Assignment Of Methyl Resonances Research Articles

1H, 13C and 15N resonance assignment of backbone and IVL-methyl side chain of the S135A mutant NS3pro/NS2B protein of Dengue II virus reveals unique secondary structure features in solution

The serotype II Dengue (DENV 2) virus is the most prevalent of all four known serotypes. Herein, we present nearly complete 1H, 15N, and 13C backbone and 1H, 13C isoleucine, valine, and leucine methyl resonance assignment of the apo S135A catalytically inactive variant of the DENV 2 protease enzyme folded as a tandem formed between the serine protease domain NS3pro and the cofactor NS2B, as well as the secondary structure prediction of this complex based on the assigned chemical shifts using the TALOS-N software. Our results provide a solid ground for future elucidation of the structure and dynamic of the apo NS3pro/NS2B complex, key for adequate development of inhibitors, and a thorough molecular understanding of their function(s).

Backbone and ILVM methyl resonance assignments of human thymidylate synthase in apo and substrate bound forms.

Human thymidylate synthase (hTS) is a 72kDa homodimeric enzyme responsible for the conversion of deoxyuridine monophosphate (dUMP) to deoxythymidine monophosphate (dTMP), making it the sole source of de novo dTMP in human cells. As a result, hTS is an attractive anti-cancer therapeutic target. Additionally, hTS is known to possess a number of interesting biophysical features, including adoption of active and inactive conformations, positively cooperative substrate binding, half-the-sites activity, and interacting with its own mRNA. The physical mechanisms underlying these properties, and how they may be leveraged to guide therapeutic development, are yet to be fully explored. Here, as a preface to detailed NMR characterization, we present backbone amide and ILVM methyl resonance assignments for hTS in apo and dUMP bound forms. In addition, we present backbone amide resonance assignments for hTS bound to a substrate analog and the native cofactor.

The methyl 13C-edited/13C-filtered transferred NOE for studying protein interactions with short linear motifs.

Many proteins interact with their ligand proteins by recognition of short linear motifs that are often intrinsically disordered. These interactions are usually weak and are characterized by fast exchange. NMR spectroscopy is a powerful tool to study weak interactions. The methods that have been commonly used are analysis of chemicals shift perturbations (CSP) upon ligand binding and saturation transfer difference spectroscopy. These two methods identify residues at the binding interface between the protein and its ligand. In the present study, we used a combination of transferred-NOE, specific methyl-labeling and an optimized isotope-edited/isotope-filtered NOESY experiment to study specific interactions between the 42kDa p38α mitogen-activated protein kinase and the kinase interaction motif (KIM) on the STEP phosphatase. These measurements distinguished between residues that both exhibit CSPs upon ligand binding and interact with the KIM peptide from residues that exhibit CSPs but do not interact with the peptide. In addition, these results provide information about pairwise interactions that is important for a more reliable docking of the KIM peptide into its interacting surface on p38α. This combination of techniques should be applicable for many protein-peptide complexes up to 80kDa for which methyl resonance assignment can be achieved.

Phosphorylated tEIN backbone and I/L/V methyl resonance assignment

Phosphorylated tEIN backbone and I/L/V methyl resonance assignment

Complete assignment of Ala, Ile, LeuProS, Met and ValProS methyl groups of the protruding domain from human norovirus GII.4 Saga

Attachment of human noroviruses to histo blood group antigens (HBGAs) is thought to be essential for infection, although how this binding event promotes infection is unknown. Recent studies have shown that 60% of all GII.4 epidemic strains may undergo a spontaneous post-translational modification (PTM) in an amino acid located adjacent to the binding pocket for HBGAs. This transformation proceeds with an estimated half-life of 1–2 days under physiological conditions, dramatically affecting HBGA recognition. The surface-exposed position of this PTM and its sequence conservation suggests a relevant role in immune escape and host-cell recognition. As a first step towards the understanding of the biological implications of this PTM at atomic resolution, we report the complete assignment of methyl resonances of a MILProSVProSA methyl-labeled sample of a 72 kDa protruding domain from a GII.4 Saga human norovirus strain. Assignments were obtained from methyl–methyl NOESY experiments combined with site-directed mutagenesis and automated assignment. This data provides the basis for a detailed characterization of the PTM-driven modulation of immune recognition in human norovirus on a molecular level.

Automatic structure-based NMR methyl resonance assignment in large proteins

Isotopically labeled methyl groups provide NMR probes in large, otherwise deuterated proteins. However, the resonance assignment constitutes a bottleneck for broader applicability of methyl-based NMR. Here, we present the automated MethylFLYA method for the assignment of methyl groups that is based on methyl-methyl nuclear Overhauser effect spectroscopy (NOESY) peak lists. MethylFLYA is applied to five proteins (28–358 kDa) comprising a total of 708 isotope-labeled methyl groups, of which 612 contribute NOESY cross peaks. MethylFLYA confidently assigns 488 methyl groups, i.e. 80% of those with NOESY data. Of these, 459 agree with the reference, 6 were different, and 23 were without reference assignment. MethylFLYA assigns significantly more methyl groups than alternative algorithms, has an average error rate of 1%, modest runtimes of 0.4–1.2 h, and can handle arbitrary isotope labeling patterns and data from other types of NMR spectra.

Combining Evolutionary Covariance and NMR Data for Protein Structure Determination.

Accurate protein structure determination by solution-state NMR is challenging for proteins greater than about 20kDa, for which extensive perdeuteration is generally required, providing experimental data that are incomplete (sparse) and ambiguous. However, the massive increase in evolutionary sequence information coupled with advances in methods for sequence covariance analysis can provide reliable residue-residue contact information for a protein from sequence data alone. These "evolutionary couplings (ECs)" can be combined with sparse NMR data to determine accurate 3D protein structures. This hybrid "EC-NMR" method has been developed using NMR data for several soluble proteins and validated by comparison with corresponding reference structures determined by X-ray crystallography and/or conventional NMR methods. For small proteins, only backbone resonance assignments are utilized, while for larger proteins both backbone and some sidechain methyl resonance assignments are generally required. ECs can be combined with sparse NMR data obtained on deuterated, selectively protonated protein samples to provide structures that are more accurate and complete than those obtained using such sparse NMR data alone. EC-NMR also has significant potential for analysis of protein structures from solid-state NMR data and for studies of integral membrane proteins. The requirement that ECs are consistent with NMR data recorded on a specific member of a protein family, under specific conditions, also allows identification of ECs that reflect alternative allosteric or excited states of the protein structure.

NMR backbone and methyl resonance assignments of an inhibitory G-alpha subunit in complex with GDP.

G-proteins are essential switch points at the cell membrane that control downstream signaling by their ability to adopt an inactive, GDP-bound or an active, GTP-bound state. Among other exchange factors, G-protein coupled receptors (GPCRs) induce exchange of GDP to GTP and thus promote the active state of the G-protein. The nucleotide-binding α subunit of the G-protein undergoes major conformational changes upon nucleotide binding. Thus, an NMR analysis of the two distinct nucleotide-bound states is essential for a more detailed understanding of associated structural changes. Here, we provide an NMR backbone as well as methyl group resonance assignment of an inhibitory G-alpha subunit subtype 1 (Gαi,1) in the GDP-bound form and show that, in contrast to the GTP-bound form, large parts of the protein are mobile, presumably caused by a loose arrangement of the two subdomains in Gα that tightly interact with each other only in the GTP-bound state. As the GDP-bound form represents the GPCR-binding-competent state, the presented NMR data will be essential for further studies on G-protein-GPCR interactions and dynamics in solution for receptor systems that couple to G-proteins containing an inhibitory Gα,1 subunit.

Toolkit for NMR Studies of Methyl-Labeled Proteins.

Selective methyl labeling is an extremely powerful approach to study the structure, dynamics, and explore mechanistic insights of large biomolecules by solution NMR. Methyls are relatively insensitive to chemical exchange-induced depolarization and provide superior probes of supramolecular interactions and allostery in such systems. In this chapter, we describe our systematic approach and contributions in the areas of sample preparation, data collection, and data analysis that streamline the application of methyl labeling in solution NMR studies of large proteins. We focus our effort on the initial and often onerous task of methyl resonance assignment and here we detail our approaches to simplify the process. We produce new methyl labeling combinations using Escherichia coli auxotrophs, increase speed, sensitivity, and resolution of NOESY experiments by employing 3D SOFAST-NOESY, and assign methyl resonances from raw data with spectral simulation tools and(or) automatically with minimal expert supervision using the MAGIC algorithm.

Assigning methyl resonances for protein solution-state NMR studies.

Solution-state NMR is an important tool for studying protein structure and function. The ability to probe methyl groups has substantially expanded the scope of proteins accessible by NMR spectroscopy, including facilitating study of proteins and complexes greater than 100 kDa in size. While the toolset for studying protein structure and dynamics by NMR continues to grow, a major rate-limiting step in these studies is the initial resonance assignments, especially for larger (>50 kDa) proteins. In this practical review, we present strategies to efficiently isotopically label proteins, delineate NMR pulse sequences that can be used to determine methyl resonance assignments in the presence and absence of backbone assignments, and outline computational methods for NMR data analysis. We use our experiences from assigning methyl resonances for the aromatic biosynthetic enzymes tryptophan synthase and chorismate mutase to provide advice for all stages of experimental set-up and data analysis.

Fully automated assignment of methyl resonances of a 36 kDa protein dimer from sparse NOESY data

High-resolution solution-state NMR spectroscopy studies of large proteins typically require uniform deuteration of the system and selective protonation and isotope labelling of methyl groups. Under such circumstances, the assignment of methyl resonances presents a considerable experimental challenge and automation of the process using computational algorithms has been actively sought. Through-space connectivities between the labelled methyl groups can be established through nuclear Overhauser enhancement spectroscopy (NOESY). If a high-resolution structure of the system is available, the sparse connectivity restraints derived from this information enable structure-based methyl resonance assignment. Here, we outline a protocol for full automation of the methyl resonance assignment process using the CYANA software package. We tested the protocol on three-dimensional (3D) 13C/13C-separated NOESY spectra of a dimer of regulatory chains of aspartate transcarbamoylase (ATCase-r2). We used CYPICK to detect NOE signals, followed by automatic resonance assignment with FLYA. On this dataset, FLYA generated highly similar results using either automatically or manually generated peak lists, confidently assigning ∼60% of the methyl groups with high accuracy (95 ± 2% correctness). We compared this performance to two alternative automatic methyl assignment protocols, MAP-XSII and FLAMEnGO2.0, both of which, similarly to FLYA, support unassigned NOESY peak lists as input.

Automatic Assignment of Methyl-NMR Spectra of Supramolecular Machines Using Graph Theory.

Methyl groups are powerful probes for the analysis of structure, dynamics and function of supramolecular assemblies, using both solution- and solid-state NMR. Widespread application of the methodology has been limited due to the challenges associated with assigning spectral resonances to specific locations within a biomolecule. Here, we present Methyl Assignment by Graph Matching (MAGMA), for the automatic assignment of methyl resonances. A graph matching protocol examines all possibilities for each resonance in order to determine an exact assignment that includes a complete description of any ambiguity. MAGMA gives 100% accuracy in confident assignments when tested against both synthetic data, and 9 cross-validated examples using both solution- and solid-state NMR data. We show that this remarkable accuracy enables a user to distinguish between alternative protein structures. In a drug discovery application on HSP90, we show the method can rapidly and efficiently distinguish between possible ligand binding modes. By providing an exact and robust solution to methyl resonance assignment, MAGMA can facilitate significantly accelerated studies of supramolecular machines using methyl-based NMR spectroscopy.

AILV Methyl Resonance Assignments for G protein alpha i3 subunit in the GoLoco14-bound state

AILV Methyl Resonance Assignments for G protein alpha i3 subunit in the GoLoco14-bound state

An Integrated Approach to Unique NMR Assignment of Methionine Methyl Resonances in Proteins.

The application of methyl nuclear magnetic resonance (NMR) spectroscopy in protein side-chain structural studies offers unique advantages of greater peak sensitivity, even for high-molecular-weight proteins. Traditionally, the utility of methyl NMR has often been limited by the difficulty in assigning the methyl resonances. Herein, a mass spectrometry (MS)-assisted strategy to assign the methyl resonances of methionine residues is presented. The strategy involves partially oxidizing the methionine and quantifying the oxidation level by both NMR and liquid chromatography-mass spectrometry (LC-MS). The NMR assignment of methyl resonances of methionine is made by correlating the quantitative results obtained from both NMR and MS. The method has been successfully demonstrated using the proteins hen egg-white lysozyme (HEWL) and porcine pepsin. The technique described herein can help facilitate the application of methyl NMR as a useful tool to study protein structure, dynamics, and interactions.

Backbone and methyl resonance assignments of the 42kDa human Hsc70 nucleotide binding domain in the ADP state.

Hsc70 is the constitutively expressed mammalian heat shock 70kDa (Hsp70) cytosolic chaperone. It plays a central role in cellular proteostasis and protein trafficking. Here, we present the backbone and methyl group assignments for the 386-residue nucleotide binding domain of the human protein. This domain controls the chaperone's allostery, binds multiple co-chaperones and is the target of several classes of known chemical Hsp70 inhibitors. The NMR assignments are based on common triple resonance experiments with triple labeled protein, and on several 15N and 13C-resolved 3D NOE experiments with methyl-reprotonated samples. A combination of computer and manual data interpretation was used.

Assignment of methyl NMR resonances of a 52 kDa protein with residue-specific 4D correlation maps

Methyl groups have become key probes for structural and functional studies by nuclear magnetic resonance. However, their NMR signals cluster in a small spectral region and assigning their resonances can be a tedious process. Here, we present a method that facilitates assignment of methyl resonances from assigned amide groups. Calculating the covariance between sensitive methyl and amide 3D spectra, each providing correlations to C(α) and C(β) separately, produces 4D correlation maps directly correlating methyl groups to amide groups. Optimal correlation maps are obtained by extracting residue-specific regions, applying derivative to the dimensions subject to covariance, and multiplying 4D maps stemming from different 3D spectra. The latter procedure rescues weak signals that may be missed in traditional assignment procedures. Using these covariance correlation maps, nearly all assigned isoleucine, leucine, and valine amide resonances of a 52 kDa nonribosomal peptide synthetase cyclization domain were paired with their corresponding methyl groups.

Dual-phosphorylated human p38 alpha ILVM methyl resonance assignments in ADP-bound state

Dual-phosphorylated human p38 alpha ILVM methyl resonance assignments in ADP-bound state

Backbone and ILV methyl resonance assignments of E. coli thymidylate synthase bound to cofactor and a nucleotide analogue

Backbone and ILV methyl resonance assignments of E. coli thymidylate synthase bound to cofactor and a nucleotide analogue

Backbone and ILV methyl resonance assignments of E. coli thymidylate synthase bound to cofactor and a nucleotide analogue

Thymidylate synthase (TSase) is a 62 kDa homodimeric enzyme required for de novo synthesis of thymidine monophosphate in most organisms. This makes the enzyme an excellent target for anticancer and microbial antibiotic drugs. In addition, TSase has been shown to exhibit negative cooperativity and half-the-sites reactivity. For these collective reasons, TSase is widely studied, and much is known about its kinetics and structure as it progresses through a multi-step catalytic cycle. Recently, nuclear magnetic resonance spin relaxation has been instrumental in demonstrating the critical role of dynamics in enzyme function in small model systems. These studies raise questions about how dynamics affect function in larger enzymes with more complex reaction coordinates. TSase is an ideal candidate given its size, oligomeric state, cooperativity, and status as a drug target. Here, as a pre-requisite to spin relaxation studies, we present the backbone and ILV methyl resonance assignments of TSase from Escherichia coli bound to a substrate analogue and cofactor.

MAP-XSII: an improved program for the automatic assignment of methyl resonances in large proteins

NMR studies of large proteins have gathered much interest in recent years, especially after methyl-transverse relaxation optimized spectroscopy was successfully applied to systems as large as ~1 MDa in molecular weight. However, to fully take advantage of these spectra, there is a need for convenient and robust methods for making resonance assignments rapidly. Here, we present an improved version of our program MAP-XS (methyl assignment prediction from X-ray structure) for the automatic assignment of methyl peaks, based on nuclear Overhauser effects (NOE) correlations and chemical shifts together with available structures. No manual analysis of the NOE data is needed in this new version, which helps to further accelerate the assignment process. A refined algorithm as well as more efficient sampling produces results from single runs of MAP-XSII using unanalyzed NOE data are comparable to those achieved by the old version using manually curated data with every NOE peak correctly attributed to the two related methyl peaks; in addition, checking the results from multiple parallel runs against each other provides an effective mechanism for getting rid of the wrong assignments while keeping the correct ones, which significantly improves the reliability of final assignments. The new program is tested against three different proteins and delivers ~95 % correct assignments; positive results are also achieved for tests using different cut-off distances for NOEs, structures of lower resolutions, and ambiguous residue types.