Exploiting new approaches for selective inhibition of trypsins

开发选择性抑制胰蛋白酶的新方法

基本信息

批准号：
10338695
负责人：
Evette S Radisky
金额：
$ 30.14万
依托单位：
MAYO CLINIC JACKSONVILLE
依托单位国家：
美国
项目类别：
财政年份：
2022
资助国家：
美国
起止时间：
2022-01-01 至 2025-11-30
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10338695
关键词：
Active Sites Affinity Allosteric Regulation Allosteric Site Binding Binding Proteins Biochemical Biological Biological Models Biological Process Calibration Catalysis Computer Analysis Data Development Dimerization Directed Molecular Evolution Disease Disease model Engineering Enzymes Family Future Generations Goals Heterogeneity Human Individual International Libraries Ligands Machine Learning Malignant Neoplasms Maps Mediating Medical Membrane Proteins Methodology Methods Molecular Molecular Conformation Mutation Nature Pancreatitis Pathologic Pathology Peptide Hydrolases Peptides Pharmaceutical Preparations Pharmacology Play Polyvalence Positioning Attribute Pre-Clinical Model Process Protease Inhibitor Protein Isoforms Proteins Proteome Publishing Regulation Role Serine Protease Shapes Specificity Structure Surface System Therapeutic Therapeutic Agents Trypsin Trypsin Inhibitors Validation X-Ray Crystallography Yeasts base combinatorial design dimer in silico inhibitor inhibitor therapy innovation insight lead optimization mesotrypsin molecular dynamics molecular modeling molecular recognition next generation sequencing novel novel strategies novel therapeutics protein complex protein protein interaction screening therapeutic target tool trypsin-like serine protease virtual screening

项目摘要

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.

项目概要/摘要人类胰蛋白酶异构体、胰蛋白酶 1、胰蛋白酶 2 和中胰蛋白酶是与胰蛋白酶相关的蛋白酶。癌症和胰腺炎的疾病过程，并可能提供可行的治疗靶点。胰蛋白酶属于胰蛋白酶样酶大家族具有相似的活性位点拓扑结构，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，因为药理学工具可以更好地定义这些单独的酶在疾病中的功能，并评估胰蛋白酶抑制作为临床前疾病模型的治疗策略。在这个项目中，我们将采取多管齐下的方法来开发有效和选择性抑制每个人类的新策略胰蛋白酶同种型。 (1) 我们的初步数据揭示了之前未曾怀疑的自抑制构象具有可用于抑制作用的配体可靶向变构位点的胰岛胰蛋白酶。我们将使用高吞吐量虚拟筛选和基于结构的命中到先导化合物优化，以开发有效和选择性的药物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 结构域可以被设计为创建更具选择性的基于蛋白质的胰蛋白酶样蛋白酶抑制剂通过使用酵母表面展示（YSD）平台进行定向进化。为了进一步优化此类抑制剂，我们寻求生成结合特异性景观的综合图谱，可以针对任何抑制剂内可能的突变组合，预测对抑制剂亲和力的影响以及对一组目标蛋白酶的特异性。我们将通过整合YSD组合来完成这项任务使用下一代测序 (NGS)、机器学习 (ML) 方法进行文库筛选，以及实验校准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识别最有效和最具选择性的 Kunitz 域针对每种人类胰蛋白酶都可以实现这一目标。 (3) 我们的初步数据表明通过能够同时结合两个胰蛋白酶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来开发更有效和更具选择性的多价胰蛋白酶的策略抑制剂。除了制定三种互补策略外，每一种策略都具有很大的潜力生产所需的人类胰蛋白酶选择性抑制剂，我们的项目将提供更广泛的见解，可以帮助未来开发许多其他重要的胰蛋白酶样蛋白酶的抑制剂。最后，新颖的方法论这里开发的用于绘制蛋白质-蛋白质相互作用 (PPI) 亲和力和特异性景观的技术将具有广泛的应用用于表征控制功能亲和力和选择性的序列和结构约束的实用程序许多其他不同系统中的蛋白质相互作用。