Discovering hybrid inhibitors for tumor microenvironment disruption

虽然肿瘤中细胞外蛋白酶和肽酶的促癌活性 微环境是众所周知的，在基本和翻译环境中的单个酶的特异性破坏 仍然是一个根本性挑战。例如，使用泛特异性化学基质抑制剂 金属蛋白酶（MMPs）在癌症动物模型中的作用已经证明，干扰MMP活性 可以减缓癌症进展，但这些抑制剂的临床转化失败，主要是由于缺乏抑制剂 的特异性努力发现特定的抑制剂或快速实施遗传方法来干扰 在肿瘤微环境中活跃的MMP和其他酶仍然具有挑战性。新发现 表明MMPs调节肿瘤微环境中的信号传导和免疫功能， 对于阐明MMPs在肿瘤微环境中发挥的广泛作用至关重要的特异性试剂 并建立具有潜在临床应用价值的新一代抑制剂。 在这个应用中，我们提出建立一个发现高度特异性酶抑制剂的平台 在高吞吐量中。我们的基础技术结合了酵母展示和非规范氨基酸的使用， 酸来构建和评估具有使用常规方法无法获得的结构的抑制剂， 接近。我们假设在抗体框架内精确定位小分子将产生 二价“杂合抑制剂”保留抗原特异性，同时获得有效的抑制能力。我们将 通过针对MMP-2、MMP-7、MMP-9和MMP-14实施我们基于酵母的发现平台， 众多与MMP相关的工具，使我们能够探索我们平台的功能。我们将建立 我们的平台使用以下两个特定目标：1）识别抗体中有效的小分子定位 以实现高效的混合发现。本文将定量地探讨小分子化合物 抗体可变区内的连接位点、官能团和接头，以鉴定最有希望的 这些因素的组合用于大规模混合发现。2)建立定量关系 抑制剂性质和细胞侵袭。在这个目标中，我们将比较我们从基于酵母的 测量与标准生物化学和基于细胞的测定的数据，以设定数值目标 在杂交发现的努力，并检查的作用，基质金属蛋白酶在细胞侵袭。 这里提出的平台将产生分子试剂，其结构和特异性不能被 使用现有的基于小分子或蛋白质的方法进行访问。所得的MMP抑制剂可用于 作为治疗先导，因为它们的高特异性将克服先前治疗的关键缺点， 候选人在肿瘤微环境中精确的酶破坏也将导致更好的理解 在分子和系统水平上的肿瘤生物学。最后，我们预计，混合方法， 酶抑制将适用于任何酶家族的成员特异性靶向。

Although cancer-promoting activities of extracellular proteases and peptidases in the tumor microenvironment are well known, the specific disruption of a single enzyme in basic and translational settings remains a fundamental challenge. For example, the use of pan-specific chemical inhibitors of matrix metalloproteinases (MMPs) in animal models of cancer has demonstrated that interfering with MMP activity can slow cancer progression, but clinical translation of these inhibitors has failed, largely due to lack of inhibitor specificity. Efforts to discover specific inhibitors or rapidly implement genetic approaches to interfere with MMPs and other enzymes active in the tumor microenvironment remain challenging. Emerging findings indicate that MMPs modulate signaling and immune function in the tumor microenvironment, making highly specific reagents critical to elucidate the wide range of roles MMPs play within the tumor microenvironment and to establish a new generation of inhibitors for potential clinical applications. In this application, we propose to establish a platform for the discovery of highly specific enzyme inhibitors in high throughput. Our underlying technology combines the use of yeast display and noncanonical amino acids to construct and evaluate inhibitors with structures that are not accessible using conventional approaches. We hypothesize that precisely positioning small molecules within an antibody framework will yield bivalent “hybrid inhibitors” that retain antigen specificity while gaining potent inhibitory capabilities. We will implement our yeast-based discovery platform by targeting MMP-2, -7, -9, and -14 because of the availability of numerous MMP-related tools that will allow us to explore the capabilities of our platform. We will establish our platform using the following two specific aims: 1) Identify effective small molecule positioning in antibodies to enable efficient hybrid discovery. In this Aim, we will quantitatively explore the effects of small molecule attachment sites, functional groups, and linkers within antibody variable regions to identify the most promising combinations of these factors for large-scale hybrid discovery. 2) Establish quantitative relationships between inhibitor properties and cell invasion. In this Aim, we will compare data we derive from yeast-based measurements with data from standard biochemical and cell-based assays in order to set numerical targets during hybrid discovery efforts and to examine the roles of MMPs in cell invasion. The platform proposed here will yield molecular reagents with structures and specificities that cannot be accessed using existing small molecule- or protein-based approaches. The resulting MMP inhibitors may serve as therapeutic leads, as their high specificities will overcome key shortcomings of previous therapeutic candidates. Precise enzyme disruption in the tumor microenvironment will also lead to a better understanding of tumor biology at both molecular and systems levels. Finally, we anticipate that the hybrid approach to enzyme inhibition will be applicable to member-specific targeting of any family of enzymes.