Sparse NMR Labeling Approach to Glycoprotein Structure and Function

糖蛋白结构和功能的稀疏 NMR 标记方法

基本信息

批准号：
10388355
负责人：
JAMES H. PRESTEGARD
金额：
$ 30.2万
依托单位：
UNIVERSITY OF GEORGIA
依托单位国家：
美国
项目类别：
财政年份：
2019
资助国家：
美国
起止时间：
2019-07-01 至 2024-04-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10388355
关键词：
3-Dimensional Address Adopted Affect Amides Amino Acids Binding Proteins Biological Biology Cell Culture Techniques Chemicals Collection Communities Computer Models Computer software Crystallization Data Data Analyses Data Set Development Disease Equilibrium Exclusion Genetic Programming Glycoproteins Goals HMQC Hand Health Homology Modeling Human Isotope Labeling Isotopes Label Magnetism Mammalian Cell Manuals Measurement Measures Methods Modeling Motion Mutation Nuclear Nuclear Magnetic Resonance Output Physiology Procedures Process Production Program Efficiency Proteins Protocols documentation Protons Relaxation Research Personnel Residual state Resolution Route Scheme Site Source Structural Models Structure Surface System Technology Time Validation Weight Work X-Ray Crystallography base computer generated design experimental study glycoprotein structure glycosylation improved methyl group multiple data types mutant pathogen preservation prevent programs protein protein interaction protein structure simulation

项目摘要

SUMMARY Glycoproteins represent a class of mammalian proteins that presents challenges for structural and functional characterization, particularly if the native glycosylation, which affects structure, stability and interaction with other molecules, is to be preserved. The best route to proteins with native glycosylation is expression in mammalian cell cultures. Unfortunately, for X-ray crystallography, this produces proteins with heterogenous glycosylation, often preventing formation of suitable crystals. For traditional nuclear magnetic resonance (NMR) methods, this forces use of expensive substrates for isotopic labeling and prohibits the perdeuteration often required to maintain resolution for larger proteins. The investigators involved in this proposal have worked together to develop an efficient mammalian cell expression system that produces proteins sparsely labeled using a restricted set of less expensive isotope enriched amino acids and maintains resolution without the aid of perdeuteration. This has been accompanied by the development of resonance assignment programs and data analysis protocols that allow structural and functional characterization from basic, high sensitivity, two-(and three-)dimensional NMR experiments. This project is designed to turn those developments into an integrated protocol that can be adopted by an expanded community of users. It centers on the refinement of a software package that accomplishes NMR resonance assignment of sparsely labeled proteins. It will be bolstered by extensive validation of program output, introduction of new data types and data analysis methods, and extension of program capabilities to the refinement of computer-generated models for protein structure. The potential impact will be a new route to structure and function studies of a class of proteins intimately involved with human physiology and disease.

概括糖蛋白代表一类哺乳动物蛋白，对结构和功能表征，特别是如果天然糖基化影响结构，稳定性和与其他分子的相互作用将保留。与天然糖基化蛋白质的最佳途径是在哺乳动物细胞培养物中的表达。不幸的是，对于X射线晶体学，这会产生与异源糖基化，通常阻止形成合适的晶体。对于传统核磁场共振（NMR）方法，这种力使用昂贵的基材作为同位素标记，并禁止 perdeuteration通常需要维持较大蛋白质的分辨率。参与此参与的调查员提案共同开发了产生有效的哺乳动物细胞表达系统蛋白质使用一组限制的较低的同位素富集氨基酸并保持的蛋白质稀疏标记无助于perdeuteration的分辨率。这伴随着共振的发展分配程序和数据分析协议允许从结构和功能表征基本，高灵敏度，两（和三）维NMR实验。该项目旨在转动这些项目发展为一个集成协议，可以由扩展的用户社区采用。它以中心为中心关于完成稀疏标签的NMR共振分配的软件包的完善软件包蛋白质。通过广泛验证程序输出，引入新数据类型和数据，它将得到加强分析方法以及将程序功能扩展到计算机生成模型的完善蛋白质结构。潜在的影响将是一系列类别的结构和功能研究的新途径蛋白质密切参与人类生理和疾病。

项目成果

期刊论文数量（5）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

AssignSLP_GUI, a software tool exploiting AI for NMR resonance assignment of sparsely labeled proteins.

DOI：
10.1016/j.jmr.2022.107336
发表时间：
2022-12
期刊：
JOURNAL OF MAGNETIC RESONANCE
影响因子：
2.2
作者：
V. Williams, Robert;Rogals, Monique J.;Eletsky, Alexander;Huang, Chin;Morris, Laura C.;Moremen, Kelley W.;Prestegard, James H.
通讯作者：
Prestegard, James H.

Glycan Conformation in the Heavily Glycosylated Protein, CEACAM1.

DOI：
10.1021/acschembio.2c00714
发表时间：
2022-12-16
期刊：
ACS CHEMICAL BIOLOGY
影响因子：
4
作者：
Rogals, Monique J.;Eletsky, Alexander;Huang, Chin;Morris, Laura C.;Moremen, Kelley W.;Prestegard, James H.
通讯作者：
Prestegard, James H.

Using molecular dynamics trajectories to predict nuclear spin relaxation behaviour in large spin systems.