Sparse labeling of proteins: structural characterization from long range constraints

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.

An Integrative Approach to Determine 3D Protein Structures Using Sparse Paramagnetic NMR Data and Physical Modeling

Paramagnetic nuclear magnetic resonance (NMR) methods have emerged as powerful tools for structure determination of large, sparsely protonated proteins. However traditional applications face several challenges, including a need for large datasets to offset the sparsity of restraints, the difficulty in accounting for the conformational heterogeneity of the spin-label, and noisy experimental data. Here we propose an integrative approach to structure determination combining sparse paramagnetic NMR with physical modelling to infer approximate protein structural ensembles. We use calmodulin in complex with the smooth muscle myosin light chain kinase peptide as a model system. Despite acquiring data from samples labeled only at the backbone amide positions, we are able to produce an ensemble with an average RMSD of ∼2.8 Å from a reference X-ray crystal structure. Our approach requires only backbone chemical shifts and measurements of the paramagnetic relaxation enhancement and residual dipolar couplings that can be obtained from sparsely labeled samples.

Sparse isotope labeling for nuclear magnetic resonance (NMR) of glycoproteins using 13C-glucose

Preparation of samples for nuclear magnetic resonance (NMR) characterization of larger proteins requires enrichment with less abundant, NMR-active, isotopes such as 13C and 15N. This is routine for proteins that can be expressed in bacterial culture where low-cost isotopically enriched metabolic substrates can be used. However, it can be expensive for glycosylated proteins expressed in mammalian culture where more costly isotopically enriched amino acids are usually used. We describe a simple, relatively inexpensive procedure in which standard commercial media is supplemented with 13C-enriched glucose to achieve labeling of all glycans plus all alanines of the N-terminal domain of the highly glycosylated protein, CEACAM1. We demonstrate an ability to detect partially occupied N-glycan sites, sites less susceptible to processing by an endoglycosidase, and some unexpected truncation of the amino acid sequence. The labeling of both the protein (through alanines) and the glycans in a single culture requiring no additional technical expertise past standard mammalian expression requirements is anticipated to have several applications, including structural and functional screening of the many glycosylated proteins important to human health.

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.

Design and applications of lanthanide chelating tags for pseudocontact shift NMR spectroscopy with biomacromolecules

In this review, lanthanide chelating tags and their applications to pseudocontact shift NMR spectroscopy as well as analysis of residual dipolar couplings are covered. A complete overview is presented of DOTA-derived and non-DOTA-derived lanthanide chelating tags, critical points in the design of lanthanide chelating tags as appropriate linker moieties, their stability under reductive conditions, e.g., for in-cell applications, the magnitude of the anisotropy transferred from the lanthanide chelating tag to the biomacromolecule under investigation and structural properties, as well as conformational bias of the lanthanide chelating tags are discussed. Furthermore, all DOTA-derived lanthanide chelating tags used for PCS NMR spectroscopy published to date are displayed in tabular form, including their anisotropy parameters, with all employed lanthanide ions, C_B-Ln distances and tagging reaction conditions, i.e., the stoichiometry of lanthanide chelating tags, pH, buffer composition, temperature and reaction time. Additionally, applications of lanthanide chelating tags for pseudocontact shifts and residual dipolar couplings that have been reported for proteins, protein-protein and protein-ligand complexes, carbohydrates, carbohydrate-protein complexes, nucleic acids and nucleic acid-protein complexes are presented and critically reviewed. The vast and impressive range of applications of lanthanide chelating tags to structural investigations of biomacromolecules in solution clearly illustrates the significance of this particular field of research. The extension of the repertoire of lanthanide chelating tags from proteins to nucleic acids holds great promise for the determination of valuable structural parameters and further developments in characterizing intermolecular interactions.

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.

Cysteine-ethylation of tissue-extracted membrane proteins as a tool to detect conformational states by solid-state NMR spectroscopy

Solid-state NMR (ssNMR) is an ideal tool to study structure and dynamics of membrane proteins in their native lipid environment. In principle, ssNMR has no size limitations. However, this feature is rarely exploited as large membrane proteins display severe resonance overlap. In addition, dismal yields from recombinant bacterial expression systems limit severely spectroscopic characterization of membrane proteins. For very large mammalian membrane proteins, extraction from the original organism remains the most viable approach. In this case, NMR-observable nuclei must be introduced post-translationally, but the approaches developed so far are rather scarce. Here, we detail the synthesis and engineering of a reactive ¹³C-ethylmethanethiosulfonate (¹³C-EMTS) reagent for the post-translational alkylation of cysteine sidechains of a 110kDa sarcoplasmic reticulum Ca²⁺-ATPase (SERCA) extracted from rabbit skeletal muscle tissue. When reconstituted into liposomes, it is possible to resolve the resonances of the engineered ethyl groups by magic-angle spinning (MAS) 2D [¹³C,¹³C]-DARR experiments. Notably, the ethyl-group modification does not perturb the function of SERCA, yielding well-resolved ¹³C-¹³C fingerprints that are used to image its structural states in the catalytic cycle and filtering out overwhelming naturally-abundant ¹³C nuclei signals arising from the enzyme and lipids. We anticipate that this approach will be used together with ¹⁹F NMR to monitor conformational transitions of enzymes and proteins that are difficult to express recombinantly.

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.

Integrating NOE and RDC using sum-of-squares relaxation for protein structure determination

We revisit the problem of protein structure determination from geometrical restraints from NMR, using convex optimization. It is well-known that the NP-hard distance geometry problem of determining atomic positions from pairwise distance restraints can be relaxed into a convex semidefinite program (SDP). However, often the NOE distance restraints are too imprecise and sparse for accurate structure determination. Residual dipolar coupling (RDC) measurements provide additional geometric information on the angles between atom-pair directions and axes of the principal-axis-frame. The optimization problem involving RDC is highly non-convex and requires a good initialization even within the simulated annealing framework. In this paper, we model the protein backbone as an articulated structure composed of rigid units. Determining the rotation of each rigid unit gives the full protein structure. We propose solving the non-convex optimization problems using the sum-of-squares (SOS) hierarchy, a hierarchy of convex relaxations with increasing complexity and approximation power. Unlike classical global optimization approaches, SOS optimization returns a certificate of optimality if the global optimum is found. Based on the SOS method, we proposed two algorithms-RDC-SOS and RDC-NOE-SOS, that have polynomial time complexity in the number of amino-acid residues and run efficiently on a standard desktop. In many instances, the proposed methods exactly recover the solution to the original non-convex optimization problem. To the best of our knowledge this is the first time SOS relaxation is introduced to solve non-convex optimization problems in structural biology. We further introduce a statistical tool, the Cramér-Rao bound (CRB), to provide an information theoretic bound on the highest resolution one can hope to achieve when determining protein structure from noisy measurements using any unbiased estimator. Our simulation results show that when the RDC measurements are corrupted by Gaussian noise of realistic variance, both SOS based algorithms attain the CRB. We successfully apply our method in a divide-and-conquer fashion to determine the structure of ubiquitin from experimental NOE and RDC measurements obtained in two alignment media, achieving more accurate and faster reconstructions compared to the current state of the art.

NMR assignments of sparsely labeled proteins using a genetic algorithm

Sparse isotopic labeling of proteins for NMR studies using single types of amino acid (15N or 13C enriched) has several advantages. Resolution is enhanced by reducing numbers of resonances for large proteins, and isotopic labeling becomes economically feasible for glycoproteins that must be expressed in mammalian cells. However, without access to the traditional triple resonance strategies that require uniform isotopic labeling, NMR assignment of crosspeaks in heteronuclear single quantum coherence (HSQC) spectra is challenging. We present an alternative strategy which combines readily accessible NMR data with known protein domain structures. Based on the structures, chemical shifts are predicted, NOE cross-peak lists are generated, and residual dipolar couplings (RDCs) are calculated for each labeled site. Simulated data are then compared to measured values for a trial set of assignments and scored. A genetic algorithm uses the scores to search for an optimal pairing of HSQC crosspeaks with labeled sites. While none of the individual data types can give a definitive assignment for a particular site, their combination can in most cases. Four test proteins previously assigned using triple resonance methods and a sparsely labeled glycosylated protein, Robo1, previously assigned by manual analysis, are used to validate the method and develop a criterion for identifying sites assigned with high confidence.

Structural Aspects of Heparan Sulfate Binding to Robo1-Ig1-2

Roundabout 1, or Robo1, is a cell surface signaling molecule important in axon guidance. Its interaction with heparan sulfate (HS) and members of the Slit protein family is essential to its activity, making characterization of these interactions by structural methods, such as NMR, highly desirable. However, the fact that Robo1 is a glycosylated protein prevents employment of commonly used bacterial hosts for expression of properly glycosylated forms with the uniform 15N, 13C, and 2H labeling needed for NMR studies. Here, we apply an alternative methodology, based on labeling with a single amino acid type and high structural content NMR data, to characterize a two-domain construct of glycosylated Robo1 (Robo1-Ig1-2) interacting with a synthetic HS tetramer (IdoA-GlcNS6S-IdoA2S-GlcNS6S-(CH2)5NH2). Significant chemical shift perturbations of the crosspeak from K81 on titration with the tetramer provide initial evidence for the location of a binding site and allow determination of a 255 μM disassociation constant. The binding epitopes, bound conformation, and binding site placement of the HS tetramer have been further characterized by saturation transfer difference (STD), transferred nuclear Overhauser effect (trNOE), and paramagnetic perturbation experiments. A model of the complex has been generated using constraints derived from the various NMR experiments. Postprocessing energetic analysis of this model provides a rationale for the role each glycan residue plays in the binding event, and examination of the binding site in the context of a previous Robo-Slit structure provides a rationale for modulation of Robo-Slit interactions by HS.

The Structural Role of Antibody N-Glycosylation in Receptor Interactions

Asparagine(N)297-linked glycosylation of immunoglobulin G (IgG) Fc is required for binding to FcγRIIa, IIb, and IIIa, although it is unclear how it contributes. We found the quaternary structure of glycosylated Fc was indistinguishable from aglycosylated Fc, indicating that N-glycosylation does not maintain relative Fc Cγ2/Cγ3 domain orientation. However, the conformation of the C'E loop, which contains N297, was significantly perturbed in the aglycosylated Fc variant. The conformation of the C'E loop as measured with a range of Fc variants shows a strong correlation with FcγRIIIa affinity. These results indicate that the primary role of the IgG1 Fc N-glycan is to stabilize the C'E loop through intramolecular interactions between carbohydrate and amino acid residues, and preorganize the FcγRIIIa interface for optimal binding affinity. The features that contribute to the capacity of the IgG1 Fc N-glycan to restrict protein conformation and tune binding affinity are conserved in other antibodies including IgG2-IgG4, IgD, IgE, and IgM.