How Much NMR Data Is Required To Determine a Protein-Ligand Complex Structure?

Protein-ligand structure determination with the NMR molecular replacement tool, NMR2

We recently reported on a new method called NMR Molecular Replacement that efficiently derives the structure of a protein-ligand complex at the interaction site. The method was successfully applied to high and low affinity complexes covering ligands from peptides to small molecules. The algorithm used in the NMR Molecular Replacement program has until now not been described in detail. Here, we present a complete description of the NMR Molecular Replacement implementation as well as several new features that further reduce the time required for structure elucidation.

NMR as a "Gold Standard" Method in Drug Design and Discovery

Studying disease models at the molecular level is vital for drug development in order to improve treatment and prevent a wide range of human pathologies. Microbial infections are still a major challenge because pathogens rapidly and continually evolve developing drug resistance. Cancer cells also change genetically, and current therapeutic techniques may be (or may become) ineffective in many cases. The pathology of many neurological diseases remains an enigma, and the exact etiology and underlying mechanisms are still largely unknown. Viral infections spread and develop much more quickly than does the corresponding research needed to prevent and combat these infections; the present and most relevant outbreak of SARS-CoV-2, which originated in Wuhan, China, illustrates the critical and immediate need to improve drug design and development techniques. Modern day drug discovery is a time-consuming, expensive process. Each new drug takes in excess of 10 years to develop and costs on average more than a billion US dollars. This demonstrates the need of a complete redesign or novel strategies. Nuclear Magnetic Resonance (NMR) has played a critical role in drug discovery ever since its introduction several decades ago. In just three decades, NMR has become a "gold standard" platform technology in medical and pharmacology studies. In this review, we present the major applications of NMR spectroscopy in medical drug discovery and development. The basic concepts, theories, and applications of the most commonly used NMR techniques are presented. We also summarize the advantages and limitations of the primary NMR methods in drug development.

PI by NMR: Probing CH-π Interactions in Protein-Ligand Complexes by NMR Spectroscopy

While CH–π interactions with target proteins are crucial determinants for the affinity of arguably every drug molecule, no method exists to directly measure the strength of individual CH–π interactions in drug–protein complexes. Herein, we present a fast and reliable methodology called PI (π interactions) by NMR, which can differentiate the strength of protein–ligand CH–π interactions in solution. By combining selective amino‐acid side‐chain labeling with ¹H‐¹³C NMR, we are able to identify specific protein protons of side‐chains engaged in CH–π interactions with aromatic ring systems of a ligand, based solely on ¹H chemical‐shift values of the interacting protein aromatic ring protons. The information encoded in the chemical shifts induced by such interactions serves as a proxy for the strength of each individual CH–π interaction. PI by NMR changes the paradigm by which chemists can optimize the potency of drug candidates: direct determination of individual π interactions rather than averaged measures of all interactions.

Characterization of Dynamic IDP Complexes by NMR Spectroscopy

NMR spectroscopy has proven to be a key method for studying intrinsically disordered proteins (IDPs). Nonetheless, traditional NMR methods developed for solving structures of ordered protein complexes are insufficient for the full characterization of dynamic IDP complexes, where the energy landscape is broader and more rugged. Furthermore, due to their high sensitivity to environmental changes, NMR studies of IDP complexes must be conducted with extra care and the observed NMR parameters thoroughly evaluated to enable disentanglement of binding events from ensemble distribution changes. In this chapter, written for the non-NMR expert, we start out by outlining sample preparation for IDP complexes, guide through the recording and evaluation of diagnostic ¹H,¹⁵N-HSQC spectra, and delineate more sophisticated NMR strategies to follow for the particular type of complex. The most relevant experiments are then described in terms of aims, needs, pitfalls, analysis, and expected outcomes, with references to recent examples.

The NMR2 Method to Determine Rapidly the Structure of the Binding Pocket of a Protein–Ligand Complex with High Accuracy

Structural characterization of complexes is crucial for a better understanding of biological processes and structure-based drug design. However, many protein–ligand structures are not solvable by X-ray crystallography, for example those with low affinity binders or dynamic binding sites. Such complexes are usually targeted by solution-state NMR spectroscopy. Unfortunately, structure calculation by NMR is very time consuming since all atoms in the complex need to be assigned to their respective chemical shifts. To circumvent this problem, we recently developed the Nuclear Magnetic Resonance Molecular Replacement (NMR2) method. NMR2 very quickly provides the complex structure of a binding pocket as measured by solution-state NMR. NMR2 circumvents the assignment of the protein by using previously determined structures and therefore speeds up the whole process from a couple of months to a couple of days. Here, we recall the main aspects of the method, show how to apply it, discuss its advantages over other methods and outline its limitations and future directions.

NMR-Based Determination of the 3D Structure of the Ligand-Protein Interaction Site without Protein Resonance Assignment

Molecular replacement in X-ray crystallography is the prime method for establishing structure-activity relationships of pharmaceutically relevant molecules. Such an approach is not available for NMR. Here, we establish a comparable method, called NMR molecular replacement (NMR(2)). The method requires experimentally measured ligand intramolecular NOEs and ligand-protein intermolecular NOEs as well as a previously known receptor structure or model. Our findings demonstrate that NMR(2) may open a new avenue for the fast and robust determination of the interaction site of ligand-protein complexes at atomic resolution.

Current Status and Future Direction of Fragment-Based Drug Discovery: A Computational Chemistry Perspective

Fragment-based drug discovery (FBDD) has become a well-established and widely used approach for lead identification. The computational chemistry community has played a central role in developing the ideas behind this area of research and computational tools are important throughout FBDD campaigns. This article discusses the evolution of best practice, on-going areas of debate and gaps in current capabilities from a computational chemistry perspective. In particular, the contribution of computational methods to areas such as fragment library design, screening analysis, data handling and the role of structure- and ligand-based design is discussed. The potential to combine FBDD with other hit-identification methods such as high-throughput screening in a more integrated approach is also highlighted.

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.

Using chemical shift perturbation to characterise ligand binding

Chemical shift perturbation (CSP, chemical shift mapping or complexation-induced changes in chemical shift, CIS) follows changes in the chemical shifts of a protein when a ligand is added, and uses these to determine the location of the binding site, the affinity of the ligand, and/or possibly the structure of the complex. A key factor in determining the appearance of spectra during a titration is the exchange rate between free and bound, or more specifically the off-rate koff. When koff is greater than the chemical shift difference between free and bound, which typically equates to an affinity Kd weaker than about 3μM, then exchange is fast on the chemical shift timescale. Under these circumstances, the observed shift is the population-weighted average of free and bound, which allows Kd to be determined from measurement of peak positions, provided the measurements are made appropriately. (1)H shifts are influenced to a large extent by through-space interactions, whereas (13)Cα and (13)Cβ shifts are influenced more by through-bond effects. (15)N and (13)C' shifts are influenced both by through-bond and by through-space (hydrogen bonding) interactions. For determining the location of a bound ligand on the basis of shift change, the most appropriate method is therefore usually to measure (15)N HSQC spectra, calculate the geometrical distance moved by the peak, weighting (15)N shifts by a factor of about 0.14 compared to (1)H shifts, and select those residues for which the weighted shift change is larger than the standard deviation of the shift for all residues. Other methods are discussed, in particular the measurement of (13)CH3 signals. Slow to intermediate exchange rates lead to line broadening, and make Kd values very difficult to obtain. There is no good way to distinguish changes in chemical shift due to direct binding of the ligand from changes in chemical shift due to allosteric change. Ligand binding at multiple sites can often be characterised, by simultaneous fitting of many measured shift changes, or more simply by adding substoichiometric amounts of ligand. The chemical shift changes can be used as restraints for docking ligand onto protein. By use of quantitative calculations of ligand-induced chemical shift changes, it is becoming possible to determine not just the position but also the orientation of ligands.

Small-molecule binding sites on proteins established by paramagnetic NMR spectroscopy

Determining the three-dimensional structure of a small molecule-protein complex with weak affinity can be a significant challenge. We present a paramagnetic NMR method to determine intermolecular structure restraints based on pseudocontact shifts (PCSs). Since the ligand must be in fast exchange between free and bound states and the fraction bound can be as low as a few percent, the method is ideal for ligands with high micromolar to millimolar dissociation constants. Paramagnetic tags are attached, one at a time, in a well-defined way via two arms at several sites on the protein surface. The ligand PCSs were measured from simple 1D (1)H spectra and used as docking restraints. An independent confirmation of the complex structure was carried out using intermolecular NOEs. The results show that structures derived from these two approaches are similar. The best results are obtained if the magnetic susceptibility tensors of the tags are known, but it is demonstrated that with two-armed probes, the magnetic susceptibility tensor can be predicted with sufficient accuracy to provide a low-resolution model of the ligand orientation and the location of the binding site in the absence of isotope-labeled protein. This approach can facilitate fragment-based drug discovery in obtaining structural information on the initial fragment hits.

Fragment screening of GPCRs using biophysical methods: identification of ligands of the adenosine A(2A) receptor with novel biological activity

Fragment-based drug discovery (FBDD) has proven a powerful method to develop novel drugs with excellent oral bioavailability against challenging pharmaceutical targets such as protein-protein interaction targets. Very recently the underlying biophysical techniques have begun to be successfully applied to membrane proteins. Here we show that novel, ligand efficient small molecules with a variety of biological activities can be found by screening a small fragment library using thermostabilized (StaR) G protein-coupled receptors (GPCRs) and target immobilized NMR screening (TINS). Detergent-solubilized StaR adenosine A(2A) receptor was immobilized with retention of functionality, and a screen of 531 fragments was performed. Hits from the screen were thoroughly characterized for biochemical activity using the wild-type receptor. Both orthosteric and allosteric modulatory activity has been demonstrated in biochemical validation assays. Allosteric activity was confirmed in cell-based functional assays. The validated fragment hits make excellent starting points for a subsequent hit-to-lead elaboration program.

NMR studies of DOXP reductoisomerase and its inhibitor complex

1-Deoxy-D-xylulose 5-phosphate (DOXP) reductoisomerase (EC1.1.1.267) catalyses the second step of the 2-C-methyl-D-erythritol 4-phosphate (MEP) pathway of isoprenoid biosynthesis. The enzyme is used by most bacteria, apicomplexan parasites and the plastids of plants, but not by humans, and therefore represents an attractive target for antibacterial, antiparasitic and herbicidal compounds. Fosmidomycin, an inhibitor of DXR, has been found to be active against bacterial infections and malaria in early clinical studies. Here, we report sample optimisation, partial backbone assignment and secondary-structure prediction of E. coli DXR by heteronuclear NMR analysis for further NMR-aided drug discovery. Perdeuterated (15)N,(13)C-labelled samples were prepared under oxygen exclusion in the presence of Mg(2+), NADPH and the inhibitor FR-900098, a close derivative of fosmidomycin. (1)H and (15)N backbone assignment was achieved for 44 % of the primary structure, and (13)C backbone assignment was achieved for 50 % of the primary structure. Comparison with previously solved crystal structures revealed that the assigned fragments were located mainly in helical regions on the solvent-exposed surface of the enzyme. Torsion angle likelihood obtained from shift and sequence similarity (TALOS) was used for secondary structure prediction, resulting in agreement with eight available crystal structures; deviations could be observed for the catalytic loop region.

Application of NMR and molecular docking in structure-based drug discovery

Drug discovery is a complex and costly endeavor, where few drugs that reach the clinical testing phase make it to market. High-throughput screening (HTS) is the primary method used by the pharmaceutical industry to identify initial lead compounds. Unfortunately, HTS has a high failure rate and is not particularly efficient at identifying viable drug leads. These shortcomings have encouraged the development of alternative methods to drive the drug discovery process. Specifically, nuclear magnetic resonance (NMR) spectroscopy and molecular docking are routinely being employed as important components of drug discovery research. Molecular docking provides an extremely rapid way to evaluate likely binders from a large chemical library with minimal cost. NMR ligand-affinity screens can directly detect a protein-ligand interaction, can measure a corresponding dissociation constant, and can reliably identify the ligand binding site and generate a co-structure. Furthermore, NMR ligand affinity screens and molecular docking are perfectly complementary techniques, where the combination of the two has the potential to improve the efficiency and success rate of drug discovery. This review will highlight the use of NMR ligand affinity screens and molecular docking in drug discovery and describe recent examples where the two techniques were combined to identify new and effective therapeutic drugs.

Characterization of the interactions of vMIP-II, and a dimeric variant of vMIP-II, with glycosaminoglycans

Chemokines are important immune proteins, carrying out their function by binding to glycosaminoglycans (GAGs) on the endothelial surface and to cell surface chemokine receptors. A unique viral chemokine analogue, viral macrophage inflammatory protein-II (vMIP-II), encoded by human herpesvirus-8, has garnered interest because of its ability to bind to multiple chemokine receptors, including both HIV coreceptors. In addition, vMIP-II binds to cell surface GAGs much more tightly than most human chemokines, which may be the key to its anti-inflammatory function in vivo. The goal of this work was to determine the mechanism of binding of GAG by vMIP-II. The interaction of vMIP-II with a heparin-derived disaccharide was characterized using NMR. Important binding sites were further analyzed by mutagenesis studies, in which corresponding vMIP-II mutants were tested for GAG binding ability using heparin chromatography and NMR. We found that despite having many more basic residues than some chemokines, vMIP-II shares a characteristic binding site similar to that of its human analogues, utilizing basic residues R18, R46, and R48. Interestingly, a particular mutation (Leu13Phe) caused vMIP-II to form a pH-dependent CC chemokine-type dimer as determined by analytical ultracentrifugation and NMR. To the best of our knowledge, this is the first example of engineering a naturally predominantly monomeric chemokine into a dissociable dimer by a single mutation. This dimeric vMIP-II mutant binds to heparin much more tightly than wild-type vMIP-II and provides a new model for studying the relationship between chemokine quaternary structure and various aspects of function. Structural differences between monomeric and dimeric vMIP-II upon GAG binding were characterized by NMR and molecular docking.

Structural basis for platelet antiaggregation by angiotensin II type 1 receptor antagonist losartan (DuP-753) via glycoprotein VI

GPVI is a key receptor for collagen-induced platelet activation. Loss or inhibition of GPVI causes only mildly prolonged bleeding times but prevents arterial thrombus formation in animal models. Therefore, GPVI is considered to be a potent target molecule for therapy of thrombotic diseases. Recently, it was reported that the AT(1)-receptor antagonist losartan (DuP-753) and EXP3179 inhibit platelet adhesion and aggregation via GPVI. However, it is still not clear how losartan is associated with inhibition of binding between GPVI and collagen at the molecular level. Here, we show by NMR that losartan directly interacts with the hydrophobic region consisting of strands C' and E in the N-terminal Ig-like domain of GPVI. A reliable GPVI-losartan complex model is presented by using a combination of NMR data and in silico tools. These data indicated that the phenyl group with the tetrazole ring in losartan plays a crucial role in the interaction with GPVI.

Use of quantitative (1)H NMR chemical shift changes for ligand docking into barnase

(1)H NMR complexation-induced changes in chemical shift (CIS) of HN protons have been used to characterize the complexes of barnase with the deoxyoligonucleotides d(GC) and d(CGAC). Quantitative shift changes are used not only to locate the most probable binding site (using ring-current shifts), but also to determine the orientation of the ligand within the binding site, based on a more complete shift calculation including bond magnetic anisotropies and electric field effects. For both ligands, the guanine is in the same binding site cleft, in the same position as identified in the crystal structure of the d(CGAC) complex. By contrast, a previous X-ray crystal structure of the d(GC) complex showed the ligand in the mouth of the active site, rather than at the guanyl-specific site, implying that the location may be an artifact of the crystallisation process.

Influence of conformational flexibility on complexation-induced changes in chemical shift in a neocarzinostatin protein-ligand complex

In this paper is described an analysis of the effects of protein flexibility on the observed CIS values and the impact on the accuracy of 3D structures determined using a (1)H NMR CIS approach. The effects of protein conformational mobility have been investigated by using a set of different protein structures as starting points for the calculation: the unbound X-ray crystal structure, the unbound NMR solution structure, and the bound NMR solution structure of the protein. The results indicated that loop movement does have a significant impact on the quality of the structure generated by the CIS structure determination methodology. The implementation of methods to treat loop flexibility within our protocol, however, did not improve the results for calculations based on the unbound protein frame.

Determination of protein-ligand binding modes using complexation-induced changes in (1)h NMR chemical shift

A new method for determining three-dimensional solution structures of protein-ligand complexes using experimentally determined complexation-induced changes in (1)H NMR chemical shift (CIS) is introduced. The method has been validated using the complex formed between the protein antitumor antibiotic neocarzinostatin (NCS) and a synthetic chromophore analogue. The X-ray crystal structure of the unbound protein and the backbone amide proton CIS were the input data used in the determination of the three-dimensional structure of the complex. The experimental CIS values were used in a continuous direct structure refinement process based on genetic algorithms to sample conformational space. The calculated structure of the complex agrees well with the NMR solution structure, indicating the potential of this approach for structure determination.

Glycyrrhizin binds to high-mobility group box 1 protein and inhibits its cytokine activities

High-mobility group box 1 protein (HMGB1) is a nuclear component, but extracellularly it serves as a signaling molecule involved in acute and chronic inflammation, for example in sepsis and arthritis. The identification of HMGB1 inhibitors is therefore of significant experimental and clinical interest. We show that glycyrrhizin, a natural anti-inflammatory and antiviral triterpene in clinical use, inhibits HMGB1 chemoattractant and mitogenic activities, and has a weak inhibitory effect on its intranuclear DNA-binding function. NMR and fluorescence studies indicate that glycyrrhizin binds directly to HMGB1 (K(d) approximately 150 microM), interacting with two shallow concave surfaces formed by the two arms of both HMG boxes. Our results explain in part the anti-inflammatory properties of glycyrrhizin, and might direct the design of new derivatives with improved HMGB1-binding properties.

Rapid protein-ligand costructures using chemical shift perturbations

Structure-based drug discovery requires the iterative determination of protein-ligand costructures in order to improve the binding affinity and selectivity of potential drug candidates. In general, X-ray and NMR structure determination methods are time consuming and are typically the limiting factor in the drug discovery process. The application of molecular docking simulations to filter and evaluate drug candidates has become a common method to improve the throughput and efficiency of structure-based drug design. Unfortunately, molecular docking methods suffer from common problems that include ambiguous ligand conformers or failure to predict the correct docked structure. A rapid approach to determine accurate protein-ligand costructures is described based on NMR chemical shift perturbation (CSP) data routinely obtained using 2D 1H-15N HSQC spectra in high-throughput ligand affinity screens. The CSP data is used to both guide and filter AutoDock calculations using our AutoDockFilter program. This method is demonstrated for 19 distinct protein-ligand complexes where the docked conformers exhibited an average rmsd of 1.17 +/- 0.74 A relative to the original X-ray structures for the protein-ligand complexes.

Protein-ligand NOE matching: a high-throughput method for binding pose evaluation that does not require protein NMR resonance assignments

Given the three-dimensional (3D) structure of a protein, the binding pose of a ligand can be determined using distance restraints derived from assigned intra-ligand and protein-ligand nuclear Overhauser effects (NOEs). A primary limitation of this approach is the need for resonance assignments of the ligand-bound protein. We have developed an approach that utilizes data from 3D 13C-edited, 13C/15N-filtered HSQC-NOESY spectra for evaluating ligand binding poses without requiring protein NMR resonance assignments. Only the 1H NMR assignments of the bound ligand are essential. Trial ligand binding poses are generated by any suitable method (e.g., computational docking). For each trial binding pose, the 3D 13C-edited, 13C/15N-filtered HSQC-NOESY spectrum is predicted, and the predicted and observed patterns of protein-ligand NOEs are matched and scored using a fast, deterministic bipartite graph matching algorithm. The best scoring (lowest "cost") poses are identified. Our method can incorporate any explicit restraints or protein assignment data that are available, and many extensions of the basic procedure are feasible. Only a single sample is required, and the method can be applied to both slowly and rapidly exchanging ligands. The method was applied to three test cases: one complex involving muscle fatty acid-binding protein (mFABP) and two complexes involving the leukocyte function-associated antigen 1 (LFA-1) I-domain. Without using experimental protein NMR assignments, the method identified the known binding poses with good accuracy. The addition of experimental protein NMR assignments improves the results. Our "NOE matching" approach is expected to be widely applicable; i.e., it does not appear to depend on a fortuitous distribution of binding pocket residues.

Identification of individual protein-ligand NOEs in the limit of intermediate exchange

Interactions of proteins with small molecules or other macromolecules play key roles in many biological processes and in drug action, and NMR is an excellent tool for their structural characterization. Frequently, however, line broadening due to intermediate exchange completely eliminates the signals needed for measuring specific intermolecular NOEs. This limits the use of NMR for detailed structural studies in such kinetic situations. Here we show that an optimally chosen excess of ligand over protein can reduce the extent of line broadening for both the ligand and the protein. This makes observation of ligand resonances possible but reduces the size of the measurable NOEs due to the residual line broadening and the non-stoichiometric concentrations. Because the solubility of small molecule drug leads are often limited to high micromolar concentrations, protein concentrations are restricted to even lower values in the low micromolar range. At these non-stoichiometric concentrations and in the presence of significant residual line broadening, conventional NOESY experiments very often are not sensitive enough to observe intermolecular NOEs since the signals inverted by the NOESY preparation pulse sequence relax prior to significant NOE build up. Thus, we employ methods related to driven NOE spectroscopy to investigate protein-ligand interactions in the intermediate exchange regime. In this approach, individual protein resonances are selectively irradiated for up to five seconds to build up measurable NOEs at the ligand resonances. To enable saturation of individual protein resonances we prepare deuterated protein samples selectively protonated at a few sites so that the 1D (1)H spectrum of the protein is resolved well enough to permit irradiation of individual protein signals, which do not overlap with the ligand spectrum. This approach is suitable for measuring a sufficiently large number of protein-ligand NOEs that allow calculation of initial complex structures, suitable for structure-based optimization of primary drug leads obtained from high-throughput screening. The method was applied to measure individual intermolecular NOEs between the anti-apoptotic protein Bcl-xL at 25 microM and a "first generation" small-molecule ligand, for which the spectrum is entirely broadened at stoichiometric concentrations. This approach is general and can also be used to characterize protein-protein or protein-nucleic-acid complexes.

Biomolecular NMR: a chaperone to drug discovery

Biomolecular NMR now contributes routinely to every step in the development of new chemical entities ahead of clinical trials. The versatility of NMR--from detection of ligand binding over a wide range of affinities and a wide range of drug targets with its wealth of molecular information, to metabolomic profiling, both ex vivo and in vivo--has paved the way for broadly distributed applications in academia and the pharmaceutical industry. Proteomics and initial target selection both benefit from NMR: screenings by NMR identify lead compounds capable of inhibiting protein-protein interactions, still one of the most difficult development tasks in drug discovery. NMR hardware improvements have given access to the microgram domain of phytochemistry, which should lead to the discovery of novel bioactive natural compounds. Steering medicinal chemists through the lead optimisation process by providing detailed information about protein-ligand interactions has led to impressive success in the development of novel drugs. The study of biofluid composition--metabonomics--provides information about pharmacokinetics and helps toxicological safety assessment in animal model systems. In vivo, magnetic resonance spectroscopy interrogates metabolite distributions in living cells and tissues with increasing precision, which significantly impacts the development of anticancer or neurological disorder therapeutics. An overview of different steps in recent drug discovery is presented to illuminate the links with the most recent advances in NMR methodology.

Combining in Silico Tools and NMR Data To Validate Protein−Ligand Structural Models: Application to Matrix Metalloproteinases

A combination of in silico tools and experimental NMR data is proposed for relatively fast determination of protein-ligand structural models and demonstrated from known inhibitors of matrix metalloproteinases (MMP). The 15N 1H heteronuclear single quantum coherence (HSQC) spectral assignment and the 3D structure, either X-ray or NMR, are needed. In this method, the HSQC spectrum with or without the ligand is used to determine the interaction region of the ligand. Docking calculations are then performed to obtain a set of structural models. From the latter, the nuclear Overhauser effects (NOEs) between the ligand and the protein can be predicted. Guided by these predictions, a number of NOEs can be detected and assigned through a HSQC NOESY experiment. These data are used as structural restraints to reject/refine the initial structural models through further in silico work. For a test protein (MMP-12, human macrophage metalloelastase), a final structure of a protein-ligand adduct was obtained that matches well with the full structural determination. A number of structural predictions were then made for adducts of a similar protein (MMP-1, human fibroblast collagenase) with the same and different ligands. The quality of the final results depended on the type and number of experimental NOEs, but in all cases, a well-defined ligand conformation in the protein binding site was obtained. This protocol is proposed as a viable alternative to the many approaches described in the literature.