Current Topics in Medicinal Chemistry - Volume 11, Issue 2, 2011

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The large superfamily of nuclear receptors is a family of ligand-activated transcription factors involved in numerous fundamental processes and shows many common characteristics and behaviors. The comprehension of these roles is of fundamental importance to select the right target for receptor structure-based screening. Recently, during the last ten years, several crystallographic structures of nuclear receptors complexed with ligands have been registered in the Protein Data Bank, supplying a structural basis for computational simulations. The macroscopic flexibility of helix12 and local flexibility of some amino acids sidechains within cavities of the Ligand Binding Domain suggest a reason for the behavior of these receptors toward different ligands. Several approaches have been applied in trying to explain this flexibility and to predict how ligand binding can influence complex conformations. In this short review, we present an introduction to the structure and function of nuclear receptors, specifically the estrogen, androgen, glucorticoid, peroxisome proliferator, steroid, thyroid and vitamin D receptors, and a discussion of the state-of-the-art of induced fit approaches for the nuclear receptor family.

Kynurenic acid (KYNA), one of the metabolites belonging to the kynurenine pathway, has been described as an important neuroprotective compound, its unbalancing being associated with several pathological conditions. In human brain, the majority of KYNA production is sustained by kynurenine aminotransferase II (KAT II). A selective KAT II inhibitor would be an important pharmacological tool, since it would reduce KYNA formation without causing complete depletion of this neuroprotector. (S)-(4)-(ethylsulfonyl)benzoylalanine (S-ESBA), described as a potent and selective inhibitor of rat KAT II, is unfortunately ineffective towards the human enzyme although the two orthologs share a remarkably high degree of sequence identity. We investigated the molecular basis for this intriguing species-specificity by adopting a site-directed mutagenesis and structural approach. We propose that the source of the inhibitor specificity toward the rat enzyme could reside on S-ESBA interaction/interference with a flexible loop that controls ligand admission to the active site by a classical induced-fit mechanism. Our data further highlights that even in case of highly conserved molecular targets, the flexibility of catalytically important structural elements can have a significant impact on the selectivity of inhibitor action.

Protein-ligand binding is a puzzling process. Many theories have been devised since the pioneering key-and-lock hypothesis based on the idea that both the protein and the ligand have a rigid single conformation. Indeed, molecular motion is the essence of the universe. Consequently, not only proteins are characterized by an extraordinary conformational freedom, but ligands too can fluctuate in a rather vast conformational space. In this scenario, the quest to understand how do they match is fascinating. Recognizing that the inherent dynamics of molecules is the key factor controlling the success of binding and, subsequently, of their chemical/biological function, here we present a view of this process from the NMR stand point. A description of the most relevant NMR parameters that can provide insights, at atomic level, on the mechanisms of protein- ligand binding is provided in the final section.

Proper incorporation of protein flexibility for prediction of binding poses and affinities of small compounds has attracted increasing attention recently in computational drug design. Various approaches have been proposed to accommodate protein flexibility in the prediction of binding modes and the binding free energy of ligands in an efficient manner. In this review, the significance of incorporating protein flexibility is discussed from the structural biophysical point of view, and then various approaches of generating protein conformation ensembles, as well as their successes and limitations, are introduced and compared. Special emphasis is on how to generate a proper ensemble of conformation for a specific purpose, as well as the computational efficiency of various approaches. Different searching algorithms for the prediction of optimal binding poses of ligands, which are the core engines of docking programs, are accounted for. Scoring functions for evaluation of protein-ligand complexes are compared. Two end-point methods of free energy calculation, Molecular Mechanics/Poisson-Boltzmann Surface Area (MM/PBSA) and the Linear Interaction Energy (LIE) method, are briefly reviewed. Finally, we also provide an example for the extension of the conventional protein-ligand docking algorithm for prediction of multiple binding sites and ligand translocation pathways.

Proteins can undergo a variety of conformational changes upon ligand binding. Although different mechanisms may play a role, the phenomenon is commonly referred to as induced fit to indicate that the tight structural complementarity of the interaction partners is a consequence of the binding event. Docking methods need to take into account this ability of the ligand and the protein to mutually adapt to each other when forming a complex. Handling the ligand as flexible is already common practice in docking applications. This is not yet the case for the protein. In fact, the accurate prediction of protein conformational changes upon ligand binding is still a major challenge, even more if computational speed is an issue, as for example in virtual screening applications. However, significant progress has been made over the past years and many valuable approaches have become available to address the protein flexibility problem and to provide more reliable docking predictions for complexes governed by significant induced-fit effects. This review provides a brief overview of the current situation, the most recent advances, and the remaining limitations of flexible protein docking, with particular focus on approaches handling protein flexibility simultaneously with ligand placement in the docking process.

The intrinsic dynamics of macromolecules is an essential property to relate the structure of biomolecular systems with their function in the cell. In the field of ligand-receptor recognition, numerous evidences have revealed the limitations of the lock-and-key theory, and the need to elaborate models that take into account the inherent plasticity of biomolecules, such as the induced-fit model or the existence of an ensemble of pre-equilibrated conformations. Depending on the nature of the target system, ligand binding can be associated with small local adjustments in side chains or even the backbone to large-scale motions of structural fragments, domains or even subunits. Reproducing the inherent flexibility of biomolecules has thus become one of the most challenging issues in molecular modeling and simulation studies, as it has direct implications in our understanding of the structure-function relationships, but even in areas such as virtual screening and structure-based drug discovery. Given the intrinsic limitation of conventional simulation tools, only events occurring in short time scales can be reproduced at a high accuracy level through all-atom techniques such as Molecular Dynamics simulations. However, larger structural rearrangements demand the use of enhanced sampling methods relying on modified descriptions of the biomolecular system or the potential surface. This review illustrates the crucial role that structural plasticity plays in mediating ligand recognition through representative examples. In addition, it discusses some of the most powerful computational tools developed to characterize the conformational flexibility in ligand-receptor complexes.

The E. coli glucose-galactose chemosensory receptor is a 309 residue, 32 kDa protein consisting of two distinct structural domains. We used two computational methods to examine the protein's thermal fluctuations, including both the large-scale interdomain movements that contribute to the receptor's mechanism of action, as well as smaller-scale motions. We primarily employ extremely fast, “semi-atomistic” Library-Based Monte Carlo (LBMC) simulations, which include all backbone atoms but “implicit” side chains. Our results were compared with previous experiments and all-atom molecular dynamics (MD) simulation. Both LBMC and MD simulations were performed using both the apo and glucosebound form of the protein, with LBMC exhibiting significantly larger fluctuations. The LBMC simulations are in general agreement with the disulfide trapping experiments of Careaga & Falke (J. Mol. Biol., 1992, Vol. 226, 1219-35), which indicate that distant residues in the crystal structure (i.e. beta carbons separated by 10 to 20 angstroms) form spontaneous transient contacts in solution. Our simulations illustrate several possible “mechanisms” (configurational pathways) for these fluctuations. We also observe several discrepancies between our calculations and experimental rate constants. Nevertheless, we believe that our semi-atomistic approach could be used to study fluctuations in other proteins, perhaps for ensemble docking or other analyses of protein flexibility in virtual screening studies.

Although two main hypotheses of mitochondrial origin have been proposed, i.e., the autogenous and the endosymbiotic, only the second is being seriously considered currently. The ‘hydrogen hypothesis’ invokes metabolic symbiosis as the driving force for a symbiotic association between an anaerobic, strictly hydrogen-dependent (the host) and an eubacterium (the symbiont) that was able to respire, but which generated molecular hydrogen as an end product of anaerobic metabolism. The resulting proto-eukaryotic cell would have acquired the essentials of eukaryotic energy metabolism, evolving not only aerobic respiration, but also the physiological cost of the oxygen consumption, i.e., generation of reactive oxygen species (ROS) and the associated oxidative damage. This is not the only price to pay for respiring oxygen: mitochondria possess nitric oxide (NO•) for regulatory purposes but, in some instances it may react with superoxide anion radical to produce the toxic reactive nitrogen species (RNS), i.e. peroxynitrite anion, and the subsequent nitrosative damage. New mitochondria contain their own genome with a modified genetic code that is highly conserved among mammals. The transcription of certain mitochondrial genes may depend on the redox potential of the mitochondrial membrane. Mitochondria are related to the life and death of cells. They are involved in energy production and conservation, having an uncoupling mechanism to produce heat instead of ATP, but they are also involved in programmed cell death. Increasing evidence suggest the participation of mitochondria in neurodegenerative and neuromuscular diseases involving alterations in both nuclear (nDNA) and mitochondrial (mtDNA) DNA. Melatonin is a known powerful antioxidant and antiinflammatory and increasing experimental and clinical evidence shows its beneficial effects against oxidative/nitrosative stress status, including that involving mitochondrial dysfunction. This review summarizes the data and mechanisms of action of melatonin in relation to mitochondrial pathologies.

Ligands of the benzodiazepine binding site of the GABAA receptor come in three flavors: positive allosteric modulators, negative allosteric modulators and antagonists all of which can bind with high affinity. The GABAA receptor is a pentameric protein which forms a chloride selective ion channel and ligands of the benzodiazepine binding site stabilize three different conformations of this protein. Classical benzodiazepines exert a positive allosteric effect by increasing the apparent affinity of channel opening by the agonist γ-aminobutyric acid (GABA). We concentrate here on the major adult isoform, the α1β2γ2 GABAA receptor. The classical binding pocket for benzodiazepines is located in a subunit cleft between α1 and γ2 subunits in a position homologous to the agonist binding site for GABA that is located between β2 and α1 subunits. We review here approaches to this picture. In particular, point mutations were performed in combination with subsequent analysis of the expressed mutant proteins using either electrophysiological techniques or radioactive ligand binding assays. The predictive power of these methods is assessed by comparing the results with the predictions that can be made on the basis of the recently published crystal structure of the acetylcholine binding protein that shows homology to the N-terminal, extracellular domain of the GABAA receptor. In addition, we review an approach to the question of how the benzodiazepine ligands are positioned in their binding pocket. We also discuss a newly postulated modulatory site for benzodiazepines at the α1/β2 subunit interface, homologous to the classical benzodiazepine binding pocket.