Exploiting new approaches for selective inhibition of trypsins

项目总结/摘要 人胰蛋白酶同种型，胰蛋白酶1、胰蛋白酶2和中胰蛋白酶，是已经牵涉到胰蛋白酶的蛋白酶。 疾病过程中的癌症和胰腺炎，并可能提供可行的治疗目标。胰蛋白酶属于 具有类似活性位点拓扑结构的胰蛋白酶样酶的大家族，因此现有的抑制剂缺乏 选择性需要选择性胰蛋白酶抑制剂和异构体选择性胰蛋白酶抑制剂， 药理学工具，以更好地定义这些单个酶在疾病中的功能，并评估 胰蛋白酶抑制作为临床前疾病模型中的治疗策略。在这个项目中，我们将采取 多管齐下的方法，以开发新的战略，有效和选择性抑制每一个人类 胰蛋白酶同种型。(1)我们的初步数据揭示了一种以前未被怀疑的自抑制构象， 在一些实施方案中，所述中胰蛋白酶具有可用于抑制作用的配体靶向变构位点。我们将使用高- 吞吐量虚拟筛选和基于结构的命中领先优化，以开发有效且有选择性的产品 中胰蛋白酶的变构抑制剂。我们还将使用结构和分子动力学分析来评估 类似的策略是否对胰蛋白酶1和2具有潜力。(2)我们发表的研究表明， Kunitz结构域可以被工程化以产生更有选择性的胰蛋白酶样蛋白酶抑制剂 利用酵母表面展示（YSD）平台进行定向进化。为了能够进一步优化这种 抑制剂，我们寻求生成结合特异性景观的全面地图，对于任何 抑制剂内突变的可能组合，预测对抑制剂亲和力的影响， 针对一组靶蛋白酶的特异性。我们将通过整合YSD组合来完成这项任务 利用下一代测序（NGS）、机器学习（ML）方法进行文库筛选， 实验校准，以便能够定量预测多种潜在相互作用的影响， 抑制剂的突变。这些数据将使我们能够确定最有效和选择性的Kunitz结构域 这可以实现靶向每一种人胰蛋白酶。(3)我们的初步数据显示， 通过能够同时结合两种分子的二价抑制剂增强胰蛋白酶亲和力 中胰蛋白酶在这里，我们将剖析负责这些亲和力增强和设计的机制， 利用这些信息开发更有效和选择性的多价胰蛋白酶的策略 抑制剂的除了制定三项互补战略外，每项战略都有很大的潜力， 产生所需的选择性抑制剂的人类胰蛋白酶，我们的项目将提供更广泛的见解，可以帮助 许多其他重要的胰蛋白酶样蛋白酶抑制剂的未来发展。最后，新的方法论 这里开发的映射蛋白质-蛋白质相互作用（PPI）的亲和力和特异性景观将是广泛的 用于表征控制功能性化合物的亲和性和选择性的序列和结构约束的实用性 蛋白质相互作用在许多其他不同的系统。

PROJECT SUMMARY/ABSTRACT The human trypsin isoforms, trypsin 1, trypsin 2, and mesotrypsin, are proteases that have been implicated in disease processes in cancer and pancreatitis, and may offer viable therapeutic targets. Trypsins belong to a large family of trypsin-like enzymes with similar active site topology, and hence existing inhibitors lack selectivity. There is a need for selective trypsin inhibitors and isoform-selective trypsin inhibitors as pharmacological tools to better define the functions of these individual enzymes in disease, and to evaluate trypsin inhibition as a therapeutic strategy in preclinical models of disease. In this project, we will take a multipronged approach to develop new strategies for potent and selective inhibition of each of the human trypsin isoforms. (1) Our preliminary data reveal a previously unsuspected auto-inhibited conformation of mesotrypsin with a ligand-targetable allosteric site that may be exploited for inhibitory effect. We will use high- throughput virtual screening and structure-based hit-to-lead optimization to develop potent and selective allosteric inhibitors of mesotrypsin. We will also use structural and molecular dynamics analyses to evaluate whether similar strategies may hold potential for trypsins 1 and 2. (2) Our published studies have shown that Kunitz domains can be engineered to create more selective protein-based inhibitors of trypsin-like proteases by using a yeast surface display (YSD) platform for directed evolution. To enable further optimization of such inhibitors, we seek to generate comprehensive maps of the binding specificity landscapes that can, for any possible combination of mutations within an inhibitor, predict the consequences on inhibitor affinity and specificity toward a set of target proteases. We will accomplish this task by integrating YSD combinatorial library screening with next-generation sequencing (NGS), machine-learning (ML) approaches, and experimental calibration to enable quantitative prediction of the impact of multiple potentially interacting mutations of an inhibitor. These data will enable us to identify the most potent and selective Kunitz domains that can be achieved for targeting each of the human trypsins. (3) Our preliminary data demonstrate an enhancement of trypsin affinity by bivalent inhibitors capable of binding simultaneously to two molecules of mesotrypsin. Here, we will dissect the mechanisms responsible for these affinity enhancements and design strategies to exploit this information toward development of more potent and selective polyvalent trypsin inhibitors. In addition to developing three complementary strategies, each of which has high potential to produce the desired selective inhibitors of human trypsins, our project will provide broader insights that can aid future development of inhibitors for many other important trypsin-like proteases. Finally, the novel methodology developed here for mapping protein-protein interaction (PPI) affinity and specificity landscapes will be of broad utility for characterizing the sequence and structural constraints governing affinity and selectivity of functional protein interactions in many other diverse systems.