The description of protein internal motions aids selection of ligand binding poses by the INPHARMA method

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.

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.

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.

General order parameter based correlation analysis of protein backbone motions between experimental NMR relaxation measurements and molecular dynamics simulations

Internal backbone dynamic motions are essential for different protein functions and occur on a wide range of time scales, from femtoseconds to seconds. Molecular dynamic (MD) simulations and nuclear magnetic resonance (NMR) spin relaxation measurements are valuable tools to gain access to fast (nanosecond) internal motions. However, there exist few reports on correlation analysis between MD and NMR relaxation data. Here, backbone relaxation measurements of (15)N-labeled SH3 (Src homology 3) domain proteins in aqueous buffer were used to generate general order parameters (S(2)) using a model-free approach. Simultaneously, 80 ns MD simulations of SH3 domain proteins in a defined hydrated box at neutral pH were conducted and the general order parameters (S(2)) were derived from the MD trajectory. Correlation analysis using the Gromos force field indicated that S(2) values from NMR relaxation measurements and MD simulations were significantly different. MD simulations were performed on models with different charge states for three histidine residues, and with different water models, which were SPC (simple point charge) water model and SPC/E (extended simple point charge) water model. S(2) parameters from MD simulations with charges for all three histidines and with the SPC/E water model correlated well with S(2) calculated from the experimental NMR relaxation measurements, in a site-specific manner.

The nuclear Overhauser effect from a quantitative perspective

The nuclear Overhauser enhancement or effect (NOE) is the most important measure in liquid-state NMR with macromolecules. Thus, the NOE is the subject of numerous reviews and books. Here, the NOE is revisited in light of our recently introduced measurements of exact nuclear Overhauser enhancements (eNOEs), which enabled the determination of multiple-state 3D protein structures. This review encompasses all relevant facets from the theoretical considerations to the use of eNOEs in multiple-state structure calculation. Important aspects include a detailed presentation of the relaxation theory relevant for the nuclear Overhauser effect, the estimation of the correction for spin diffusion, the experimental determination of the eNOEs, the conversion of eNOE rates into distances and validation of their quality, the distance-restraint classification and the protocols for calculation of structures and ensembles.