Mapping, modeling and manipulating the interactions of protein domains that bind short linear motifs

许多蛋白质-蛋白质相互作用是由短的线性基序介导的，这些基序选择性地结合到模块， 保守的蛋白质结构域。了解分子生物学是现代生物学长期追求的目标。 这些类型的相互作用的识别代码，因为这将有助于阐明信号的机制 转导和预测细胞定位、靶向和底物选择性 多肽识别结构域。重新设计结构域-多肽相互作用的能力将导致蛋白质- 对研究和治疗有用的相互作用抑制剂。蛋白质和多肽文库的研究进展 筛选和测序提供了令人兴奋的机会来测量结构域-肽之间的相互作用 吞吐量。在这种测量的同时，需要计算方法来解释筛查。 结果并建立可用于蛋白质相互作用预测和设计的模型。这项建议 描述了一个用于测量、建模和设计的综合实验/计算程序 由结构保守的EVH1结构域介导的相互作用，这些EVH1结构域与短的富含Pro的基序结合。这个 拟议的研究集中在Ena/Vasp家族蛋白，这些蛋白对肌动蛋白细胞骨架的调节至关重要。三 人类的Paralog，Mena，Vasp和EVL，作为支架在肌动蛋白纤维的末端组装复合体。 Ena/Vasp蛋白对于丝足和片脂的形成以及对肌动蛋白的调节都是至关重要的。 基于细胞的运动性；它们在神经发育中也有新发现的作用。中东和北非，特别是其 同型膜侵袭，控制癌细胞侵袭，促进化疗耐药；EVH1 因此，MENA的结合活性是一个有吸引力的治疗靶点。的多肽结合决定因素 人们对EVH1结构域知之甚少。在早期的工作中已经确定了短的共识结合基序 但不足以预测哪些序列将结合，或具有什么样的平行对数特异性。该序列 侧翼已知的基序调节与EVH1结构域的结合，但这种现象尚未得到系统的研究 学习。在三个具体目标中，我们建议(1)通过实验鉴定Ena/Vasp EVH1结构域结合 人类蛋白质组中的多肽，确定结合的序列要求，并假设新的 生物相关的相互作用伙伴，(2)应用计算结构建模和实验 结构测定以了解结合专一性的机制，包括 核心基序和侧翼序列，以及(3)设计高亲和力和对对数和/或异构体具有选择性 EVH1结构域相互作用的抑制物。更深入地了解EVH1领域如何吸引其合作伙伴 促进我们对这些蛋白质如何促进细胞运动的理解，包括在浸润性癌症中的作用 细胞。抑制剂的设计将提供干扰Ena/Vasp蛋白功能的试剂，包括 MENA在调节神经元局部mRNA翻译中的作用。这项工作将为测绘和 抑制可应用于许多其他多肽识别结构域的结构域-多肽相互作用。

Many protein-protein interactions are mediated by short, linear motifs that bind selectively to modular, conserved protein domains. It is a long-standing goal of modern biology to understand the molecular recognition code for these types of interactions, because this would help elucidate mechanisms of signal transduction and predict cellular localization, targeting, and substrate selectivity of proteins that contain peptide-recognition domains. The ability to re-design domain-peptide interactions would lead to protein- interaction inhibitors useful for research and therapy. Recent advances in protein and peptide library screening and sequencing provide exciting opportunities to measure domain-peptide interactions in high throughput. In parallel with such measurements, computational methods are needed to interpret screening results and build models that can be used for protein interaction prediction and design. This proposal describes an integrated experimental/computational program for measuring, modeling and designing interactions mediated by structurally conserved EVH1 domains that bind to short, proline-rich motifs. The proposed studies focus on Ena/VASP family proteins critical for regulation of the actin cytoskeleton. Three human paralogs, Mena, VASP and EVL, act as scaffolds to assemble complexes at the ends of actin fibers. Ena/VASP proteins are critical for the formation of filopodia and lamellipodia and for regulation of actin- based cell motility; they also have newly discovered roles in neural development. Mena, and particularly its isoform Mena invasive, control cancer cell invasion and promote resistance to chemotherapy; the EVH1 binding activity of Mena is therefore an attractive therapeutic target. The peptide binding determinants for EVH1 domains are poorly understood. Short consensus binding motifs have been identified in earlier work but are not sufficient to predict which sequences will bind, or with what paralog specificity. Sequence that flanks known motifs modulates binding to EVH1 domains, but this phenomenon has not been systematically studied. In three specific aims, we propose to (1) experimentally identify Ena/VASP EVH1 domain-binding peptides in the human proteome, determine the sequence requirements for binding, and postulate new biologically relevant interaction partners, (2) apply computational structural modeling and experimental structure determination to understand the mechanisms of binding specificity, including the contributions of core-motif and flanking sequences, and (3) design high affinity and paralog- and/or isoform-selective inhibitors of EVH1 domain interactions. Deeper insight into how EVH1 domains engage their partners will advance our understanding of how these proteins contribute to cell motility, including in invasive cancer cells. Inhibitor design will provide reagents for perturbing Ena/VASP protein functions, including the role of Mena in regulating local mRNA translation in neurons. This work will establish a path for mapping and inhibiting domain-peptide interactions that can be applied to many other peptide-recognition domains.