Biomolecular Recognition and Binding Mechanisms

蛋白质通过相互作用发挥作用，而蛋白质相互作用网络的可用性可以帮助理解细胞过程。然而，已知的结构数据是有限的，经典的网络节点-边表示，其中蛋白质是节点，相互作用是边，只显示了哪些蛋白质相互作用；而不是它们如何相互作用。结构性网络提供了这方面的信息。蛋白质-蛋白质界面结构还可以指示哪些结合伙伴可以同时相互作用，哪些是竞争性的，并有助于预测潜在的有害药物副作用。在这里，我们使用一个强大的蛋白质相互作用预测工具，能够在蛋白质组水平上进行准确的预测，以构建丝裂原活化蛋白激酶(MAPK)信号通路中细胞外信号调节蛋白激酶(ERK)的结构网络结构。这种基于知识的方法PRISM是基于Motif的，并与灵活的求精和能量评分相结合。PRISM基于与已知蛋白质界面的结构和进化相似性来预测蛋白质相互作用。细胞凋亡是细胞的生死攸关的问题，抑制和促进细胞凋亡可能参与人类疾病的发病机制。在细胞凋亡信号通路中，蛋白质-蛋白质复合体的结构非常重要，因为这种结构通路有助于理解调控和信息传递的机制，并有助于确定药物设计的靶点。在这里，我们的目标是预测这些结构，以获得比目前可用的更多信息的途径。基于靶途径中复合体的三维结构和蛋白质-蛋白质相互作用的建模工具，我们模拟了29个相互作用的结构，其中21个是以前未知的。接下来，预测了27个未列入KEGG细胞凋亡途径的相互作用，并随后通过文献中的实验数据进行了验证。还预测了更多的相互作用。分析了多伙伴HUB蛋白，并确定了可以和不能共存的相互作用。总体而言，我们的结果丰富了对该途径相互作用的理解，并为人类凋亡途径提供了结构细节。他们还表明，大规模的蛋白质-蛋白质相互作用的计算模型可以帮助验证实验数据，并提供准确的、原子水平的人类细胞信号通路的结构细节。CBP的KIX结构域是一个转录辅助激活因子。原癌基因蛋白c-Myb的激活域与三胸群蛋白混合系白血病(MLL)转录因子的反式激活域结合形成具有生物活性的MLL-KIX-c-Myb三元复合体，在Pol II介导的转录过程中发挥作用。MLL的激活域与KIX的结合增强了c-Myb的结合。在这里，我们对MLL-KIX-c-Myb三元配合物、其二元组分和KIX进行了分子动力学(MD)模拟，目的是为实验观察提供机理解释。动力学行为表明，MLL结合部位与c-Myb结合部位是变构偶联的。MLL结合重新分配KIX的构象集合，导致更多有利于c-Myb结合的状态。变构通讯通路中的关键元件是KIX环，它作为一种控制机制来增强后续的结合事件。我们通过KIX-LL复合体中环残基的电子突变以及通过MD模拟比较野生型和突变型的动力学来验证这一结论。环假定MLL结合构象类似于在KIX-c-Myb状态下观察到的，这不利于变构网络。与c-Myb结合部位的偶联消失，取消了在MLL存在下观察到的正协同性。我们的主要结论是，通过在结合事件后的不同状态之间引发环介导的变构开关，转录激活可以被调节。KIX系统提供了一个例子，大自然如何利用构象控制来更高水平地调控转录活动，从而调节细胞事件。NRF2是众所周知的氧化和异种应激反应的主要转录因子(TF)。最近的研究发现，NRF2具有更广泛的调控作用，影响癌症的发生、炎症和神经退变。在这些进展的推动下，我们提供了一个系统水平的NRF2相互作用组和调节组资源，包括289个蛋白质-蛋白质相互作用，7469个Tf-DNA相互作用和85个miRNA相互作用。作为NRF2相关信号的系统水平的例子，我们确定了NRF2相互作用蛋白(例如JNK1和CBP)的调控环和一个微调的调控系统，其中由NRF2调控的35个TF影响63个下调NRF2的miRNAs。目前的网络和已发现的调控环可能会促进高效的、基于NRF2的治疗药物的开发。变构药物因其副作用较少而越来越多地被使用。变构信号的传播不会在蛋白质的‘末端’停止，而是可以动态地在细胞内传播。我们在这里提出，变构药物的概念可以扩展到别构网络药物-其作用可以在一个蛋白质内传播，也可以跨几个蛋白质传播，以增强或抑制沿着一条途径的特定相互作用。我们假设目前的变构药物是异构型药物的特例，并认为异构型药物可以在系统水平上实现特定的、有限的改变，从而获得更少的副作用和更低的毒性。最后，我们提出了确定异源网络药物靶点和位置的步骤和方法，概述了基于系统的药物设计的新范式。

Proteins function through their interactions, and the availability of protein interaction networks could help in understanding cellular processes. However, the known structural data are limited and the classical network node-and-edge representation, where proteins are nodes and interactions are edges, shows only which proteins interact; not how they interact. Structural networks provide this information. Protein-protein interface structures can also indicate which binding partners can interact simultaneously and which are competitive, and can help forecasting potentially harmful drug side effects. Here, we use a powerful protein-protein interactions prediction tool which is able to carry out accurate predictions on the proteome scale to construct the structural network of the extracellular signal-regulated kinases (ERK) in the mitogen-activated protein kinase (MAPK) signaling pathway. This knowledge-based method, PRISM, is motif-based, and is combined with flexible refinement and energy scoring. PRISM predicts protein interactions based on structural and evolutionary similarity to known protein interfaces.Apoptosis is a matter of life and death for cells and both inhibited and enhanced apoptosis may be involved in the pathogenesis of human diseases. The structures of protein-protein complexes in the apoptosis signaling pathway are important as the structural pathway helps in understanding the mechanism of the regulation and information transfer, and in identifying targets for drug design. Here, we aim to predict the structures toward a more informative pathway than currently available. Based on the 3D structures of complexes in the target pathway and a protein-protein interaction modeling tool which allows accurate and proteome-scale applications, we modeled the structures of 29 interactions, 21 of which were previously unknown. Next, 27 interactions which were not listed in the KEGG apoptosis pathway were predicted and subsequently validated by the experimental data in the literature. Additional interactions are also predicted. The multi-partner hub proteins are analyzed and interactions that can and cannot co-exist are identified. Overall, our results enrich the understanding of the pathway with interactions and provide structural details for the human apoptosis pathway. They also illustrate that computational modeling of protein-protein interactions on a large scale can help validate experimental data and provide accurate, structural atom-level detail of signaling pathways in the human cell.The KIX domain of CBP is a transcriptional coactivator. Concomitant binding to the activation domain of proto-oncogene protein c-Myb and the transactivation domain of the trithorax group protein mixed lineage leukemia (MLL) transcription factor lead to the biologically active ternary MLL-KIX-c-Myb complex which plays a role in Pol II-mediated transcription. The binding of the activation domain of MLL to KIX enhances c-Myb binding. Here we carried out molecular dynamics (MD) simulations for the MLL-KIX-c-Myb ternary complex, its binary components and KIX with the goal of providing a mechanistic explanation for the experimental observations. The dynamic behavior revealed that the MLL binding site is allosterically coupled to the c-Myb binding site. MLL binding redistributes the conformational ensemble of KIX, leading to higher populations of states which favor c-Myb binding. The key element in the allosteric communication pathways is the KIX loop, which acts as a control mechanism to enhance subsequent binding events. We tested this conclusion by in silico mutations of loop residues in the KIX-LL complex and by comparing wild type and mutant dynamics through MD simulations. The loop assumed MLL binding conformation similar to that observed in the KIX-c-Myb state which disfavors the allosteric network. The coupling with c-Myb binding site faded, abolishing the positive cooperativity observed in the presence of MLL. Our major conclusion is that by eliciting a loop-mediated allosteric switch between the different states following the binding events, transcriptional activation can be regulated. The KIX system presents an example how nature makes use of conformational control in higher level regulation of transcriptional activity and thus cellular events.NRF2 is a well-known, master transcription factor (TF) of oxidative and xenobiotic stress responses. Recent studies uncovered an even wider regulatory role of NRF2 influencing carcinogenesis, inflammation and neurodegeneration. Prompted by these advances here we present a systems-level resource for NRF2 interactome and regulome that includes 289 protein-protein, 7469 TF-DNA and 85 miRNA interactions. As systems-level examples of NRF2-related signaling we identified regulatory loops of NRF2 interacting proteins (e.g., JNK1 and CBP) and a fine-tuned regulatory system, where 35 TFs regulated by NRF2 influence 63 miRNAs that down-regulate NRF2. The presented network and the uncovered regulatory loops may facilitate the development of efficient, NRF2-based therapeutic agents.Allosteric drugs are increasingly used because they produce fewer side effects. Allosteric signal propagation does not stop at the 'end' of a protein, but may be dynamically transmitted across the cell. We propose here that the concept of allosteric drugs can be broadened to allo-network drugs - whose effects can propagate either within a protein, or across several proteins, to enhance or inhibit specific interactions along a pathway. We posit that current allosteric drugs are a special case of allo-network drugs, and suggest that allo-network drugs can achieve specific, limited changes at the systems level, and in this way can achieve fewer side effects and lower toxicity. Finally, we propose steps and methods to identify allo-network drug targets and sites that outline a new paradigm in systems-based drug design.