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High-Throughput Assessment of De Novo Protein Design: Generation of Molecular Probes for Guanine Exchange Factors

从头蛋白质设计的高通量评估：鸟嘌呤交换因子分子探针的生成

基本信息

批准号：
9911096
负责人：
David Thieker
金额：
$ 6.53万
依托单位：
UNIV OF NORTH CAROLINA CHAPEL HILL
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-01-09 至 2021-01-08
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/9911096
关键词：
Affinity Amino Acids Binding Binding Sites Biological Process Biological Sciences Biosensor Cancer Biology Cell Proliferation Cells Chimeric Proteins Communities Complex Crystallization Data Development Disease Engineering Environment Equilibrium Evaluation Fluorescence Generations Genes Goals Guanine Guanine Nucleotide Exchange Factors Guanosine Triphosphate Phosphohydrolases In Vitro Knowledge Learning Link Malignant Neoplasms Methods Microinjections Molecular Molecular Probes Mutation Nature Oligonucleotides Outcome Play Procedures Process Protein Engineering Proteins Protocols documentation Ramp Reagent Reporting Reproducibility Research Role Sample Size Sampling Scientist Side Signal Transduction Structural Protein Techniques Technology Testing Time Weight Yeasts base biophysical model design fluorophore gene synthesis high throughput screening high throughput technology improved in silico inhibitor/antagonist interest model design nanomolar novel process optimization programs protein complex protein protein interaction protein structure protein structure function screening small molecule small molecule inhibitor therapeutic target tool

项目摘要

Knowledge of the underlying principles of protein-protein interactions facilitates the design of proteins with novel functions that remain unobserved in nature and create new opportunities for scientists to dissect the molecular basis for diseases. Although significant advancements in the field have been made, evaluation of the computational design process by expressing proteins in vitro has been limited to small sample sizes due to constraints associated with gene synthesis. Recent advances in the field of oligonucleotide synthesis have enabled the high-throughput screening of designs with yeast display. We will harness this technology to assess new methods for packing amino acids at protein interfaces and to determine ideal score term targets for designed models. During this process, we will develop proteins that inhibit guanine exchange factors (GEFs), which are critical for cellular proliferation and have thereby garnered significant interest as therapeutic targets for cancer. We also aim to develop novel biosensors that are capable of reporting GEF activation by engineering a binding site into the SnapTag and HaloTag constructs. These results are expected to have an important positive impact for the field of protein engineering, ultimately providing new opportunities for the development of reagents that enable the scientific community to advance our understanding of biological processes.

蛋白质-蛋白质相互作用的基本原理的知识有助于设计具有新功能的蛋白质，在自然界中尚未观察到，并创造了新的机会，科学家们剖析疾病的分子基础。虽然在这方面取得了重大进展，领域已经取得了，通过表达蛋白质的计算设计过程的评价，由于与基因合成相关的限制，体外研究仅限于小样本量。寡核苷酸合成领域的最新进展使得高通量寡核苷酸合成成为可能。用酵母展示筛选设计。我们将利用这项技术来评估新的方法，用于在蛋白质界面包装氨基酸，并确定理想的评分项目标，设计模型。在这个过程中，我们将开发抑制鸟嘌呤交换的蛋白质因子（GEF），这是细胞增殖的关键，从而获得了显着的作为癌症的治疗靶点。我们还致力于开发新型生物传感器，能够通过将结合位点工程化到SnapTag和HaloTag中来报告GEF激活结构。这些成果预计将对该领域产生重要的积极影响，蛋白质工程，最终为试剂的开发提供了新的机会，使科学界能够推进我们对生物过程的理解。