Easily Used Kits to Evolve Reagents that Covalently Tag and Inactivate Proteins

易于使用的试剂盒可进化出共价标记和灭活蛋白质的试剂

基本信息

批准号：
10478279
负责人：
STEVEN A BENNER
金额：
$ 31.39万
依托单位：
FOUNDATION FOR APPLIED MOLECULAR EVOLUTN
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：
2021-09-01 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10478279
关键词：
2019-nCoV Acylation Address Amides Amino Acid Sequence Antibodies Area Binding Binding Proteins Bioinformatics Biological Biology Biomedical Research Brain COVID-19 detection COVID-19 pandemic Catalytic Antibodies Catalytic RNA Cell surface Cells Chemicals Chemistry Clinical Laboratory Information Systems DNA DNA biosynthesis DNA sequencing Data Development Diagnostic Disease Disease Management Doxorubicin Enzymes Esters Evolution Feedback Foundations GPC3 gene Image In Vitro India Information Systems Knowledge Laboratories Language Lysine Malignant neoplasm of liver Maps Measures Medical Medical Research Medicine Modification Molecular Evolution National Institute of General Medical Sciences Organic Chemistry Outcome Peptides Performance Pharmaceutical Preparations Physiological Process Protein Engineering Protein Sequence Analysis Proteins Reaction Reaction Time Reagent Reproducibility Research Personnel Rest Ribosomal RNA Role Science Ships Site Sodium Chloride Specificity Surgeon Synthesis Chemistry System Technology Temperature Testing Thermodynamics Toxin Translating Vision Work acyl group amino group base biological systems cancer cell cell killing combinatorial chemistry design drug discovery gene synthesis genetic information in vivo innovation invention meetings molecular recognition multiplex diagnostics new technology next generation sequencing protein function success synthetic biology tool tumor web-based tool

项目摘要

Easily Used Kits to Evolve Reagents that Covalently Tag and Inactivate Proteins Foundation for Applied Molecular Evolution Steven Benner ABSTRACT Under PAR-19-253, the NIGMS seeks new technologies that create a positive feedback loop that drives science forward by allowing new questions to be asked and new discoveries to be made, which in turn drives the development of new technologies. The Benner group has, for 30 years, contributed to this NIGMS vision, developing new technologies for NextGen DNA sequencing and NextGen DNA synthesis, bioinformatic and evolutionary analyses, dynamic combinatorial chemistry for drug discovery, protein engineering, and new platforms that make multiplexed diagnostics easy, platforms used today to manage the COVID pandemic. Here, we offer the NIGMS another transformative tool, a platform to allow researchers to choose a protein target and create a reagent (an AEGISZyme) that chemically transforms bound proteins. Such reagents have been sought for 40 years with only limited success. We will focus on one transformation: AEGISZymes that add an acyl group to an amino group on a lysine of the bound target, where the acylation reagent is an ester. This acylation may inactivate the targeted protein, allow- ing researchers to test hypotheses about the role of that protein in biology. It may carry a payload which, when internalized with the target protein, carry drugs or stabilized AEGISZymes into a cell. It may fluorescently tag the protein to help clinicians cut away fluorescing cancer cells selectively as they resect a tumor. To achieve this transformative and innovative outcome, we will apply laboratory in vitro evolution (LIVE) to artificially expanded genetic information systems (AEGIS). The platform will be delivered by meeting 3 Aims: Aim 1. We will use AEGIS-LIVE to deliver AEGISZymes that acylate lysines in target proteins with pass/fail reaction times of <10 sec-1. To test this, we will create these AEGISZymes that use a co-substrate carrying an ester group for three targets. Rates of the selected AEGISZymes will be quantitated, specificity will be metricked against similar targets with slightly different amino acid sequences, and modification sites will be found, Aim 2. We will use AEGIS-LIVE to deliver AEGISZymes that acylate lysines on researcher-chosen targets with turnover, with pass/fail turnovers of >1000 and kcat/KM of >105 M-1 sec-1. Turnover rates will be metricked under physiological and laboratory conditions, and correlated to duplex stability from thermodynamic data. Aim 3. We will use AEGIS-LIVE to deliver mirror AEGISZymes that are stable in biological systems, including transport into cells. This will allow AEGISZymes to be used in biological media, to support nanotrain toxin delivery, and to set the stage to use these molecules in vivo. Aim 4. We will test the scope of the platform to address design parameters, such as how long random regions should be, how good loops are as full protein surrogates, and how sequence space is searched. Last, to lay to rest any view that AEGIS-LIVE is too "cumbersome", we will create distributable kits that allow their recipients to make their own AEGISZymes. This is the ultimate in authentication and reproducibility.

易于使用的试剂盒可进化出共价标记和灭活蛋白质的试剂应用分子进化基金会史蒂文·本纳抽象的根据 PAR-19-253，NIGMS 寻求新技术来创建正反馈循环，以驱动通过允许提出新问题和做出新发现来推动科学前进，这反过来又推动新技术的开发。 Benner 集团 30 年来一直致力于实现 NIGMS 愿景，开发下一代 DNA 测序和下一代 DNA 合成、生物信息学和进化分析、药物发现的动态组合化学、蛋白质工程和新使多重诊断变得简单的平台，如今用于管理新冠疫情的平台。在这里，我们为 NIGMS 提供了另一个变革性工具，一个允许研究人员选择的平台蛋白质目标并创建一种试剂（AEGISZyme），以化学方式转化结合的蛋白质。这样的四十年来一直在寻找试剂，但只取得了有限的成功。我们将重点关注一种转化：AEGISZymes 将酰基添加到赖氨酸上的氨基上结合靶标，其中酰化试剂是酯。这种酰化可能会使目标蛋白失活，从而允许- 研究人员正在测试有关该蛋白质在生物学中的作用的假设。它可能携带一个有效负载，当与靶蛋白内化，将药物或稳定的 AEGISZymes 携带到细胞中。它可能会发出荧光标记这种蛋白质可以帮助临床医生在切除肿瘤时选择性地切除荧光癌细胞。为了实现这一变革性和创新性成果，我们将应用实验室体外进化（LIVE）人工扩展的遗传信息系统（AEGIS）。该平台将通过满足 3 个目标来实现：目标 1. 我们将使用 AEGIS-LIVE 交付 AEGISZymes，酰化目标蛋白中的赖氨酸（通过/失败）反应时间<10 sec-1。为了测试这一点，我们将创建这些 AEGISZymes，它们使用带有三个目标的酯基团。所选 AEGISZymes 的速率将被定量，特异性将被度量针对氨基酸序列略有不同的相似靶标，会发现修饰位点，目标 2. 我们将使用 AEGIS-LIVE 提供 AEGISZymes，在研究人员选择的目标上酰化赖氨酸周转率，通过/失败周转率 >1000，kcat/KM >105 M-1 sec-1。周转率将被衡量在生理和实验室条件下，并与热力学数据的双链体稳定性相关。目标 3. 我们将使用 AEGIS-LIVE 提供在生物系统中稳定的镜像 AEGISZymes，包括运输到细胞中。这将使 AEGISZymes 可用于生物介质，以支持纳米链毒素递送，并为在体内使用这些分子奠定基础。目标 4. 我们将测试平台的范围以解决设计参数，例如随机区域的长度应该是，循环作为完整蛋白质替代物有多好，以及如何搜索序列空间。最后，为了平息任何认为 AEGIS-LIVE 太“麻烦”的观点，我们将创建可分发的套件，允许他们的接受者可以制作自己的 AEGISZymes。这是最终的验证和再现性。