De novo engineering of protein agonists and antagonists

描述（由申请人提供）：重组生产的细胞因子和抗体除了在正常生理中发挥重要作用外，还构成了一个重要的药物家族，用于治疗癌症、HIV和许多血液学和免疫疾病。然而，这些分子通常难以大量生产，由于二硫键的存在，它们的折叠和聚集性较差，并且作为治疗制剂相对不稳定。最近，与细胞因子和抗体相比，具有优越生物物理特性的替代支架已被用于定向进化实验，以设计高亲和力的结合物来靶向目标。然而，细胞因子和抗体疗法可以作为激动剂或拮抗剂，目前的定向进化方法只选择目标结合，而不是随后的激动剂或拮抗剂。在这里，我们建议利用替代支架的模块化折叠-设计的锚蛋白重复蛋白-开发新的定向进化方法来分离新的激动剂和拮抗剂。这项R21提案的目标是：1)设计模拟白细胞介素-12（一种有效的抗肿瘤细胞因子）的anykrin激动剂；2)制造基质酶的位点特异性锚定蛋白抑制剂，基质酶是一种细胞表面蛋白酶，与多种上皮源性肿瘤有关。更一般地说，这些方法不仅能够产生新的治疗方法，而且还将为特定的高亲和力蛋白质识别的基本要求提供独特的见解。

DESCRIPTION (provided by applicant): In addition to their vital roles in normal physiology, recombinantly produced cytokines and antibodies constitute a large, critical family of drugs used in the treatments for cancer, HIV, and a host of hematological and immune disorders. However, these molecules are often difficult to produce in mass quantities, suffer from poor folding and aggregation due to the presence of disulfide bonds, and are relatively unstable as therapeutic formulations. Recently, alternative scaffolds with superior biophysical properties to cytokines and antibodies have been used in directed evolution experiments to engineer high-affinity binders to targets of interest. However, cytokine and antibody therapeutics can serve as either agonists or antagonists, and current directed evolution methodologies only select for target binding, not consequent agonism or antagonism. Here, we propose to exploit the modular fold of an alternative scaffold - the designed ankyrin repeat protein - to develop novel directed evolution approaches for isolating new agonists and antagonists. The goals of this R21 proposal are to: 1) engineer anykrin agonists that are mimetics of interleukin-12, a potent anti-tumor cytokine, and 2) create site-specific ankyrin inhibitors of matriptase, a cell-surface protease tha is implicated in a variety of epithelial-derived tumors. More generally, these methods will not only enable the production of new therapeutics, but will also provide unique insights into the basic requirements for specific, high-affinity protein recognition.