Engineering of Proteins for Crystallography

晶体学蛋白质工程

• 批准号: 8534193
• 负责人: Zygmunt S Derewenda
• 金额: $ 39.14万
• 依托单位: UNIVERSITY OF VIRGINIA
• 依托单位国家: 美国
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-30 至 2015-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8534193
• 关键词: Address; Affect; Algorithms; Amino Acids; Bioinformatics; Biological; Biology; Collaborations; Collection; Communicable Diseases; Communities; Complex; Crystallization; Crystallography; Development; Drug Design; Drug Targeting; Engineering; Entropy; Evaluation; Failure; Gene Expression; Generations; Glutamine; Goals; Heteronuclear NMR; Human; Individual; Investigation; Membrane Proteins; Methodology; Methods; Molecular; Mutagenesis; Mutation; NMR Spectroscopy; National Institute of Allergy and Infectious Disease; Nature; Online Systems; Performance; Phase; Physical Chemistry; Physiology; Production; Property; Protein Engineering; Protein Structure Initiative; Proteins; Protocols documentation; Recombinant Proteins; Research; Research Personnel; Roentgen Rays; Sampling; Site-Directed Mutagenesis; Solubility; Solutions; Solvents; Speed; Staging; Structure; Surface; Surface Properties; Synthetic Genes; Testing; Time; Variant; base; computer studies; cost; design; design and construction; globular protein; lysylglutamic acid; molecular mechanics; novel; protein complex; protein structure; research study; screening; structural biology; structural genomics; success; tool

DESCRIPTION (provided by applicant): In spite of its enormous successes, structural biology is severely limited by the low success rates of macromolecular crystallization, and by the poor performance of many samples in NMR. Many valuable, biomedically important targets elude crystallization attempts, and overall high costs of structure determination are due primarily to the labor and time-intensive screening of targets at the stages of protein production, crystallization and initial HSQC spectra collection. Our research will address this bottleneck, through development of protein engineering strategies that allow for rational design of target variants with enhanced solubility, stability, and crystallizability or performance in NMR, and implementation of web-based, publicly available servers that facilitate application of these strategies. During the previous phase, we demonstrated that protein crystallization can be rationally induced by surface engineering based on the premise of surface entropy reduction (SER), i.e. mutagenesis of large, polar and solvent exposed amino acids, such as Lys, Glu and Gln, with small residues, e.g. Ala. Further, we designed and implemented the first generation XtalPred and SERp servers, which offer automated evaluation of protein's propensity to crystallize and design of variants with enhanced crystallizability based on the SER strategy. These tools have been used successfully by thousands of investigators world-wide, and helped solve nearly 170 crystal structures, including those of novel globular and membrane proteins, complexes and drug- targets in drug design pipelines. We now propose to pursue further experimental and computational studies of the relationships between physical chemistry of the protein surface and its solution properties. Specifically, we will investigate how surface entropy reduction affects protein solubility and stability, and how protein surface properties impact on the quality of heteronuclear NMR spectra. We will design and implement second generation XtalPred and SERp algorithms, with numerous new features, to achieve higher success rates for prediction of protein crystallizability and for design of variants with higher crystallizability, solubility, and with enhanced performance in NMR spectroscopy. The two second generation servers will be integrated into an interoperable network with the fold-prediction server FFAS03, and we will design a Protein Construct Design Metaserver (PCDM) making it possible to access the entire toolbox from a single GUI, proceeding from prediction to interactive design of primers and/or synthetic genes for expression of targets. Finally, to validate the methods, we will test them using a selection of biologically relevant protein targets.

描述（由申请人提供）：尽管取得了巨大的成功，但结构生物学受到大分子结晶成功率的低成功率，以及许多样本在NMR中的性能不佳。许多有价值的，生物医学上重要的目标避免了结晶的尝试，而整体结构确定的总成本主要是由于对蛋白质生产，结晶和初始HSQC光谱收集阶段的目标和时间密集型筛查。我们的研究将通过制定蛋白质工程策略来解决这一瓶颈，这些策略允许在NMR中使用增强的溶解度，稳定性和结晶性或性能以及实施基于Web的公开服务器，以促进这些策略的应用。在上一个阶段，我们证明了蛋白质结晶可以通过表面工程基于表面熵还原（SER）的前提，即大型，极性和溶剂暴露的氨基酸（例如Lys，Glu和Gln）的诱变，例如，lys，glu和gln的诱变，并具有小型残留物，例如。此外，我们设计并实施了第一代Xtalpred和SERP服务器，这些服务器可自动评估蛋白质的倾向，并根据SER策略具有增强的结晶性结晶和设计变体的倾向。这些工具已被全球成千上万的研究人员成功地使用，并帮助解决了近170种晶体结构，包括新型球状和膜蛋白，配合物和药物设计管道中的药物靶标的结构。现在，我们建议对蛋白质表面物理化学及其溶液特性之间的关系进行进一步的实验和计算研究。具体而言，我们将研究表面熵的还原如何影响蛋白质溶解度和稳定性，以及蛋白质表面特性如何影响异核NMR光谱的质量。我们将设计和实施具有许多新功能的第二代XTALPRED和SERP算法，以实现更高的成功率，以预测蛋白质的结晶性，并设计具有更高结晶性，溶解度以及NMR光谱性能增强的变体。第二代服务器将与折叠预测服务器FFAS03集成到可互操作的网络中，我们将设计蛋白质构造设计元标准器（PCDM），从而可以从单个GUI访问整个工具箱，从单个GUI到互动到引物和/或合成基因以表达目标的互动设计。最后，为了验证这些方法，我们将使用一系列与生物学相关的蛋白质靶标进行测试。