NMR assignments of sparsely labeled proteins using a genetic algorithm

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

Not all proteins are amenable to uniform isotopic labeling with 13C and 15N, something needed for the widely used, and largely deductive, triple resonance assignment process. Among them are proteins expressed in mammalian cell culture where native glycosylation can be maintained, and proper formation of disulfide bonds facilitated. Uniform labeling in mammalian cells is prohibitively expensive, but sparse labeling with one or a few isotopically enriched amino acid types is an option for these proteins. However, assignment then relies on accessing the best match between a variety of measured NMR parameters and predictions based on 3D structure, often from X-ray crystallography. Finding this match is a challenging process that has benefitted from many computational tools, including trained neural nets for chemical shift prediction, genetic algorithms for searches through a myriad of assignment possibilities, and now AI-based prediction of high-quality structures for protein targets. AssignSLP_GUI, a new version of a software package for assignment of resonances from sparsely-labeled proteins, uses many of these tools. These tools and new additions to the package are highlighted in an application to a sparsely-labeled domain from a glycoprotein, CEACAM1.

Automated assignment of methyl NMR spectra from large proteins

As structural biology trends towards larger and more complex biomolecular targets, a detailed understanding of their interactions and underlying structures and dynamics is required. The development of methyl-TROSY has enabled NMR spectroscopy to provide atomic-resolution insight into the mechanisms of large molecular assemblies in solution. However, the applicability of methyl-TROSY has been hindered by the laborious and time-consuming resonance assignment process, typically performed with domain fragmentation, site-directed mutagenesis, and analysis of NOE data in the context of a crystal structure. In response, several structure-based automatic methyl assignment strategies have been developed over the past decade. Here, we present a comprehensive analysis of all available methods and compare their input data requirements, algorithmic strategies, and reported performance. In general, the methods fall into two categories: those that primarily rely on inter-methyl NOEs, and those that utilize methyl PRE- and PCS-based restraints. We discuss their advantages and limitations, and highlight the potential benefits from standardizing and combining different methods.

Backbone and methyl assignment of bacteriorhodopsin incorporated into nanodiscs

Resonance assignments are challenging for membrane proteins due to the size of the lipid/detergent-protein complex and the presence of line-broadening from conformational exchange. As a consequence, many correlations are missing in the triple-resonance NMR experiments typically used for assignments. Herein, we present an approach in which correlations from these solution-state NMR experiments are supplemented by data from ¹³C unlabeling, single-amino acid type labeling, 4D NOESY data and proximity of moieties to lipids or water in combination with a structure of the protein. These additional data are used to edit the expected peaklists for the automated assignment protocol FLYA, a module of the program package CYANA. We demonstrate application of the protocol to the 262-residue proton pump from archaeal bacteriorhodopsin (bR) in lipid nanodiscs. The lipid-protein assembly is characterized by an overall correlation time of 44 ns. The protocol yielded assignments for 62% of all backbone (H, N, C^α, C^β, C') resonances of bR, corresponding to 74% of all observed backbone spin systems, and 60% of the Ala, Met, Ile (δ1), Leu and Val methyl groups, thus enabling to assign a large fraction of the protein without mutagenesis data. Most missing resonances stem from the extracellular half, likely due intermediate exchange line-broadening. Further analysis revealed that missing information of the amino acid type of the preceding residue is the largest problem, and that 4D NOESY experiments are particularly helpful to compensate for that information loss.

NMR Resonance Assignment Methodology: Characterizing Large Sparsely Labeled Glycoproteins

Characterization of proteins using NMR methods begins with assignment of resonances to specific residues. This is usually accomplished using sequential connectivities between nuclear pairs in proteins uniformly labeled with NMR active isotopes. This becomes impractical for larger proteins, and especially for proteins that are best expressed in mammalian cells, including glycoproteins. Here an alternate protocol for the assignment of NMR resonances of sparsely labeled proteins, namely, the ones labeled with a single amino acid type, or a limited subset of types, isotopically enriched with ¹⁵N or ¹³C, is described. The protocol is based on comparison of data collected using extensions of simple two-dimensional NMR experiments (correlated chemical shifts, nuclear Overhauser effects, residual dipolar couplings) to predictions from molecular dynamics trajectories that begin with known protein structures. Optimal pairing of predicted and experimental values is facilitated by a software package that employs a genetic algorithm, ASSIGN_SLP_MD. The approach is applied to the 36-kDa luminal domain of the sialyltransferase, rST6Gal1, in which all phenylalanines are labeled with ¹⁵N, and the results are validated by elimination of resonances via single-point mutations of selected phenylalanines to tyrosines. Assignment allows the use of previously published paramagnetic relaxation enhancements to evaluate placement of a substrate analog in the active site of this protein. The protocol will open the way to structural characterization of the many glycosylated and other proteins that are best expressed in mammalian cells.

Measurement of residual dipolar couplings in methyl groups via carbon detection

Residual dipolar couplings (RDCs) provide both structural and dynamical information useful in the characterization of biological macromolecules. While most data come from the interaction of simple pairs of directly bonded spin-1/2 nuclei (¹H-¹⁵N, ¹H-¹³C, ¹H-¹H), it is possible to acquire data from interactions among the multiple spins of ¹³C-labeled methyl groups (¹H₃-¹³C). This is especially important because of the advantages that observation of ¹³C-labeled methyl groups offers in working with very large molecules. Here we consider some of the options for measurement of methyl RDCs in large and often fully protonated proteins and arrive at a pulse sequence that exploits both J-modulation and direct detection of ¹³C. Its utility is illustrated by application to a fully protonated two domain fragment from the mammalian glycoprotein, Robo1, ¹³C-methyl-labeled in all valines.

Paramagnetic Tag for Glycosylation Sites in Glycoproteins: Structural Constraints on Heparan Sulfate Binding to Robo1

An enzyme- and click chemistry-mediated methodology for the site-specific nitroxide spin labeling of glycoproteins has been developed and applied. The procedure relies on the presence of single N-glycosylation sites that are present natively in proteins or that can be engineered into glycoproteins by mutational elimination of all but one glycosylation site. Recombinantly expressing glycoproteins in HEK293S (GnT1-) cells results in N-glycans with high-mannose structures that can be processed to leave a single GlcNAc residue. This can in turn be modified by enzymatic addition of a GalNAz residue that is subject to reaction with an alkyne-carrying TEMPO moiety using copper(I)-catalyzed click chemistry. To illustrate the procedure, we have made an application to a two-domain construct of Robo1, a protein that carries a single N-glycosylation site in its N-terminal domains. The construct has also been labeled with 15N at amide nitrogens of lysine residues to provide a set of sites that are used to derive an effective location of the paramagnetic nitroxide moiety of the TEMPO group. This, in turn, allowed measurements of paramagnetic perturbations to the spectra of a new high affinity heparan sulfate ligand. Calculation of distance constraints from these data facilitated determination of an atomic level model for the docked complex.

Structural Characterization of a Heparan Sulfate Pentamer Interacting with LAR-Ig1-2

Leukocyte common antigen-related (LAR) protein is one of the type IIa receptor protein tyrosine phosphatases (RPTPs) that are important for signal transduction in biological processes, including axon growth and regeneration. Glycosaminoglycan chains, including heparan sulfate (HS) and chondroitin sulfate (CS), act as ligands that regulate LAR signaling. Here, we report the structural characterization of the first two immunoglobulin domains (Ig1-2) of LAR interacting with an HS pentasaccharide (GlcNS6S-GlcA-GlcNS3,6S-IdoA2S-GlcNS6S-OME, fondaparinux) using multiple solution-based NMR methods. In the course of the study, we extended an assignment strategy useful for sparsely labeled proteins expressed in mammalian cell culture supplemented with a single type of isotopically enriched amino acid ([¹⁵N]-Lys in this case) by including paramagnetic perturbations to NMR resonances. The folded two-domain structure for LAR-Ig1-2 seen in previous crystal structures has been validated in solution using residual dipolar coupling data, and a combination of chemical shift perturbation on titration of LAR-Ig1-2 with fondaparinux, saturation transfer difference (STD) spectra, and transferred nuclear Overhauser effects (trNOEs) have been employed in the docking program HADDOCK to generate models for the LAR-fondaparinux complex. These models are further analyzed by postprocessing energetic analysis to identify key binding interactions. In addition to providing insight into the ligand interaction mechanisms of type IIa RPTPs and the origin of opposing effects of CS and HS ligands, these results may assist in future design of therapeutic compounds for nervous system repair.

NMR characterization of HtpG, the E. coli Hsp90, using sparse labeling with 13C-methyl alanine

A strategy for acquiring structural information from sparsely isotopically labeled large proteins is illustrated with an application to the E. coli heat-shock protein, HtpG (high temperature protein G), a 145 kDa dimer. It uses ¹³C-alanine methyl labeling in a perdeuterated background to take advantage of the sensitivity and resolution of Methyl-TROSY spectra, as well as the backbone-centered structural information from ¹H-¹³C residual dipolar couplings (RDCs) of alanine methyl groups. In all, 40 of the 47 expected crosspeaks were resolved and 36 gave RDC data. Assignments of crosspeaks were partially achieved by transferring assignments from those made on individual domains using triple resonance methods. However, these were incomplete and in many cases the transfer was ambiguous. A genetic algorithm search for consistency between predictions based on domain structures and measurements for chemical shifts and RDCs allowed 60% of the 40 resolved crosspeaks to be assigned with confidence. Chemical shift changes of these crosspeaks on adding an ATP analog to the apo-protein are shown to be consistent with structural changes expected on comparing previous crystal structures for apo- and complex- structures. RDCs collected on the assigned alanine methyl peaks are used to generate a new solution model for the apo-protein structure.