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NMR Resonance Assignment Methodology: Characterizing Large Sparsely Labeled Glycoproteins.

Gordon R Chalmers¹, Alexander Eletsky¹, Laura C Morris¹

¹Complex Carbohydrate Research Center, University of Georgia, Athens, GA 30602, USA.

Journal of Molecular Biology

|April 30, 2019

Summary

This summary is machine-generated.

A new nuclear magnetic resonance (NMR) method enables resonance assignment for sparsely labeled proteins, crucial for characterizing complex proteins like glycoproteins. This technique aids structural studies of proteins expressed in mammalian cells.

Keywords:

genetic algorithm ligand docking mammalian cell culture molecular dynamics sialyltransferase

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Methods to Identify the NMR Resonances of the 13C-Dimethyl N-terminal Amine on Reductively Methylated Proteins

Methods to Identify the NMR Resonances of the 13C-Dimethyl N-terminal Amine on Reductively Methylated Proteins

Published on: December 12, 2013

Area of Science:

Biochemistry
Structural Biology
Biophysics

Background:

Protein structure determination using Nuclear Magnetic Resonance (NMR) typically relies on uniform isotopic labeling.
This uniform labeling approach becomes challenging for larger proteins and those expressed in mammalian cells, such as glycoproteins.
Efficient assignment of NMR resonances is critical for understanding protein structure and function.

Purpose of the Study:

To develop and present an alternative protocol for NMR resonance assignment in sparsely labeled proteins.
To enable structural characterization of proteins that are difficult to study with traditional methods, particularly those expressed in mammalian systems.
To facilitate the study of glycoproteins and other complex biological molecules.

Main Methods:

A novel protocol for assigning NMR resonances of proteins with sparse isotopic labeling (e.g., single amino acid type enrichment with 15N or 13C).
Utilizes extended 2D NMR experiments (correlated chemical shifts, NOEs, residual dipolar couplings) compared with molecular dynamics predictions.
Employs a genetic algorithm-based software package, ASSIGN_SLP_MD, for optimal pairing of experimental and predicted data.
Application to the 36-kDa rST6Gal1 protein with 15N-labeled phenylalanines, validated by single-point mutations.

Main Results:

Successful application of the sparse labeling protocol to the rST6Gal1 protein.
Validation of resonance assignments through site-directed mutagenesis.
Demonstrated utility in evaluating substrate analog binding within the protein's active site using prior paramagnetic relaxation enhancement data.

Conclusions:

The described protocol provides an effective strategy for NMR resonance assignment in sparsely labeled proteins.
This method significantly expands the scope of proteins amenable to structural characterization, including those produced in mammalian cells.
Opens new avenues for structural studies of glycoproteins and other challenging protein targets.