Rapid Protein–Ligand Costructures from Sparse NOE Data

Selective binding of small molecules to Vibrio cholerae DsbA offers a starting point for the design of novel antibacterials

DsbA enzymes catalyze oxidative folding of proteins that are secreted into the periplasm of Gram‐negative bacteria, and they are indispensable for the virulence of human pathogens such as Vibrio cholerae and Escherichia coli. Therefore, targeting DsbA represents an attractive approach to control bacterial virulence. X‐ray crystal structures reveal that DsbA enzymes share a similar fold, however, the hydrophobic groove adjacent to the active site, which is implicated in substrate binding, is shorter and flatter in the structure of V. cholerae DsbA (VcDsbA) compared to E. coli DsbA (EcDsbA). The flat and largely featureless nature of this hydrophobic groove is challenging for the development of small molecule inhibitors. Using fragment‐based screening approaches, we have identified a novel small molecule, based on the benzimidazole scaffold, that binds to the hydrophobic groove of oxidized VcDsbA with a K_D of 446±10 μM. The same benzimidazole compound has ∼8‐fold selectivity for VcDsbA over EcDsbA and binds to oxidized EcDsbA, with K_D>3.5 mM. We generated a model of the benzimidazole complex with VcDsbA using NMR data but were unable to determine the structure of the benzimidazole bound EcDsbA using either NMR or X‐ray crystallography. Therefore, a structural basis for the observed selectivity is unclear. To better understand ligand binding to these two enzymes we crystallized each of them in complex with a known ligand, the bile salt sodium taurocholate. The crystal structures show that taurocholate adopts different binding poses in complex with VcDsbA and EcDsbA, and reveal the protein‐ligand interactions that stabilize the different modes of binding. This work highlights the capacity of fragment‐based drug discovery to identify inhibitors of challenging protein targets. In addition, it provides a starting point for development of more potent and specific VcDsbA inhibitors that act through a novel anti‐virulence mechanism.

NMR spectroscopy of wastewater: A review, case study, and future potential

NMR spectroscopy is arguably the most powerful tool for the study of molecular structures and interactions, and is increasingly being applied to environmental research, such as the study of wastewater. With over 97% of the planet's water being saltwater, and two thirds of freshwater being frozen in the ice caps and glaciers, there is a significant need to maintain and reuse the remaining 1%, which is a precious resource, critical to the sustainability of most life on Earth. Sanitation and reutilization of wastewater is an important method of water conservation, especially in arid regions, making the understanding of wastewater itself, and of its treatment processes, a highly relevant area of environmental research. Here, the benefits, challenges and subtleties of using NMR spectroscopy for the analysis of wastewater are considered. First, the techniques available to overcome the specific challenges arising from the nature of wastewater (which is a complex and dilute matrix), including an examination of sample preparation and NMR techniques (such as solvent suppression), in both the solid and solution states, are discussed. Then, the arsenal of available NMR techniques for both structure elucidation (e.g., heteronuclear, multidimensional NMR, homonuclear scalar coupling-based experiments) and the study of intermolecular interactions (e.g., diffusion, nuclear Overhauser and saturation transfer-based techniques) in wastewater are examined. Examples of wastewater NMR studies from the literature are reviewed and potential areas for future research are identified. Organized by nucleus, this review includes the common heteronuclei (¹³C, ¹⁵N, ¹⁹F, ³¹P, ²⁹Si) as well as other environmentally relevant nuclei and metals such as ²⁷Al, ⁵¹V, ²⁰⁷Pb and ¹¹³Cd, among others. Further, the potential of additional NMR methods such as comprehensive multiphase NMR, NMR microscopy and hyphenated techniques (for example, LC-SPE-NMR-MS) for advancing the current understanding of wastewater are discussed. In addition, a case study that combines natural abundance (i.e. non-concentrated), targeted and non-targeted NMR to characterize wastewater, along with in vivo based NMR to understand its toxicity, is included. The study demonstrates that, when applied comprehensively, NMR can provide unique insights into not just the structure, but also potential impacts, of wastewater and wastewater treatment processes. Finally, low-field NMR, which holds considerable future potential for on-site wastewater monitoring, is briefly discussed. In summary, NMR spectroscopy is one of the most versatile tools in modern science, with abilities to study all phases (gases, liquids, gels and solids), chemical structures, interactions, interfaces, toxicity and much more. The authors hope this review will inspire more scientists to embrace NMR, given its huge potential for both wastewater analysis in particular and environmental research in general.

NMR fragment screening reveals a novel small molecule binding site near the catalytic surface of the disulfide-dithiol oxidoreductase enzyme DsbA from Burkholderia pseudomallei

The presence of suitable cavities or pockets on protein structures is a general criterion for a therapeutic target protein to be classified as 'druggable'. Many disease-related proteins that function solely through protein-protein interactions lack such pockets, making development of inhibitors by traditional small-molecule structure-based design methods much more challenging. The 22 kDa bacterial thiol oxidoreductase enzyme, DsbA, from the gram-negative bacterium Burkholderia pseudomallei (BpsDsbA) is an example of one such target. The crystal structure of oxidized BpsDsbA lacks well-defined surface pockets. BpsDsbA is required for the correct folding of numerous virulence factors in B. pseudomallei, and genetic deletion of dsbA significantly attenuates B. pseudomallei virulence in murine infection models. Therefore, BpsDsbA is potentially an attractive drug target. Herein we report the identification of a small molecule binding site adjacent to the catalytic site of oxidized BpsDsbA. ¹H^N CPMG relaxation dispersion NMR measurements suggest that the binding site is formed transiently through protein dynamics. Using fragment-based screening, we identified a small molecule that binds at this site with an estimated affinity of K_D ~ 500 µM. This fragment inhibits BpsDsbA enzymatic activity in vitro. The binding mode of this molecule has been characterized by NMR data-driven docking using HADDOCK. These data provide a starting point towards the design of more potent small molecule inhibitors of BpsDsbA.

Determination of protein-ligand binding modes using fast multi-dimensional NMR with hyperpolarization

Elucidation of small molecule-protein interactions provides essential information for understanding biological processes such as cellular signaling, as well as for rational drug development. Here, multi-dimensional NMR with sensitivity enhancement by dissolution dynamic nuclear polarization (D-DNP) is shown to allow the determination of the binding epitope of folic acid when complexed with the target dihydrofolate reductase. Protein signals are selectively enhanced by polarization transfer from the hyperpolarized ligand. A pseudo three-dimensional data acquisition with ligand-side Hadamard encoding results in protein-side [13C, 1H] chemical shift correlations that contain intermolecular nuclear Overhauser effect (NOE) information. A scoring function based on this data is used to select pre-docked ligand poses. The top five poses are within 0.76 Å root-mean-square deviation from a reference structure for the encoded five protons, showing improvements compared with the poses selected by an energy-based scoring function without experimental inputs. The sensitivity enhancement provided by the D-DNP combined with multi-dimensional NMR increases the speed and potentially the selectivity of structure elucidation of ligand binding epitopes.

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.

The structures and dynamics of large proteins can be studied with methyl-based NMR but peak assignment is still challenging. Here the authors present MethylFLYA that allows automated assignment of methyl groups and apply it to five proteins with molecular weights in the range from 28 to 358 kDa.

Determination of Ligand Binding Epitope Structures Using Polarization Transfer from Hyperpolarized Ligands

Drug discovery processes require the determination of the protein binding site structure, which can be achieved via nuclear magnetic resonance (NMR) spectroscopy. While traditional NMR spectroscopy suffers from low sensitivity, NMR signals can be significantly enhanced through hyperpolarization of nuclear spins. Here, folic acid is hyperpolarized by dissolution dynamic nuclear polarization (D-DNP). Polarization transfer to dihydrofolate reductase is compared to signal evolution predicted for docking-derived structures. The results demonstrate that a scoring function derived from the experimental data improves the ranking of structures. With data from six methyl groups, Spearman's correlation coefficient of the experimental scoring function to the root-mean-square deviation from a reference structure is 0.88 for five individually addressed ligand protons and 0.59 for the entire ligand, while the same correlation coefficient of the energy calculated from docking alone is 0.49. D-DNP NMR-derived ranking, therefore, is capable of determining the ligand structure with a small number of individually addressed source spins.

Selective Methyl Labeling of Proteins: Enabling Structural and Mechanistic Studies As Well As Drug Discovery Applications by Solution-State NMR

Escherichia coli expression protocols for selective labeling of methyl groups in proteins have been essential in expanding the size range of targets that can be studied by biomolecular NMR. Based on the initial work achieving selective labeling of isoleucine, leucine, and valine residues, additional methods were developed over the past years which enabled the individual and/or simultaneous combinatorial labeling of all methyl containing amino acids. Together with the introduction of new methyl-optimized NMR experiments, this now allows the detailed characterization of protein-ligand interactions as well as mechanistic and dynamic processes of protein-protein complexes up to 1MDa in size. In this chapter, we provide a general introduction to selective labeling of proteins using E. coli-based expression systems, describe the considerations taken into account prior to the selective labeling of a protein, and include the protocols used to produce such proteins. An overview of applications using selectively labeled proteins with an emphasis on examples relevant to the drug discovery process is then presented.

Methyl group assignment using pseudocontact shifts with PARAssign

A new version of the program PARAssign has been evaluated for assignment of NMR resonances of the 76 methyl groups in leucines, isoleucines and valines in a 25 kDa protein, using only the structure of the protein and pseudocontact shifts (PCS) generated with a lanthanoid tag at up to three attachment sites. The number of reliable assignments depends strongly on two factors. The principle axes of the magnetic susceptibility tensors of the paramagnetic centers should not be parallel so as to avoid correlated PCS. Second, the fraction of resonances in the spectrum of a paramagnetic sample that can be paired with the diamagnetic counterparts is critical for the assignment. With the data from two tag positions a reliable assignment could be obtained for 60% of the methyl groups and for many of the remaining resonances the number of possible assignments is limited to two or three. With a single tag, reliable assignments can be obtained for methyl groups with large PCS near the tag. It is concluded that assignment of methyl group resonances by paramagnetic tagging can be particularly useful in combination with some additional data, such as from mutagenesis or NOE-based experiments. Approaches to yield the best assignment results with PCS generating tags are discussed.

NMR in structure-based drug design

NMR spectroscopy is a powerful technique that can provide valuable structural information for drug discovery endeavors. Here, we discuss the strengths (and limitations) of NMR applications to structure-based drug discovery, highlighting the different levels of resolution and throughput obtainable. Additionally, the emerging field of paramagnetic NMR in drug discovery and recent developments in approaches to speed up and automate protein-observed NMR data collection and analysis are discussed.

Fragment library screening identifies hits that bind to the non-catalytic surface of Pseudomonas aeruginosa DsbA1

At a time when the antibiotic drug discovery pipeline has stalled, antibiotic resistance is accelerating with catastrophic implications for our ability to treat bacterial infections. Globally we face the prospect of a future when common infections can once again kill. Anti-virulence approaches that target the capacity of the bacterium to cause disease rather than the growth or survival of the bacterium itself offer a tantalizing prospect of novel antimicrobials. They may also reduce the propensity to induce resistance by removing the strong selection pressure imparted by bactericidal or bacteriostatic agents. In the human pathogen Pseudomonas aeruginosa, disulfide bond protein A (PaDsbA1) plays a central role in the oxidative folding of virulence factors and is therefore an attractive target for the development of new anti-virulence antimicrobials. Using a fragment-based approach we have identified small molecules that bind to PaDsbA1. The fragment hits show selective binding to PaDsbA1 over the DsbA protein from Escherichia coli, suggesting that developing species-specific narrow-spectrum inhibitors of DsbA enzymes may be feasible. Structures of a co-complex of PaDsbA1 with the highest affinity fragment identified in the screen reveal that the fragment binds on the non-catalytic surface of the protein at a domain interface. This biophysical and structural data represent a starting point in the development of higher affinity compounds, which will be assessed for their potential as selective PaDsbA1 inhibitors.

Determination of ligand binding modes in weak protein-ligand complexes using sparse NMR data

We describe a general approach to determine the binding pose of small molecules in weakly bound protein-ligand complexes by deriving distance constraints between the ligand and methyl groups from all methyl-containing residues of the protein. We demonstrate that using a single sample, which can be prepared without the use of expensive precursors, it is possible to generate high-resolution data rapidly and obtain the resonance assignments of Ile, Leu, Val, Ala and Thr methyl groups using triple resonance scalar correlation data. The same sample may be used to obtain Met ^εCH₃ assignments using NOESY-based methods, although the superior sensitivity of NOESY using [U-¹³C,¹⁵N]-labeled protein makes the use of this second sample more efficient. We describe a structural model for a weakly binding ligand bound to its target protein, DsbA, derived from intermolecular methyl-to-ligand nuclear Overhauser enhancements, and demonstrate that the ability to assign all methyl resonances in the spectrum is essential to derive an accurate model of the structure. Once the methyl assignments have been obtained, this approach provides a rapid means to generate structural models for weakly bound protein-ligand complexes. Such weak complexes are often found at the beginning of programs of fragment based drug design and can be challenging to characterize using X-ray crystallography.

Protein-ligand structure guided by backbone and side-chain proton chemical shift perturbations

The fragment-based drug design approach consists of screening libraries of fragment-like ligands, to identify hits that typically bind the protein target with weak affinity (100 μM-5 mM). The determination of the protein-fragment complex 3D structure constitutes a crucial step for uncovering the key interactions responsible for the protein-ligand recognition, and for growing the initial fragment into potent active compounds. The vast majority of fragments are aromatic compounds that induce chemical shift perturbations (CSP) on protein NMR spectra. These experimental CSPs can be quantitatively used to guide the ligand docking, through the comparison between experimental CSPs and CSP back-calculation based on the ring current effect. Here we implemented the CSP back-calculation into the scoring function of the program PLANTS. We compare the results obtained with CSPs measured either on amide or aliphatic protons of the human peroxiredoxin 5. We show that the different kinds of protons lead to different results for resolving the 3D structures of protein-fragment complexes, with the best results obtained with the Hα protons.

Performance of protein-ligand docking with simulated chemical shift perturbations

Protein chemical shift perturbations (CSPs) that result from the binding of a ligand to the protein contain structural information about the complex. Therefore, the CSP data, typically obtained during library screening from two-dimensional (2D) nuclear magnetic resonance (NMR) spectra, are often available before attempts to solve the experimental structure of the complex are started, and can be used to solve the complex structure with CSP-based docking. Here, we compare the performance of the post-docking filter and the guided-docking approaches using either amide or α-proton CSPs with 10 protein-ligand complexes. We show that the comparison of experimental CSPs with CSPs simulated for virtual ligand positions can be used to evidence protein conformational change upon binding and possibly improve the CSP-based docking.

Comparing binding modes of analogous fragments using NMR in fragment-based drug design: application to PRDX5

Fragment-based drug design is one of the most promising approaches for discovering novel and potent inhibitors against therapeutic targets. The first step of the process consists of identifying fragments that bind the protein target. The determination of the fragment binding mode plays a major role in the selection of the fragment hits that will be processed into drug-like compounds. Comparing the binding modes of analogous fragments is a critical task, not only to identify specific interactions between the protein target and the fragment, but also to verify whether the binding mode is conserved or differs according to the fragment modification. While X-ray crystallography is the technique of choice, NMR methods are helpful when this fails. We show here how the ligand-observed saturation transfer difference (STD) experiment and the protein-observed 15N-HSQC experiment, two popular NMR screening experiments, can be used to compare the binding modes of analogous fragments. We discuss the application and limitations of these approaches based on STD-epitope mapping, chemical shift perturbation (CSP) calculation and comparative CSP sign analysis, using the human peroxiredoxin 5 as a protein model.