Combining NMR and small angle X-ray and neutron scattering in the structural analysis of a ternary protein-RNA complex

Many processes in the regulation of gene expression and signaling involve the formation of protein complexes involving multi-domain proteins. Individual domains that mediate protein-protein and protein-nucleic acid interactions are typically connected by flexible linkers, which contribute to conformational dynamics and enable the formation of complexes with distinct binding partners. Solution techniques are therefore required for structural analysis and to characterize potential conformational dynamics. Nuclear magnetic resonance spectroscopy (NMR) provides such information but often only sparse data are obtained with increasing molecular weight of the complexes. It is therefore beneficial to combine NMR data with additional structural restraints from complementary solution techniques. Small angle X-ray/neutron scattering (SAXS/SANS) data can be efficiently combined with NMR-derived information, either for validation or by providing additional restraints for structural analysis. Here, we show that the combination of SAXS and SANS data can help to refine structural models obtained from data-driven docking using HADDOCK based on sparse NMR data. The approach is demonstrated with the ternary protein-protein-RNA complex involving two RNA recognition motif (RRM) domains of Sex-lethal, the N-terminal cold shock domain of Upstream-to-N-Ras, and msl-2 mRNA. Based on chemical shift perturbations we have mapped protein-protein and protein-RNA interfaces and complemented this NMR-derived information with SAXS data, as well as SANS measurements on subunit-selectively deuterated samples of the ternary complex. Our results show that, while the use of SAXS data is beneficial, the additional combination with contrast variation in SANS data resolves remaining ambiguities and improves the docking based on chemical shift perturbations of the ternary protein-RNA complex.     

Solid-state NMR structures of integral membrane proteins

Abstract

Solid-state NMR is unique for its ability to obtain three-dimensional structures and to measure atomic-resolution structural and dynamic information for membrane proteins in native lipid bilayers. An increasing number and complexity of integral membrane protein structures have been determined by solid-state NMR using two main methods. Oriented sample solid-state NMR uses macroscopically aligned lipid bilayers to obtain orientational restraints that define secondary structure and global fold of embedded peptides and proteins and their orientation and topology in lipid bilayers. Magic angle spinning (MAS) solid-state NMR uses unoriented rapidly spinning samples to obtain distance and torsion angle restraints that define tertiary structure and helix packing arrangements. Details of all current protein structures are described, highlighting developments in experimental strategy and other technological advancements. Some structures originate from combining solid- and solution-state NMR information and some have used solid-state NMR to refine X-ray crystal structures. Solid-state NMR has also validated the structures of proteins determined in different membrane mimetics by solution-state NMR and X-ray crystallography and is therefore complementary to other structural biology techniques. By continuing efforts in identifying membrane protein targets and developing expression, isotope labelling and sample preparation strategies, probe technology, NMR experiments, calculation and modelling methods and combination with other techniques, it should be feasible to determine the structures of many more membrane proteins of biological and biomedical importance using solid-state NMR. This will provide three-dimensional structures and atomic-resolution structural information for characterising ligand and drug interactions, dynamics and molecular mechanisms of membrane proteins under physiological lipid bilayer conditions.     

NMR observable-based structure refinement of DAP12-NKG2C activating immunoreceptor complex in explicit membranes

NMR observables, such as NOE-based distance measurements, are increasingly being used to characterize membrane protein structures. However, challenges in membrane protein NMR studies often yield a relatively small number of such restraints that can create ambiguities in defining critical side chain-side chain interactions. In the recent solution NMR structure of the DAP12-NKG2C immunoreceptor transmembrane helix complex, five functionally required interfacial residues (two Asps and two Thrs in the DAP12 dimer and one Lys in NKG2C) display a surprising arrangement in which one Asp side chain faces the membrane hydrophobic core. To explore whether these side-chain interactions are energetically optimal, we used the published distance restraints for molecular dynamics simulations in explicit micelles and bilayers. The structures refined by this protocol are globally similar to the published structure, but the side chains of those five residues form a stable network of salt bridges and hydrogen bonds, leaving the Asp side chain shielded from the hydrophobic core, which is also consistent with available experimental observations. Moreover, the simulations show similar short-range interactions between the transmembrane complex and lipid/detergent molecules in micelles and bilayers, respectively. This study illustrates the efficacy of NMR membrane protein structure refinements in explicit membrane systems.     

Nucleotide substrate recognition by UDP-N-acetylglucosamine acyltransferase (LpxA) in the first step of lipid A biosynthesis

Lipid A is an integral component of the lipopolysaccharide (LPS) that forms the selective and protective outer monolayer of Gram-negative bacteria, and is essential for bacterial growth and viability. UDP-N-acetylglucosamine acyltransferase (LpxA) initiates lipid A biosynthesis by catalyzing the transfer of R-3-hydroxymyristic acid from acyl carrier protein to the 3'-hydroxyl group of UDP-GlcNAc. The enzyme is a homotrimer, and previous studies suggested that the active site lies within a positively charged cleft formed at the subunit-subunit interface. The crystal structure of Escherichia coli LpxA in complex with UDP-GlcNAc reveals details of the substrate-binding site, with prominent hydrophilic interactions between highly conserved clusters of residues (Asn198, Glu200, Arg204 and Arg205) with UDP, and (Asp74, His125, His144 and Gln161) with the GlcNAc moiety. These interactions serve to bind and orient the substrate for catalysis. The crystallographic model supports previous results, which suggest that acylation occurs via nucleophilic attack of deprotonated UDP-GlcNAc on the acyl donor in a general base-catalyzed mechanism involving a catalytic dyad of His125 and Asp126. His125, the general base, interacts with the 3'-hydroxyl group of UDP-GlcNAc to generate the nucleophile. The Asp126 side-chain accepts a hydrogen bond from His125 and helps orient the general base to participate in catalysis. Comparisons with an LpxA:peptide inhibitor complex indicate that the peptide competes with both nucleotide and acyl carrier protein substrates.     

Structural Basis for the Recognition of Peptide RJPXD33 by Acyltransferases in Lipid A Biosynthesis

UDP-N-acetylglucosamine acyltransferase (LpxA) and UDP-3-O-(acyl)-glucosamine acyltransferase (LpxD) constitute the essential, early acyltransferases of lipid A biosynthesis. Recently, an antimicrobial peptide inhibitor, RJPXD33, was identified with dual affinity for LpxA and LpxD. To gain a fundamental understanding of the molecular basis of inhibitor binding, we determined the crystal structure of LpxA from Escherichia coli in complex with RJPXD33 at 1.9 Å resolutions. Our results suggest that the peptide binds in a unique modality that mimics (R)-β-hydroxyacyl pantetheine binding to LpxA and displays how the peptide binds exclusive of the native substrate, acyl-acyl carrier protein. Acyltransferase binding studies with photo-labile RJPXD33 probes and truncations of RJPXD33 validated the structure and provided fundamental insights for future design of small molecule inhibitors. Overlay of the LpxA-RJPXD33 structure with E. coli LpxD identified a complementary peptide binding pocket within LpxD and serves as a model for further biochemical characterization of RJPXD33 binding to LpxD.     

Protein-protein complexation in bioluminescence

In this review we summarize the progress made towards understanding the role of protein-protein interactions in the function of various bioluminescence systems of marine organisms, including bacteria, jellyfish and soft corals, with particular focus on methodology used to detect and characterize these interactions. In some bioluminescence systems, protein-protein interactions involve an “accessory protein” whereby a stored substrate is efficiently delivered to the bioluminescent enzyme luciferase. Other types of complexation mediate energy transfer to an “antenna protein” altering the color and quantum yield of a bioluminescence reaction. Spatial structures of the complexes reveal an important role of electrostatic forces in governing the corresponding weak interactions and define the nature of the interaction surfaces. The most reliable structural model is available for the protein-protein complex of the Ca²⁺-regulated photoprotein clytin and green-fluorescent protein (GFP) from the jellyfish Clytia gregaria, solved by means of X-ray crystallography, NMR mapping and molecular docking. This provides an example of the potential strategies in studying the transient complexes involved in bioluminescence. It is emphasized that structural studies such as these can provide valuable insight into the detailed mechanism of bioluminescence.     

Rapid identification of protein-protein interfaces for the construction of a complex model based on multiple unassigned signals by using time-sharing NMR measurements

Protein-protein interactions are necessary for various cellular processes, and therefore, information related to protein-protein interactions and structural information of complexes is invaluable. To identify protein-protein interfaces using NMR, resonance assignments are generally necessary to analyze the data; however, they are time consuming to collect, especially for large proteins. In this paper, we present a rapid, effective, and unbiased approach for the identification of a protein-protein interface without resonance assignments. This approach requires only a single set of 2D titration experiments of a single protein sample, labeled with a unique combination of an (15)N-labeled amino acid and several amino acids (13)C-labeled on specific atoms. To rapidly obtain high resolution data, we applied a new pulse sequence for time-shared NMR measurements that allowed simultaneous detection of a ω(1)-TROSY-type backbone (1)H-(15)N and aromatic (1)H-(13)C shift correlations together with single quantum methyl (1)H-(13)C shift correlations. We developed a structure-based computational approach, that uses our experimental data to search the protein surfaces in an unbiased manner to identify the residues involved in the protein-protein interface. Finally, we demonstrated that the obtained information of the molecular interface could be directly leveraged to support protein-protein docking studies. Such rapid construction of a complex model provides valuable information and enables more efficient biochemical characterization of a protein-protein complex, for instance, as the first step in structure-guided drug development.     

TROSY and CRINEPT: NMR with large molecular and supramolecular structures in solution

TROSY and CRINEPT are new techniques for solution NMR studies of molecular and supramolecular structures. They allow the collection of high-resolution spectra of structures with molecular weights >100 kDa, significantly extending the range of macromolecular systems that can be studied by NMR in solution. TROSY has already been used to map protein-protein interfaces, to conduct structural studies on membrane proteins and to study nucleic acid conformations in multimolecular assemblies. These techniques will help us to investigate the conformational states of individual macromolecular components and will support de novo protein structure determination in large supramolecular structures.     

蛋白质复合体及蛋白质相互作用研究新策略—化学交联结合质谱分析法

近年来化学交联法结合质谱分析法被广泛用于蛋白质复合体结构及蛋白质相互作用的研究。研究表明这两种方法的有机结合为研究蛋白质复合体结构及蛋白质相互作用提供了一条新的途径。文章对不同类型的化学交联剂、质谱分析中的Bottom-up 与Top-down 两种研究策略,以及化学交联法结合质谱分析法在蛋白质复合体结构、蛋白质相互作用研究中的应用进行综述。这两种方法的不断发展与完善,将会极大促进生物大分子复合体结构及蛋白质相互作用的研究。     

Filtering and selection of structural models: combining docking and NMR

It is generally accepted that protein structures are more conserved than protein sequences, and 3D structure determination by computer simulations have become an important necessity in the postgenomic area. Despite major successes no robust, fast, and automated ab initio prediction algorithms for deriving accurate folds of single polypeptide chains or structures of intermolecular complexes exist at present. Here we present a methodology that uses selection and filtering of structural models generated by docking of known substructures such as individual proteins or domains through easily obtainable experimental NMR constraints. In particular, residual dipolar couplings and chemical shift mapping are used. Heuristic inclusion of chemical or biochemical knowledge about point-to-point interactions is combined in our selection strategy with the NMR data and commonly used contact potentials. We demonstrate the approach for the determination of protein-protein complexes using the EIN/HPr complex as an example and for establishing the domain-domain orientation in a chimeric protein, the recently determined hybrid human-Escherichia. coli thioredoxin.     

Efficient comprehensive scoring of docked protein complexes using probabilistic support vector machines

Biological systems and processes rely on a complex network of molecular interactions. While the association of biological macromolecules is a fundamental biochemical phenomenon crucial for the understanding of complex living systems, protein-protein docking methods aim for the computational prediction of protein complexes from individual subunits. Docking algorithms generally produce large numbers of putative protein complexes with only few of these conformations resembling the native complex structure within an acceptable degree of structural similarity. A major challenge in the field of docking is to extract near-native structure(s) out of the large pool of solutions, the so called scoring or ranking problem. A series of structural, chemical, biological and physical properties are used in this work to classify docked protein-protein complexes. These properties include specialized energy functions, evolutionary relationship, class specific residue interface propensities, gap volume, buried surface area, empiric pair potentials on residue and atom level as well as measures for the tightness of fit. Efficient comprehensive scoring functions have been developed using probabilistic Support Vector Machines in combination with this array of properties on the largest currently available protein-protein docking benchmark. The established classifiers are shown to be specific for certain types of protein-protein complexes and are able to detect near-native complex conformations from large sets of decoys with high sensitivity. Using classification probabilities the ranking of near-native structures was drastically improved, leading to a significant enrichment of near-native complex conformations within the top ranks. It could be shown that the developed schemes outperform five other previously published scoring functions.     

A novel NMR method for determining the interfaces of large protein-protein complexes

Identification of the interfaces of large (Mr > 50,000) protein-protein complexes in solution by high resolution NMR has typically been achieved using experiments involving chemical shift perturbation and/or hydrogen-deuterium exchange of the main chain amide groups of the proteins. Interfaces identified using these techniques, however, are not always identical to those revealed using X-ray crystallography. In order to identify the contact residues in a large protein-protein complex more accurately, we developed a novel NMR method that uses cross-saturation phenomena in combination with TROSY detection in an optimally deuterium labeled system.     

Unraveling a bacterial hexose transport pathway

Structural information about proteins involved in bacterial hexose transport mediated by the phosphoenolpyruvate:sugar phosphotransferase system is rapidly accumulating. Within the past year, two crystal structures and two solution NMR structures of the histidine-containing phosphocarrier protein have been reported, adding structural details to previous NMR and crystallographic work on this protein and on enzyme IIA. The crystal structure of the regulatory complex between the glucose enzyme IIA and glycerol kinase has been determined, and the association of the histidine-containing phosphocarrier protein and either the glucose enzyme IIA or the mannitol enzyme IIA have been studied by NMR. Proposals concerning the mechanism of phosphoryl transfer and the protein-protein interactions involved may now be tested more rigorously using these data.     

Application of NMR and EPR methods to the study of RNA

The application of techniques based on magnetic resonance, specifically electron paramagnetic resonance (EPR) and nuclear magnetic resonance (NMR), has provided a wealth of new information on RNA structures, as well as insights into the dynamics and function of these important biomolecules. NMR spectroscopy is very successful for determining the solution structures of small RNA domains, aptamers and ribozymes, and exploring their intramolecular dynamics and interactions with ligands. EPR-based methods have been used to map local dynamic and structural features of RNA, to explore different modes of RNA-ligand interaction, to obtain long-range structural restraints and to probe metal-ion-binding sites.     

The active site of Escherichia coli UDP-N-acetylglucosamine acyltransferase. Chemical modification and site-directed mutagenesis.

UDP-N-acetylglucosamine (UDP-GlcNAc) acyltransferase (LpxA) catalyzes the reversible transfer of an R-3-hydroxyacyl chain from R-3-hydroxyacyl-acyl carrier protein to the glucosamine 3-OH of UDP-GlcNAc in the first step of lipid A biosynthesis. Lipid A is required for the growth and virulence of most Gram-negative bacteria, making its biosynthetic enzymes intriguing targets for the development of new antibacterial agents. LpxA is a member of a large family of left-handed beta-helical proteins, many of which are acyl- or acetyltransferases. We now demonstrate that histidine-, lysine-, and arginine-specific reagents effectively inhibit LpxA of Escherichia coli, whereas serine- and cysteine-specific reagents do not. Using this information in conjunction with multiple sequence alignments, we constructed site-directed alanine substitution mutations of conserved histidine, lysine, and arginine residues. Many of these mutant LpxA enzymes show severely decreased specific activities under standard assay conditions. The decrease in activity corresponds to decreased k(cat)/K(m,UDP-GlcNAc) values for all the mutants. With the exception of H125A, in which no activity is seen under any assay condition, the decrease in k(cat)/K(m,UDP-GlcNAc) mainly reflects an increased K(m,UDP-GlcNAc). His(125) of E. coli LpxA may therefore function as a catalytic residue, possibly as a general base. LpxA does not catalyze measurable UDP-3-O-(R-3-hydroxymyristoyl)-GlcNAc hydrolysis or UDP-GlcNAc/UDP-3-O-(R-3-hydroxymyristoyl)-GlcNAc exchange, arguing against a ping-pong mechanism with an acyl-enzyme intermediate.     

Activity and crystal structure of Arabidopsis thaliana UDP-N-acetylglucosamine acyltransferase

The UDP-N-acetylglucosamine (UDP-GlcNAc) acyltransferase, encoded by lpxA, catalyzes the first step of lipid A biosynthesis in Gram-negative bacteria, the (R)-3-hydroxyacyl-ACP-dependent acylation of the 3-OH group of UDP-GlcNAc. Recently, we demonstrated that the Arabidopsis thaliana orthologs of six enzymes of the bacterial lipid A pathway produce lipid A precursors with structures similar to those of Escherichia coli lipid A precursors [Li, C., et al. (2011) Proc. Natl. Acad. Sci. U.S.A. 108, 11387-11392]. To build upon this finding, we have cloned, purified, and determined the crystal structure of the A. thaliana LpxA ortholog (AtLpxA) to 2.1 ? resolution. The overall structure of AtLpxA is very similar to that of E. coli LpxA (EcLpxA) with an α-helical-rich C-terminus and characteristic N-terminal left-handed parallel β-helix (LβH). All key catalytic and chain length-determining residues of EcLpxA are conserved in AtLpxA; however, AtLpxA has an additional coil and loop added to the LβH not seen in EcLpxA. Consistent with the similarities between the two structures, purified AtLpxA catalyzes the same reaction as EcLpxA. In addition, A. thaliana lpxA complements an E. coli mutant lacking the chromosomal lpxA and promotes the synthesis of lipid A in vivo similar to the lipid A produced in the presence of E. coli lpxA. This work shows that AtLpxA is a functional UDP-GlcNAc acyltransferase that is able to catalyze the same reaction as EcLpxA and supports the hypothesis that lipid A molecules are biosynthesized in Arabidopsis and other plants.     

Investigation of the utility of selective methyl protonation for determination of membrane protein structures

Polytopic alpha-helical membrane proteins present one of the final frontiers for protein structural biology, with significant challenges causing severe under-representation in the protein structure databank. However, with the advent of hardware and methodology geared to the study of large molecular weight complexes, solution NMR is being increasingly considered as a tool for structural studies of these types of membrane proteins. One method that has the potential to facilitate these studies utilizes uniformly deuterated samples with protons reintroduced at one or two methyl groups of leucine, valine and isoleucine. In this work we demonstrate that in spite of the increased proportion of these amino acids in membrane proteins, the quality of structures that can be obtained from this strategy is similar to that obtained for all alpha-helical water soluble proteins. This is partly attributed to the observation that NOEs between residues within the transmembrane helix did not have an impact on structure quality. Instead the most important factors controlling structure accuracy were the strength of dihedral angle restraints imposed and the number of unique inter-helical pairs of residues constrained by NOEs. Overall these results suggest that the most accurate structures will arise from accurate identification of helical segments and utilization of inter-helical distance restraints from various sources to maximize the distribution of long-range restraints.     

Homology inference of protein-protein interactions via conserved binding sites

The coverage and reliability of protein-protein interactions determined by high-throughput experiments still needs to be improved, especially for higher organisms, therefore the question persists, how interactions can be verified and predicted by computational approaches using available data on protein structural complexes. Recently we developed an approach called IBIS (Inferred Biomolecular Interaction Server) to predict and annotate protein-protein binding sites and interaction partners, which is based on the assumption that the structural location and sequence patterns of protein-protein binding sites are conserved between close homologs. In this study first we confirmed high accuracy of our method and found that its accuracy depends critically on the usage of all available data on structures of homologous complexes, compared to the approaches where only a non-redundant set of complexes is employed. Second we showed that there exists a trade-off between specificity and sensitivity if we employ in the prediction only evolutionarily conserved binding site clusters or clusters supported by only one observation (singletons). Finally we addressed the question of identifying the biologically relevant interactions using the homology inference approach and demonstrated that a large majority of crystal packing interactions can be correctly identified and filtered by our algorithm. At the same time, about half of biological interfaces that are not present in the protein crystallographic asymmetric unit can be reconstructed by IBIS from homologous complexes without the prior knowledge of crystal parameters of the query protein.