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

许多蛋白质-蛋白质相互作用由短的线性基序介导， 保守的蛋白质结构域。了解分子生物学是现代生物学的一个长期目标， 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的机制， 转导和预测细胞定位，靶向和底物选择性的蛋白质，含有 肽识别结构域。重新设计结构域-肽相互作用的能力将导致蛋白质- 用于研究和治疗的相互作用抑制剂。蛋白质和肽库的研究进展 筛选和测序提供了令人兴奋的机会，以测量结构域-肽相互作用， 吞吐量与这些测量平行，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。这项建议 描述了一个集成的实验/计算程序的测量，建模和设计 由结构保守的EVH 1结构域介导的相互作用，结合短的富含脯氨酸的基序。的 建议的研究集中在对肌动蛋白细胞骨架的调节至关重要的Ena/VASP家族蛋白。三 人旁系同源物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板状伪足的形成以及肌动蛋白的调节是至关重要的。 基于细胞运动;他们也有新发现的神经发育中的作用。尤其是它的 亚型Mena侵袭性，控制癌细胞侵袭并促进对化疗的抵抗; EVH 1 因此，Mena的结合活性是有吸引力的治疗靶点。肽结合决定簇 EVH 1结构域知之甚少。在早期的工作中已经确定了短的共有结合基序 但不足以预测哪些序列将结合，或以何种特异性结合。序列 侧翼已知的基序调节EVH 1结构域的结合，但这种现象尚未系统地 研究了在三个具体目标中，我们提出（1）实验鉴定Ena/VASP EVH 1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，和（3）设计高亲和力和特异性和/或同种型选择性 EVH 1结构域相互作用的抑制剂。更深入地了解EVH 1域如何与合作伙伴互动， 推进我们对这些蛋白质如何促进细胞运动的理解，包括在侵袭性癌症中 细胞抑制剂设计将提供用于干扰Ena/VASP蛋白功能的试剂，包括以下作用： Mena在神经元中调节局部mRNA翻译。这项工作将建立一个映射路径， 抑制结构域-肽相互作用，其可应用于许多其它肽识别结构域。

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.