Data-driven prediction and design of bZIP coiled-coil interactions.
Data-driven prediction and design of bZIP coiled-coil interactions.
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DOI：
10.1371/journal.pcbi.1004046
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发表时间：
2015-02
影响因子：
4.3
通讯作者：
Keating AE
中科院分区：
文献类型：
--
作者：
Potapov V;Kaplan JB;Keating AE
碱性区亮氨酸拉链（bZIP）转录因子的选择性二聚化提供了一个生动的例子，说明如何在结构相似的蛋白质家族中实现高度的相互作用特异性。已经深入研究了介导bZIP蛋白质的同源或异源二聚化的卷曲螺旋基序，并且已经提出了多种方法来从序列数据预测这些相互作用。在这项工作中，我们使用了大量的4，549 bZIP卷曲螺旋相互作用来开发一个预测模型，该模型利用了卷曲螺旋基序中结构保守的残基-残基相互作用的知识。我们的模型，它表示相互作用能作为一个可解释的残基对和三重态项的总和，实现了与实验结合自由能的相关性R = 0.68，并显着优于其他评分功能。为了在蛋白质设计应用中使用我们的模型，我们设计了一种策略，其中通过将7个残基的天然蛋白质七肽模块组装成新的组合来构建合成肽。使用整数线性规划来找到选择性结合靶人bZIP卷曲螺旋但不结合靶旁系同源物的七肽的最佳组合。使用这种方法，我们设计了与来自人JUN、XBP 1、ATF 4和ATF 5的bZIP结构域相互作用的肽。使用荧光共振能量转移测定法测试超过132种候选蛋白质复合物，证实了所设计的肽与其靶标之间形成紧密的和选择性的异二聚体。这种方法可用于制造天然蛋白质的抑制剂，或开发用于合成生物学或纳米技术的新型肽。蛋白质相互作用对所有生命过程都很重要，合理控制或选择性抑制蛋白质复合物的能力将影响细胞结构、生物信息处理、分子调控过程和其他现象的研究。合理的蛋白质设计在开发生物治疗药物和推进合成生物学和纳米技术方面具有应用。在过去的几十年里，人们以多种方式研究了合理的蛋白质相互作用设计，但这仍然是一个挑战。计算方法需要模型来预测绑定和工具，用于在设计中应用预测模型。许多这样的方法是基于使用物理或半物理能量项来建模和评估蛋白质结构。在这项工作中，我们使用了一种不同的策略，推导出一个结合模型，该模型描述了蛋白质-蛋白质相互作用的碱性区域亮氨酸拉链（bZIP）translucent因子直接从大量的实验相互作用数据。我们的模型表现出比以前发表的预测更好的性能。我们使用我们的模型，结合蛋白质设计策略，从已知蛋白质的模块化部分构建新的蛋白质，成功地设计了新的bZIP样蛋白质结构域。我们通过实验证明，所设计的蛋白质紧密且特异性地结合到许多调节重要过程（包括应激反应和肿瘤发生）的人类bZIPs。
Selective dimerization of the basic-region leucine-zipper (bZIP) transcription factors presents a vivid example of how a high degree of interaction specificity can be achieved within a family of structurally similar proteins. The coiled-coil motif that mediates homo- or hetero-dimerization of the bZIP proteins has been intensively studied, and a variety of methods have been proposed to predict these interactions from sequence data. In this work, we used a large quantitative set of 4,549 bZIP coiled-coil interactions to develop a predictive model that exploits knowledge of structurally conserved residue-residue interactions in the coiled-coil motif. Our model, which expresses interaction energies as a sum of interpretable residue-pair and triplet terms, achieves a correlation with experimental binding free energies of R = 0.68 and significantly out-performs other scoring functions. To use our model in protein design applications, we devised a strategy in which synthetic peptides are built by assembling 7-residue native-protein heptad modules into new combinations. An integer linear program was used to find the optimal combination of heptads to bind selectively to a target human bZIP coiled coil, but not to target paralogs. Using this approach, we designed peptides to interact with the bZIP domains from human JUN, XBP1, ATF4 and ATF5. Testing more than 132 candidate protein complexes using a fluorescence resonance energy transfer assay confirmed the formation of tight and selective heterodimers between the designed peptides and their targets. This approach can be used to make inhibitors of native proteins, or to develop novel peptides for applications in synthetic biology or nanotechnology. Protein interactions are important for all life processes, and an ability to rationally control or selectively inhibit protein complexes would impact studies of cellular structure, biological information processing, molecular regulatory processes and other phenomena. Rational protein design has applications in developing biotherapeutics and in advancing synthetic biology and nanotechnology. Rational protein-interaction design has been approached in many ways over the past decades, but it remains a challenge. Computational methods require models to predict binding and tools for applying predictive models in design. Many such methods are based on modeling and evaluating protein structure using physical or semi-physical energy terms. In this work, we used a different strategy, deriving a binding model that describes the protein-protein interactions of basic-region leucine-zipper (bZIP) transcriptions factors directly from a large body of experimental interaction data. Our model showed much better performance than previously published predictors. We used our model, in conjunction with a protein-design strategy that builds new proteins from modular parts of known proteins, to successfully design novel bZIP-like protein domains. We demonstrated experimentally that the designed proteins bind tightly and specifically to a number of human bZIPs that regulate important processes including stress responses and oncogenesis.
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影响因子：
2.9
作者：
Krivov, Georgii G.;Shapovalov, Maxim V.;Dunbrack, Roland L., Jr.
通讯作者：
Dunbrack, Roland L., Jr.
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作者：
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通讯作者：
Ron, D
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Chen, Xi;Iliopoulos, Dimitrios;Zhang, Qing;Tang, Qianzi;Greenblatt, Matthew B.;Hatziapostolou, Maria;Lim, Elgene;Tam, Wai Leong;Ni, Min;Chen, Yiwen;Mai, Junhua;Shen, Haifa;Hu, Dorothy Z.;Adoro, Stanley;Hu, Bella;Song, Minkyung;Tan, Chen;Landis, Melissa D.;Ferrari, Mauro;Shin, Sandra J.;Brown, Myles;Chang, Jenny C.;Liu, X. Shirley;Glimcher, Laurie H.
通讯作者：
Glimcher, Laurie H.