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.

项目概要 DeNovX 创建了改进结晶的创新平台产品。 高影响传染病相关蛋白质的结晶和样品处理效率 将工程成核功能 (ENF) 融入微流控结晶芯片中，兼容 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，即使是最佳工作流程，失败率仍平均≥ 80-85%。 DeNovX 的 ENF 减少了晶体成核的热力学和动力学障碍，并将 ENF 与 微流体流动结晶通过产生更多的蛋白质晶体来固定和纯化，从而有利于结构生物学 在新兴的“破坏前衍射”策略中使用高亮度 X 射线和通过 更有效地利用蛋白质资源仍然是一项基准技术。 提供无与伦比的原子分辨率数据，用作冷冻电镜和核磁共振结构的模型，以及 对公共卫生的好处来自于对疾病起源的加速和扩大的了解， 具体目标 1 - 定义微流体蛋白流结晶芯片格式和 纳入 ENF 作为基准选择碳水化合物活性酶 (CAzyme)、ꞵ-内酰胺酶和 SARS-CoV-2（例如，Nsp15、Mpro、PLpro）蛋白，收集重复（n≥6）结晶命中率、晶体 聚二甲基硅氧烷 (PDMS)/玻璃的 12 个独特 ENF 与控制表面的产量和起始时间数据 使用微批量结晶来确定显示的前四种 ENF 的微流体材料。 结晶命中率增加 ≥ 10%、晶体数量增加 ≥ 20% 的可重复性改进 产生，或与对照相比，结晶起始时间减少 ≥ 15% 具体目标 2 - 设计微流体。 包含 ENF 的蛋白质流结晶平台，可以生产和运输： (a) 1-50 µm 晶体 使用 XFEL 进行连续飞秒晶体学的固定目标网格和流动样品微射流注射， (b) 用于传统单晶衍射的 50-100 µm 蛋白质晶体组装两个功能性 PDMS/玻璃。 具有 ≥ 3 个流体添加点的 α-原型用于操纵结晶条件，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 液滴尺寸的平均变化≤ 25%（可能影响晶体尺寸）。具体目标 3 - 对于蛋白质微流体流动。 使用精选 ENF 和基准蛋白（CAzymes、ꞵ-内酰胺酶、SARS-CoV-2）进行结晶， 表现出可重复的 (n ≥ 6) 改善，生成的晶体数量增加 ≥ 20%，≥ 20% 与对照相比，结晶起始时间缩短，或晶体尺寸分布缩小 ≥ 20%。 同步加速器 X 射线，蛋白质晶体的结构质量指标（例如分辨率、R 等）在 ± 3 esds 范围内 PDB 基准预计微流体蛋白质流结晶将有效地产生衍射。 优质晶体可提高蛋白质结构测定研究的质量和数量。