Microfluidic Protein Flow Crystallization Using Engineered Nucleation Features for Serial and Traditional Crystallography

使用工程成核特征进行串行和传统晶体学的微流蛋白流结晶

• 批准号: 10323393
• 负责人: Andrew H. Bond
• 金额: $ 31.32万
• 依托单位: DENOVX, LLC
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-08-01 至 2023-01-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10323393
• 关键词: 2019-nCoV; Address; Affect; Benchmarking; Biological Process; Carbohydrates; Communicable Diseases; Complement; Construction Materials; Cryoelectron Microscopy; Crystallization; Crystallography; Data; Data Collection; Disease; Drug Design; Engineering; Enzymes; Failure; Foundations; Glass; Goals; Health Benefit; Injections; Kinetics; Knowledge acquisition; Lactamase; Legal patent; Liquid substance; Methods; Microfluidics; Modeling; Outcome; Pharmacologic Substance; Phase; Photons; Productivity; Proteins; Public Health; Reproducibility; Research Personnel; Resolution; Resources; Roentgen Rays; Sampling; Small Business Innovation Research Grant; Source; Structure; Surface; Synchrotrons; System; Techniques; Thermodynamics; Time; X-Ray Crystallography; base; commercial application; cost; design; drug development; flexibility; improved; innovation; operation; polydimethylsiloxane; preservation; protein structure; prototype; public health research; small molecule; structural biology; tool; vaccine development; x-ray free-electron laser

PROJECT SUMMARY DeNovX creates innovative platform products that improve crystallization. Phase I seeks to improve the crystallization and sample handling efficiencies of high impact infectious disease related proteins by incorporating engineered nucleation features (ENFs) into microfluidic flow crystallization chips compatible with single crystal and serial crystallography using synchrotron X-ray and free electron laser (XFEL) lightsources. Crystal nucleation of proteins is challenging with the best workflows still averaging ≥ 80-85% failure rates. DeNovX’s ENFs reduce the thermodynamic and kinetic barriers to crystal nucleation, and combining ENFs with microfluidic flow crystallization benefits structural biology by producing more protein crystals for fixed and flowing sample targetry in the emerging “diffract before destroying” strategies with high brilliance X-rays and by more efficiently using the protein resources. X-ray crystallography remains a benchmark technique by providing unparalleled atomic resolution data that serve as models for cryo-EM and NMR structures, and benefits to Public Health derive from an accelerated and expanded understanding of disease genesis, progression, and therapy. Specific Aim 1 - Define microfluidic protein flow crystallization chip formats and incorporate ENFs. Using as benchmarks select carbohydrate active enzyme (CAzyme), ꞵ-lactamase, and SARS-CoV-2 (e.g., Nsp15, Mpro, PLpro) proteins, collect replicate (n ≥ 6) crystallization hit percentage, crystal yield, and onset time data with 12 unique ENFs vs. control surfaces for the polydimethylsiloxane (PDMS)/glass microfluidic materials of construction using microbatch crystallization. Identify the top four ENFs showing reproducible improvements of ≥ 10% increase in crystallization hits, ≥ 20% increase in the quantity of crystals generated, or ≥ 15% reduction in crystallization onset times vs. controls. Specific Aim 2 - Design a microfluidic protein flow crystallization platform incorporating ENFs that can produce and transport: (a) 1-50 µm crystals for fixed target meshes and flowing sample microjet injection for serial femtosecond crystallography using XFELs, and (b) 50-100 µm protein crystals for traditional single crystal diffraction. Assemble two functional PDMS/glass α-prototypes with ≥ 3 fluid addition points for manipulation of crystallization conditions, establish hydrodynamic conditions for operation, and demonstrate efficient transport of 1-50 µm and 50-100 µm protein crystals with ≤ 25% average change in droplet size (may affect crystal size). Specific Aim 3 - For protein microfluidic flow crystallization using select ENFs and benchmark proteins (CAzymes, ꞵ-lactamases, SARS-CoV-2), demonstrate reproducible (n ≥ 6) improvements of ≥ 20% increase in the quantity of crystals generated, ≥ 20% reduction in crystallization onset time, or ≥ 20% narrowing of crystal size distribution vs. controls. Confirm using synchrotron X-rays that structure quality metrics (e.g., resolution, R, etc.) of protein crystals are within ± 3 esds of PDB benchmarks. It is expected that microfluidic protein flow crystallization will efficiently produce diffraction quality crystals to enhance the quality and quantity of protein structure determination studies.

项目摘要 DeNovX创造创新的平台产品，改善结晶。第一阶段旨在改善 高影响传染病相关蛋白质的结晶和样品处理效率， 将工程化成核特征（ENF）结合到微流体流动结晶芯片中， 使用同步加速器X射线和自由电子激光（XFEL）光源的单晶和连续晶体学。 蛋白质的晶体成核具有挑战性，最佳工作流程的平均失败率仍≥ 80-85%。 DeNovX的ENF降低了晶体成核的热力学和动力学障碍， 微流控流动结晶通过产生更多的蛋白质晶体用于固定和 流动样品靶向技术在新兴的“先销毁后销毁”战略中使用高亮度X射线， 更有效地利用蛋白质资源。X射线晶体学仍然是一种基准技术， 提供无与伦比的原子分辨率数据，作为冷冻EM和NMR结构的模型， 对公共卫生的益处来自于对疾病成因的加速和扩展的理解， 进展和治疗。具体目标1 -定义微流体蛋白质流动结晶芯片格式和 纳入ENF。使用作为基准，选择碳水化合物活性酶（CAzyme）、β-内酰胺酶和 SARS-CoV-2（例如，Nsp 15、Mpro、PLpro）蛋白，收集重复样品（n ≥ 6）结晶命中百分比，晶体 聚二甲基硅氧烷（PDMS）/玻璃的12种独特ENF与对照表面的产率和起始时间数据 微流控材料的结构使用微批量结晶。确定前四个ENF显示 结晶命中率增加≥ 10%，晶体数量增加≥ 20%的可重现性改善 生成，或与对照相比结晶开始时间减少≥ 15%。具体目标2 -设计微流体 包含ENF的蛋白质流动结晶平台，可以产生和运输：（a）1-50 µm晶体， 固定的目标网格和流动的样品微射流注射用于使用XFEL的连续飞秒晶体学， 和（B）用于传统单晶衍射的50-100 μm蛋白质晶体。组装两个功能PDMS/玻璃 具有≥ 3个流体添加点的α-原型，用于控制结晶条件，建立流体动力学 操作条件，并证明1-50 µm和50-100 µm蛋白质晶体的有效运输， 液滴尺寸平均变化≤ 25%（可能影响晶体尺寸）。具体目标3 -用于蛋白质微流体流动 使用选择的ENF和基准蛋白（CAzymes、β-内酰胺酶、SARS-CoV-2）进行结晶， 证明了可重现性（n ≥ 6）改善，生成的晶体数量增加≥ 20%，≥ 20% 与对照相比，结晶开始时间缩短，或晶体粒度分布变窄≥ 20%。确认使用 同步加速器X射线结构质量度量（例如，分辨率、R等）的蛋白质晶体在± 3 esds内 PDB基准。预期微流控蛋白质流动结晶将高效地产生衍射 优质晶体，提高蛋白质结构测定研究的质量和数量。