Developing cell-penetrating miniproteins as a new class of therapeutics

开发细胞穿透微型蛋白作为一类新型疗法

基本信息

批准号：
10454275
负责人：
Gabriel Jacob Rocklin
金额：
$ 19.16万
依托单位：
NORTHWESTERN UNIVERSITY AT CHICAGO
依托单位国家：
美国
项目类别：
财政年份：
2021
资助国家：
美国
起止时间：
2021-08-01 至 2023-07-31
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10454275
关键词：
Address Affinity Amino Acids Area Autoimmunity Binding Proteins Biological Assay Biology Cell Line Cell membrane Cells Cellular Membrane Charge Clinical Cytolysis Cytosol Data Development Disease Dose Drug Targeting Endosomes Engineering Ensure Escherichia coli Future Goals Hand Human Hydrophobicity Incubated Individual Learning Length Libraries Link Lysosomes Malignant Neoplasms Mass Spectrum Analysis Measurement Measures Medicine Methods Modeling Peptides Pharmaceutical Preparations Plasma Cells Property Protein Engineering Proteins Proteomics Recombinants Recovery Risk Sampling Structure Structure-Activity Relationship Surface Technology Testing Therapeutic Update Ursidae Family Validation base course development design drug development improved insight iterative design large scale data machine learning prediction multiplex assay nanomolar nervous system disorder new therapeutic target novel drug class novel strategies novel therapeutic intervention novel therapeutics peptide drug pre-clinical predictive modeling protein protein interaction small molecule success supervised learning therapeutic protein

项目摘要

Project Summary Current protein therapeutics have a major limitation: they generally cannot cross the cellular membrane or interact with cytosolic targets. The ability to design protein therapeutics that enter the cell cytosol would enable new therapeutic strategies across many disease areas, including cancer, autoimmunity, and neurological disease. Therapeutic “miniproteins” (30-60 residues in length) have the potential to address this challenge, and several miniproteins capable of efficiently reaching the cell cytosol have recently been identified. However, we lack a general understanding of the “design rules” for cell-penetrating miniproteins, limiting the development of this class of molecules. Furthermore, current approaches to measure cytosolic delivery require measuring each protein individually, which is slow and labor intensive. This makes it impossible to test large numbers of miniproteins to develop a robust, quantitative understanding of the determinants of cytosolic delivery. In this exploratory project, we will develop a new approach to measure delivery for each different protein in a large mixed pool, using targeted mass spectrometry to individually identify each miniprotein sequence. In our approach, a soluble mixed pool containing thousands of designed miniprotein sequences is incubated with cells, and miniproteins that enter those cells are captured by a cytosolic target. Miniproteins captured by the target are then purified out of the cellular contents and identified and quantified using targeted proteomics. The amount of each protein in the captured sample (relative to the starting sample) will provide a quantitative measure of delivery efficiency. This approach is unprecedented, and we will test and optimize this approach using different positive and negative control miniproteins, different library sizes, and different cell lines. With this method in hand, we will use approaches we previously pioneered to computationally design thousands of candidate cell-penetrating miniproteins with intentionally diverse sequence and structural properties. We will then quantify cytosolic delivery for these new proteins using our new high-throughput approach, creating unprecedented large-scale data on delivery efficiency. We will then use these data to build machine learning models that predict miniprotein delivery based on sequence and structural properties. Finally, we will repeatedly iterate, designing new miniprotein libraries based on our predictive models of delivery, testing these designs using our high-throughput experimental approach, and further updating our models. This iterative design-test- learn approach will build a robust, predictive understanding of the determinants of delivery. Ultimately, the ability to design cell-penetrating miniproteins will unlock a wide range of new therapeutic targets inside the cell.

项目概要目前的蛋白质疗法有一个主要限制：它们通常不能穿过细胞膜或与细胞质靶点相互作用的能力将使得设计进入细胞质的蛋白质疗法成为可能。跨许多疾病领域的新治疗策略，包括癌症、自身免疫和神经系统疾病治疗性“微型蛋白”（长度为 30-60 个残基）有可能解决这一挑战，并且然而，最近已经鉴定出几种能够有效到达细胞质的微型蛋白。对细胞穿透微型蛋白的“设计规则”缺乏总体了解，限制了其发展此外，目前测量细胞质递送的方法需要测量每一种分子。单独检测蛋白质，这既缓慢又费力，这使得不可能对大量蛋白质进行测试。微型蛋白，以对胞质递送的决定因素建立可靠的定量理解。在这个探索性项目中，我们将开发一种新方法来测量每种不同蛋白质在大型混合库，使用靶向质谱法单独识别我们的每个微型蛋白质序列。方法，将包含数千个设计的小蛋白序列的可溶性混合库与细胞一起孵育，进入这些细胞的微型蛋白被胞质靶标捕获。然后纯化出细胞内容物并使用靶向蛋白质组学进行鉴定和定量。捕获样品中的每种蛋白质（相对于起始样品）将提供定量测量这种方法的交付效率是前所未有的，我们将使用不同的方法来测试和优化这种方法。阳性和阴性对照小蛋白、不同的文库大小和不同的细胞系。有了这个方法，我们将使用我们之前开创的方法来计算设计数千个我们将有意选择具有不同序列和结构特性的候选细胞穿透小蛋白。然后使用我们新的高通量方法量化这些新蛋白质的胞质传递，创建前所未有的关于交付效率的大规模数据然后我们将使用这些数据来构建机器学习。最后，我们将重复基于序列和结构特性预测微蛋白递送的模型。迭代，根据我们的预测交付模型设计新的微型蛋白库，测试这些设计使用我们的高通量实验方法，并进一步更新我们的模型。学习方法将建立对交付的决定因素的强大的、预测性的理解，最终是能力。设计细胞穿透性微型蛋白将在细胞内解锁一系列新的治疗靶点。