Specific Methyl Group Protonation for the Measurement of Pharmacophore-Specific Interligand NOE Interactions

Methyl probes in proteins for determining ligand binding mode in weak protein-ligand complexes

Structures of protein–ligand complexes provide critical information for drug design. Most protein–ligand complex structures are determined using X-ray crystallography, but where crystallography is not able to generate a structure for a complex, NMR is often the best alternative. However, the available tools to enable rapid and robust structure determination of protein–ligand complexes by NMR are currently limited. This leads to situations where projects are either discontinued or pursued without structural data, rendering the task more difficult. We previously reported the NMR Molecular Replacement (NMR²) approach that allows the structure of a protein–ligand complex to be determined without requiring the cumbersome task of protein resonance assignment. Herein, we describe the NMR² approach to determine the binding pose of a small molecule in a weak protein–ligand complex by collecting sparse protein methyl-to-ligand NOEs from a selectively labeled protein sample and an unlabeled ligand. In the selective labeling scheme all methyl containing residues of the protein are protonated in an otherwise deuterated background. This allows measurement of intermolecular NOEs with greater sensitivity using standard NOESY pulse sequences instead of isotope-filtered NMR experiments. This labelling approach is well suited to the NMR² approach and extends its utility to include larger protein–ligand complexes.

Isobenzofuran-1(3H)-ones as new tyrosinase inhibitors: Biological activity and interaction studies by molecular docking and NMR

Tyrosinase is a multifunctional, glycosylated and copper-containing oxidase enzyme that can be found in animals, plants, and fungi. It is involved in several biological processes such as melanin biosynthesis. In this work, a series of isobenzofuran-1(3H)-ones was evaluated as tyrosinase inhibitors. It was found that compounds phthalaldehydic acid (1), 3-(2,6-dihydroxy-4-isopropylphenyl)isobenzofuran-1(3H)-one (7), and 2-(3-oxo-1,3-dihydroisobenzofuran-1-yl)-1,3-phenylene diacetate (9) were the most potent compounds inhibiting tyrosinase activity in a concentration dependent manner. Ligand-enzyme NMR studies and docking investigations allowed to map the atoms of the ligands involved in the interaction with the copper atoms present in the active site of the tyrosinase. This behaviour is similar to kojic acid, a well know tyrosinase inhibitor and used as positive control in the biological assays. The findings herein described pave the way for future rational design of new tyrosinase inhibitors.

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.

INPHARMA-Based Determination of Ligand Binding Modes at α1 -Adrenergic Receptors Explains the Molecular Basis of Subtype Selectivity

The structural poses of ligands that bind weakly to protein receptors are challenging to define. In this work we have studied ligand interactions with the adrenoreceptor (AR) subtypes, α_1A -AR and α_1B -AR, which belong to the G protein-coupled receptor (GPCR) superfamily, by employing the solution-based ligand-observed NMR method interligand NOEs for pharmacophore mapping (INPHARMA). A lack of receptor crystal structures and of subtype-selective drugs has hindered the definition of the physiological roles of each subtype and limited drug development. We determined the binding pose of the weakly binding α_1A -AR-selective agonist A-61603 relative to an endogenous agonist, epinephrine, at both α_1A -AR and α_1B -AR. The NMR experimental data were quantitatively compared, by using SpINPHARMA, to the back-calculated spectra based on ligand poses obtained from all-atom molecular dynamics simulations. The results helped mechanistically explain the selectivity of (R)-A-61603 towards α_1A -AR, thus demonstrating an approach for targeting subtype selectivity in ARs.

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.

Structure-Based Design of Scaffolds Targeting PDE10A by INPHARMA-NMR

Phosphodiesterases (PDE) hydrolyze both cyclic AMP and GMP (cAMP/cGMP) and are responsible for the regulation of their levels in a multitude of cellular functions. PDE10A is expressed in the brain and is a validated target for both schizophrenia and Huntington disease. Here, we address the identification of novel chemical scaffolds that may bind PDE10A via structure-based drug design. For this task, we use INPHARMA, an NMR-based method that measures protein-mediated interligand NOEs between pairs of weakly, competitively binding ligands. INPHARMA is applied to a combination of four chemically diverse PDE10A binding fragments, with the aim of merging their pharmacophoric features into a larger, tighter binding molecule. All four ligands bind the PDE10A cAMP binding domain with affinity in the micromolar range. The application of INPHARMA to identify the correct docking poses of these ligands is challenging due to the nature of the binding pocket and the high content of water-mediated intermolecular contacts. Nevertheless, ensemble docking in the presence of conserved water molecules generates docking poses that are in agreement with all sets of INPHARMA data. These poses are used to build a pharmacophore model with which we search the ZINC database.

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.

On-the-Fly Integration of Data from a Spin-Diffusion-Based NMR Experiment into Protein-Ligand Docking

INPHARMA (interligand nuclear Overhauser enhancement for pharmacophore mapping) determines the relative orientation of two competitive ligands in the protein binding pocket. It is based on the observation of interligand transferred NOEs mediated by spin diffusion through protons of the protein and is, therefore, sensitive to the specific interactions of each of the two ligands with the protein. We show how this information can be directly included into a protein-ligand docking program to guide the prediction of the complex structures. Agreement between the experimental and back-calculated spectra based on the full relaxation matrix approach is translated into a score contribution that is combined with the scoring function ChemPLP of our docking tool PLANTS. This combined score is then used to predict the poses of five weakly bound cAMP-dependent protein kinase (PKA) ligands. After optimizing the setup, which finally also included trNOE data and optimized protonation states, very good success rates were obtained for all combinations of three ligands. For one additional ligand, no conclusive results could be obtained due to the ambiguous electron density of the ligand in the X-ray structure, which does not disprove alternative ligand poses. The failures of the remaining ligand are caused by suboptimal locations of specific protein side chains. Therefore, side-chain flexibility should be included in an improved INPHARMA-PLANTS version. This will reduce the strong dependence on the used protein input structure leading to improved scores overall, not only for this last ligand.

De novo fragment-based design of inhibitors of DXS guided by spin-diffusion-based NMR spectroscopy

A ligand-based NMR methodology (STI) enabled de novo fragment-based design of inhibitors of the enzyme DXS present in the non-mevalonate pathway in the absence of X-ray co-crystal structures.

Relaxation Matrix Analysis of Spin Diffusion for the NMR Structure Calculation with eNOEs

NMR structure determination is usually based on distance restraints extracted semiquantitatively from cross peak volumes or intensities in NOESY spectra. The recent introduction of exact NOEs (eNOE) by Vogeli et al. opens an avenue for the ensemble-based structure determination of proteins on the basis of eNOE-derived quantitative distance restraints. We present an approach to extract eNOE from build-up curve intensities. For the determination of eNOEs, spin diffusion is a major source of errors. A full relaxation matrix analysis is used to calculate the spin diffusion contribution to the NOESY cross peaks of each individual spin pair of interest. A software program is written, which requires as input the peak intensities from the various NOESY spectra as well as a 3D structure of the protein. This structure can be either an X-ray structure or an NMR structure determined with the conventional approach. The outputs of the program are the eNOE rates, the autorelaxation rates, as well as graphs and quality factors from the individual NOE build-up curves for semiautomated analysis of the derived rates. The protocol is straightforward, and the program integrates well into the current structure calculation workflow.

Pharmacophore-based virtual screening

This chapter is a review of the most recent developments in the field of pharmacophore modeling, covering both methodology and application. Pharmacophore-based virtual screening is nowadays a mature technology, very well accepted in the medicinal chemistry laboratory. Nevertheless, like any empirical approach, it has specific limitations and efforts to improve the methodology are still ongoing. Fundamentally, the core idea of "stripping" functional groups of their actual chemical nature in order to classify them into very few pharmacophore types, according to their dominant physico-chemical features, is both the main advantage and the main drawback of pharmacophore modeling. The advantage is the one of simplicity - the complex nature of noncovalent ligand binding interactions is rendered intuitive and comprehensible by the human mind. Although computers are much better suited for comparisons of pharmacophore patterns, a chemist's intuition is primarily scaffold-oriented. Its underlying simplifications render pharmacophore modeling unable to provide perfect predictions of ligand binding propensities - not even if all its subsisting technical problems would be solved. Each step in pharmacophore modeling and exploitation has specific drawbacks: from insufficient or inaccurate conformational sampling to ambiguities in pharmacophore typing (mainly due to uncertainty regarding the tautomeric/protonation status of compounds), to computer time limitations in complex molecular overlay calculations, and to the choice of inappropriate anchoring points in active sites when ligand cocrystals structures are not available. Yet, imperfections notwithstanding, the approach is accurate enough in order to be practically useful and actually is the most used virtual screening technique in medicinal chemistry - notably for "scaffold hopping" approaches, allowing the discovery of new chemical classes carriers of a desired biological activity.

The INPHARMA technique for pharmacophore mapping: A theoretical guide to the method

During the process of drug discovery, INPHARMA can be used to derive the structure of receptor/lead compound complexes binding to each other with a K(d) in the microM to mM range. To be successful, the methodology needs adjustment of various parameters that depend on the physical constants of the binding event and on the receptor size. Here we present a thorough theoretical analysis of the INPHARMA interligand NOE effect in dependence of experimental parameters and physical constants. This analysis helps the experimentalist to choose the correct experimental parameters and consequentially to achieve optimal performance of the methodology.