这项工作将为研究变构的各种实验提供信息，并提出了将变构工程化为非变构蛋白的概念。
Allosteric proteins bind an effector molecule at one site resulting in a functional change at a second site. We hypothesize that allosteric communication in proteins relies upon networks of quaternary (collective, rigid-body) and tertiary (residue–residue contact) motions. We argue that cyclic topology of these networks is necessary for allosteric communication. An automated algorithm identifies rigid bodies from the displacement between the inactive and the active structures and constructs “quaternary networks” from these rigid bodies and the substrate and effector ligands. We then integrate quaternary networks with a coarse-grained representation of contact rearrangements to form “global communication networks” (GCNs). The GCN reveals allosteric communication among all substrate and effector sites in 15 of 18 multidomain and multimeric proteins, while tertiary and quaternary networks exhibit such communication in only 4 and 3 of these proteins, respectively. Furthermore, in 7 of the 15 proteins connected by the GCN, 50% or more of the substrate-effector paths via the GCN are “interdependent” paths that do not exist via either the tertiary or the quaternary network. Substrate-effector “pathways” typically are not linear but rather consist of polycyclic networks of rigid bodies and clusters of rearranging residue contacts. These results argue for broad applicability of allosteric communication based on structural changes and demonstrate the utility of the GCN. Global communication networks may inform a variety of experiments on allosteric proteins as well as the design of allostery into non-allosteric proteins. Allosteric regulation is a major mechanism of control in many biological processes, including cell signaling, gene regulation, and metabolic regulation, and malfunctioning allosteric proteins are often involved in cancer and other diseases. In allostery, an effector-binding signal transmits over a long distance through the protein structure, resulting in a functional change at a second site. While many three-dimensional structures of allosteric proteins have been solved, the allosteric communication mechanism is usually not obvious from the motions between inactive and active state structures. In addition, allosteric structural transitions involve both small-scale motions at the level of amino acid residues and large-scale motions at the level of domains. Here, to address allosteric mechanisms, we transform the aforementioned protein motions into a multi-scale “global communication network” (GCN) representation from which substrate-effector pathways and other important allosteric communication properties can be identified. The GCN accounts for substrate-effector pathways in 15 of 18 proteins surveyed, and the GCN reveals that allostery often depends on linkage between the small- and the large-scale motions. This work will inform a wide variety of experiments investigating allostery, and it proposes concepts for engineering allostery into non-allosteric proteins.
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影响因子：
5.6
作者：
Eyal, E;Gerzon, S;Sobolev, V
通讯作者：
Sobolev, V
影响因子：
2.9
作者：
Daily, Michael D.;Upadhyaya, Tarak J.;Gray, Jeffrey J.
通讯作者：
Gray, Jeffrey J.
DOI：
10.1016/s1359-0278(97)00024-2
发表时间：
1997-01-01
期刊：
FOLDING & DESIGN
影响因子：
--
作者：
Bahar, I;Atilgan, AR;Erman, B
通讯作者：
Erman, B
影响因子：
5.7
作者：
Koppole, Sampath;Smith, Jeremy C.;Fischer, Stefan
通讯作者：
Fischer, Stefan
影响因子：
5.6
作者：
BOUTONNET, NS;ROOMAN, MJ;WODAK, SJ
通讯作者：
WODAK, SJ