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模块化、 保守的蛋白质结构域。理解分子生物学是现代生物学的长期目标 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机制 转导和预测包含以下蛋白质的细胞定位、靶向和底物选择性 肽识别域。重新设计结构域-肽相互作用的能力将导致蛋白质- 可用于研究和治疗的相互作用抑制剂。蛋白质和肽库的最新进展 筛选和测序提供了令人兴奋的机会来测量高水平的结构域-肽相互作用 吞吐量。与此类测量并行，需要计算方法来解释筛选 结果并建立可用于蛋白质相互作用预测和设计的模型。这个提议 描述了用于测量、建模和设计的集成实验/计算程序 由结构保守的 EVH1 结构域介导的相互作用，该结构域与短的、富含脯氨酸的基序结合。的 拟议的研究重点是对肌动蛋白细胞骨架调节至关重要的 Ena/VASP 家族蛋白。三 人类旁系同源物 Mena、VASP 和 EVL 作为支架在肌动蛋白纤维末端组装复合物。 Ena/VASP 蛋白对于丝状伪足和片状伪足的形成以及肌动蛋白的调节至关重要。 基于细胞运动；它们在神经发育中也有新发现的作用。梅纳，特别是其 异构体Mena具有侵袭性，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。肽结合决定因素 EVH1 结构域人们知之甚少。早期工作中已鉴定出短的共有结合基序 但不足以预测哪些序列将结合，或具有何种旁系同源特异性。排序 侧翼已知基序调节与 EVH1 结构域的结合，但这种现象尚未得到系统的研究 研究过。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 人类蛋白质组中的肽，确定结合的序列要求，并假设新的 生物学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特异性的机制，包括 核心基序和侧翼序列，以及（3）设计高亲和力和旁系同源物和/或异构体选择性 EVH1 结构域相互作用的抑制剂。更深入地了解 EVH1 域如何吸引合作伙伴 增进我们对这些蛋白质如何促进细胞运动（包括侵袭性癌症）的理解 细胞。抑制剂设计将提供干扰 Ena/VASP 蛋白功能的试剂，包括 Mena 调节神经元局部 mRNA 翻译。这项工作将为测绘和建立一条路径 抑制结构域-肽相互作用，可应用于许多其他肽识别结构域。

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.