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创建了创新的平台产品，以改善结晶。第一阶段试图改善 结晶和样品处理效率高影响感染性疾病与蛋白质相关的蛋白质 将工程成核特征（ENF）纳入与与与 单晶和连续晶体学使用同步加速器X射线和游离电子激光（XFEL）LightsOrces。 蛋白质的晶体成核具有挑战性，最佳的工作流程仍然平均≥80-85％的失败率。 Denovx的ENF降低了晶核的热力学和动力学障碍，并将ENF与ENF与 微流动流结晶通过产生更多的固定和蛋白质晶体来使结构生物学受益 以高光彩X射线和通过 更有效地使用蛋白质资源。 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，该数据是冷冻EM和NMR结构的模型，以及 对公共卫生的益处来自对疾病起源的加速和扩展的理解， 进展和治疗。特定目标1-定义微流体蛋白流量结晶芯片格式和 合并ENF。使用AS基准选择碳水化的活性酶（Cazyme），ꞵ-内酰胺酶和 SARS-COV-2（例如NSP15，MPRO，PLPRO）蛋白质，收集复制（n≥6）结晶命中百分比，晶体 产量和发作时间数据，具有12个独特的ENF与聚二甲基硅氧烷（PDMS）/玻璃的控制表面 使用微匹配结晶的构造的微流体材料。识别出现的前四个ENF 可再现的改善效果增加了≥10％的结晶效果，晶体数量增加了20％ 产生的，或≥15％的结晶开始时间与对照。特定目标2-设计微流体 蛋白质流结晶平台编码可以产生和运输的ENF：（a）1-50 µm晶体 固定目标网格和流动的样品微吉注射，用于使用Xfels的连续飞秒晶体学， （b）传统单晶体衍射的50-100 µm蛋白质晶体。组装两个功能性PDM/玻璃 α-蛋白型具有≥3个流体添加点以操纵结晶条件，建立流体动力学 操作条件，并证明具有1-50 µm和50-100 µm蛋白晶体的有效运输 ≤25％的液滴大小变化（可能影响晶体尺寸）。特定目标3-蛋白质微流动流 使用精选的ENF和基准蛋白（Cazymes，ꞵ-内乳糖酶，SARS-COV-2）结晶化， 证明可再现（n≥6）提高了≥20％的晶体量增加，≥20％ 结晶开始时间的减少或晶体尺寸分布与对照组的狭窄≥20％。确认使用 蛋白质晶体的结构质量指标（例如，分辨率，R等）在±3 ESD中 PDB基准测试。预计微流体蛋白流量结晶将有效产生衍射 质量晶体以增强蛋白质结构测定研究的质量和数量。