De novo design of a generalizable protein biosensor platform for point-of-care testing

用于即时测试的通用蛋白质生物传感器平台的从头设计

• 批准号: 10836196
• 负责人: Hsien Wei YEH
• 金额: $ 24.9万
• 依托单位: UNIVERSITY OF CALIFORNIA SANTA CRUZ
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10836196
• 关键词: 2019-nCoV; Address; Affinity; Algorithms; Antibodies; Area; Basic Science; Binding; Binding Proteins; Biological Assay; Biological Markers; Bioluminescence; Biosensor; Body Fluids; Botulinum Toxins; Bypass; COVID-19; COVID-19 pandemic; Cardiac; Caring; Clinic; Clinical; Collection; Color; Colorimetry; Consumption; Coupled; Coupling; Creativeness; Darkness; Detection; Development; Development Plans; Devices; Diagnostic; Diagnostic Reagent; Diagnostic Services; Directed Molecular Evolution; Disease; Drops; ERBB2 gene; Economics; Energy Transfer; Engineering; Enzyme-Linked Immunosorbent Assay; Equilibrium; Event; Fc domain; Future; Gene Order; Goals; Health Priorities; Healthcare; Hepatitis B Antibodies; Hepatitis B Virus; Home; Hospitals; Human; Incubated; Interleukin-6; Light; Luciferases; Measurable; Measures; Medical; Mentors; Mentorship; Methods; Mission; Modality; Molecular; Molecular Conformation; Monitor; Monoclonal Antibodies; Names; Oligonucleotide Microarrays; Patients; Peptides; Phase; Protein Engineering; Proteins; Published Comment; Reporter; Reporting; Research; Research Personnel; SARS-CoV-2 antibody; Sampling; Serology test; Signal Transduction; Specimen; Surface; System; Technology; Therapeutic; Thermodynamics; Time; Treatment outcome; Troponin I; United States National Institutes of Health; Work; Yeasts; antibody detection; career; career development; clinically relevant; complement system; design; disability; emergency settings; flu; health care availability; health care quality; health care service; improved; instrument; interest; luminescence; molecular diagnostics; neutralizing antibody; novel; pandemic impact; pathogen; personalized medicine; point of care; point of care testing; point-of-care diagnostics; precision medicine; protein biomarkers; ratiometric; receptor; receptor binding; seasonal influenza; sensor; synergism; systemic inflammatory response; tv watching

úú PROJECT SUMMARY/ABSTRACT Delivering diagnostic services at the point-of-care (POC) can improve the quality of healthcare in clinics, in emergency settings, or at home, which can potentially ease hospitals’ burden, for instance, during the COVID- 19 pandemic. Precision and personalized medicine revolution also require POC testing to provide readily available biomarker information to clinicians. The goal of this career development proposal is to create fast, inexpensive, sensitive, and reliable molecular diagnostics to address the 21st-century healthcare challenges. The central hypothesis is that we can efficiently utilize computational protein design to create modular allosteric protein switches, named LOCKR (Latching Orthogonal Cage–Key pRotein), that enable the rapid and reversible conformational changes upon interaction. As a proof of principle, we demonstrate that LOCKR- based biosensors can be configured to produce bioluminescence upon the addition of clinical targets (e.g., botulinum toxin, cardiac troponin I, HER2 receptor, Fc domain, anti-HBV mAb, anti-SARS-CoV2 antibodies, and SARS-CoV2 receptor-binding domain/spike protein, Fig 1 and 2) in homogeneous “all-in-solution” assays. Due to the modularity of LOCKR sensor platform and the advance in de novo binder design for arbitrary protein targets, we proposed the integration of both features as the universal strategy to develop tailored biosensors for user-defined targets. The main specific aims for the independent phase are to iteratively expand LOCKR-based diagnostics with the synergy of (1) de novo protein binder design to directly detect various disease protein biomarkers, and (2) indirectly detect the antibodies that compete with the designed interface, as POC devices; and (3) to repurpose the original luminescence signal with other compatible readouts by exchanging the reporter modules. For more specific proof-of-concept projects during the mentored phase, I describe in Aim 1 the use of state-of-the-art computational protein design methods to create an interleukin-6 binder and biosensor. In Aim 2, I propose a general way to develop antibody biosensors by demonstrating COVID-19 serological tests as an example. With my expertise in biosensor engineering, I attempt in Aim 3 to develop a ratiometric bioluminescence resonance energy transfer (BRET) biosensor to analyze the HBV antibody and a colorimetric biosensor to measure human cardiac troponin I level. Ultimately, I anticipate this new sensor platform is significant for the development of robust protein sensors that will be broadly applicable to arbitrary targets and enabling its POC compatible readouts for future diagnostics.

úd项目摘要/摘要 在医疗点（POC）提供诊断服务可以提高诊所的医疗保健质量 例如 19大流行。精度和个性化医学革命还需要POC测试才能轻松提供 向临床医生提供的生物标志物信息。这项职业发展建议的目标是快速创建 廉价，敏感且可靠的分子诊断，以应对21世纪的医疗保健挑战。 中心假设是我们可以有效利用计算蛋白设计来创建模块化 变构蛋白开关，名为Lockr（闩锁正交笼 - 键蛋白），可以快速 相互作用时可逆的构象变化。作为原则的证明，我们证明了Lockr- 可以将基于的生物传感器配置为在添加临床目标时产生生物发光（例如 肉毒杆菌毒素，心脏肌钙蛋白I，HER2受体，FC结构域，抗HBV MAB，抗SARS-COV2抗体， 和SARS-COV2受体结合域/尖峰蛋白，图1和2） 测定。由于Lockr传感器平台的模块化以及从头粘合剂设计的进步 任意蛋白质靶标，我们提出了两种特征作为发展的普遍策略的整合 针对用户定义目标的量身定制的生物传感器。独立阶段的主要具体目的是 迭代地扩展基于lockr的诊断，其协同作用（1）从头蛋白质粘合剂设计直接 检测各种疾病蛋白生物标志物，（2）间接检测 设计的界面是POC设备； （3）用其他 通过交换记者模块来兼容读数。对于更具体的概念验证项目 修改阶段，我在AIM 1中描述了最先进的计算蛋白设计方法的使用 创建白介素6粘合剂和生物传感器。在AIM 2中，我提出了一种开发抗体的一般方法 生物传感器通过证明COVID-19的血清学检测为例。有了我在生物传感器方面的专业知识 工程学，我试图在AIM 3中开发比率的生物发光共振能量转移（BRET） 生物传感器分析HBV抗体和比色生物传感器来测量人类心脏肌钙蛋白I 等级。最终，我预计这个新的传感器平台对于稳健蛋白质的开发很重要 传感器将广泛适用于任意目标并启用其POC兼容读数的传感器 诊断。