Oligomers of D-2 dopamine receptors - Evidence from ligand binding

There is increasing evidence that G protein-coupled receptors form oligomers and that this might be important for their function. We have studied this phenomenon for the D-2 dopamine receptor and have shown-using a variety of biochemical and biophysical techniques-that this receptor forms dimers or higher-order oligomers. Using ligand-binding studies, we have also found evidence that this oligomer formation has functional relevance. Thus, for the receptor expressed in either CHO cells or Sf 9 insect cells, the binding properties of several radioligands (in saturation, competition, and dissociation assays) do not conform to those expected for a monomeric receptor with a single binding site. We propose that the receptors exist in oligomers with homotropic and heterotropic negatively cooperative interactions between ligands.

Oligomers of D-2 dopamine receptors: evidence from ligand binding

There is increasing evidence that G protein-coupled receptors form oligomers and that this might be important for their function. We have studied this phenomenon for the D-2 dopamine receptor and have shown-using a variety of biochemical and biophysical techniques-that this receptor forms dimers or higher-order oligomers. Using ligand-binding studies, we have also found evidence that this oligomer formation has functional relevance. Thus, for the receptor expressed in either CHO cells or Sf 9 insect cells, the binding properties of several radioligands (in saturation, competition, and dissociation assays) do not conform to those expected for a monomeric receptor with a single binding site. We propose that the receptors exist in oligomers with homotropic and heterotropic negatively cooperative interactions between ligands

Modelling the interdependence between the stoichiometry of receptor oligomerization and ligand binding for a coexisting dimer/tetramer receptor system

Many G protein-coupled receptors have been shown to exist as oligomers, but the oligomerization state and the effects of this on receptor function are unclear. For some G protein-coupled receptors, in ligand binding assays, different radioligands provide different maximal binding capacities. Here we have developed mathematical models for co-expressed dimeric and tetrameric species of receptors. We have considered models where the dimers and tetramers are in equilibrium and where they do not interconvert and we have also considered the potential influence of the ligands on the degree of oligomerization. By analogy with agonist efficacy, we have considered ligands that promote, inhibit or have no effect on oligomerization. Cell surface receptor expression and the intrinsic capacity of receptors to oligomerize are quantitative parameters of the equations. The models can account for differences in the maximal binding capacities of radioligands in different preparations of receptors and provide a conceptual framework for simulation and data fitting in complex oligomeric receptor situations.

FunFOLDQA: a quality assessment tool for protein-ligand binding site residue predictions

The estimation of prediction quality is important because without quality measures, it is difficult to determine the usefulness of a prediction. Currently, methods for ligand binding site residue predictions are assessed in the function prediction category of the biennial Critical Assessment of Techniques for Protein Structure Prediction (CASP) experiment, utilizing the Matthews Correlation Coefficient (MCC) and Binding-site Distance Test (BDT) metrics. However, the assessment of ligand binding site predictions using such metrics requires the availability of solved structures with bound ligands. Thus, we have developed a ligand binding site quality assessment tool, FunFOLDQA, which utilizes protein feature analysis to predict ligand binding site quality prior to the experimental solution of the protein structures and their ligand interactions. The FunFOLDQA feature scores were combined using: simple linear combinations, multiple linear regression and a neural network. The neural network produced significantly better results for correlations to both the MCC and BDT scores, according to Kendall’s τ, Spearman’s ρ and Pearson’s r correlation coefficients, when tested on both the CASP8 and CASP9 datasets. The neural network also produced the largest Area Under the Curve score (AUC) when Receiver Operator Characteristic (ROC) analysis was undertaken for the CASP8 dataset. Furthermore, the FunFOLDQA algorithm incorporating the neural network, is shown to add value to FunFOLD, when both methods are employed in combination. This results in a statistically significant improvement over all of the best server methods, the FunFOLD method (6.43%), and one of the top manual groups (FN293) tested on the CASP8 dataset. The FunFOLDQA method was also found to be competitive with the top server methods when tested on the CASP9 dataset. To the best of our knowledge, FunFOLDQA is the first attempt to develop a method that can be used to assess ligand binding site prediction quality, in the absence of experimental data.

Retinoid-Related Receptor (ROR) alpha mRNA Expression Is Altered in the Brain of Male Mice Lacking All Ligand-Binding Thyroid Hormone Receptor (TR) Isoforms

In the vertebrate brain, the thalamus serves as a relay and integration station for diverse neuronal information en route from the periphery to the cortex. Deficiency of TH during development results in severe cerebral abnormalities similar to those seen in the mouse when the retinoic acid receptor (ROR)α gene is disrupted. To investigate the effect of the thyroid hormone recep-tors (TRs) on RORalpha gene expression, we used intact male mice, in which the genes encoding the α and beta TRs have been deleted. In situ hybridization for RORalpha mRNA revealed that this gene is expressed in specific areas of the brain including the thalamus, pons, cerebellum, cortex, and hippocampus. Our quantitative data showed differences in RORalpha mRNA expression in different subthalamic nuclei between wild-type and knock-out mice. For example, the centromedial nucleus of the thalamus, which plays a role in mediating nociceptive and visceral information from the brainstem to the basal ganglia and cortical regions, has less expression of RORalpha mRNA in the knockout mice (-37%) compared to the wild-type controls. Also, in the dorsal geniculate (+72%) and lateral posterior nuclei (+58%) we found more RORalpha mRNA in dKO as compared to dWT animals. Such differences in RORalpha mRNA expression may play a role in the behavioral alterations resulting from congenital hypothyroidism.

In silico identification and characterization of protein-ligand binding sites

Protein–ligand binding site prediction methods aim to predict, from amino acid sequence, protein–ligand interactions, putative ligands, and ligand binding site residues using either sequence information, structural information, or a combination of both. In silico characterization of protein–ligand interactions has become extremely important to help determine a protein’s functionality, as in vivo-based functional elucidation is unable to keep pace with the current growth of sequence databases. Additionally, in vitro biochemical functional elucidation is time-consuming, costly, and may not be feasible for large-scale analysis, such as drug discovery. Thus, in silico prediction of protein–ligand interactions must be utilized to aid in functional elucidation. Here, we briefly discuss protein function prediction, prediction of protein–ligand interactions, the Critical Assessment of Techniques for Protein Structure Prediction (CASP) and the Continuous Automated EvaluatiOn (CAMEO) competitions, along with their role in shaping the field. We also discuss, in detail, our cutting-edge web-server method, FunFOLD for the structurally informed prediction of protein–ligand interactions. Furthermore, we provide a step-by-step guide on using the FunFOLD web server and FunFOLD3 downloadable application, along with some real world examples, where the FunFOLD methods have been used to aid functional elucidation.

Identification of a novel ligand binding motif in the transthyretin channel

The design of therapeutic compounds targeting transthyretin (TTR) is challenging due to the low specificity of interaction in the hormone binding site. Such feature is highlighted by the interactions of TTR with diclofenac, a compound with high affinity for TTR, in two dissimilar modes, as evidenced by crystal structure of the complex. We report here structural analysis of the interactions of TTR with two small molecules, 1-amino-5-naphthalene sulfonate (1,5-AmNS) and 1-anilino-8-naphthalene sulfonate (1,8-ANS). Crystal structure of TTR: 1,8-ANS complex reveals a peculiar interaction, through the stacking of the naphthalene ring between the side-chain of Lys15 and Leu17. The sulfonate moiety provides additional interaction with Lys15` and a water-mediated hydrogen bond with Thr119`. The uniqueness of this mode of ligand recognition is corroborated by the crystal structure of TTR in complex with the weak analogue 1,5-AmNS, the binding of which is driven mainly by hydrophobic partition and one electrostatic interaction between the sulfonate group and the Lys15. The ligand binding motif unraveled by 1,8-ANS may open new possibilities to treat TTR amyloid diseases by the elucidation of novel candidates for a more specific pharmacophoric pattern. (C) 2009 Published by Elsevier Ltd.

Only subtle protein conformational adaptations are required for ligand binding to thyroid hormone receptors: Simulations using a novel multipoint steered molecular dynamics approach

Thyroid hormone receptors (TR) are hormone-dependent transcription regulators that play a major role in human health, development, and metabolic functions. The thyroid hormone resistance syndrome, diabetes, obesity, and some types of cancer are just a few examples of important diseases that are related to TR malfunctioning, particularly impaired hormone binding. Ligand binding to and dissociation from the receptor ultimately control gene transcription and, thus, detailed knowledge of binding and release mechanisms are fundamental for the comprehension of the receptor`s biological function and development of pharmaceuticals. In this work, we present the first computational study of ligand entry into the ligand binding domain (LBD) of a nuclear receptor. We report molecular dynamics simulations of ligand binding to TRs using a generalization of the steered molecular dynamics technique designed to perform single-molecule pulling simulations along arbitrarily nonlinear driving pathways. We show that only gentle protein movements and conformational adaptations are required for ligand entry into the LBDs and that the magnitude of the forces applied to assist ligand binding are of the order of the forces involved in ligand dissociation. Our simulations suggest an alternative view for the mechanisms ligand binding and dissociation of ligands from nuclear receptors in which ligands can simply diffuse through the protein surface to reach proper positioning within the binding pocket. The proposed picture indicates that the large-amplitude protein motions suggested by the apo- and holo-RXR alpha crystallographic structures are not required, reconciling conformational changes of LBDs required for ligand entry with other nuclear receptors apo-structures that resemble the ligand-bound LBDs.

On the Denaturation Mechanisms of the Ligand Binding Domain of Thyroid Hormone Receptors

The ligand binding domain (LBD) of nuclear hormone receptors adopts a very compact, mostly alpha-helical structure that binds specific ligands with very high affinity. We use circular dichroism spectroscopy and high-temperature molecular dynamics Simulations to investigate unfolding of the LBDs of thyroid hormone receptors (TRs). A molecular description of the denaturation mechanisms is obtained by molecular dynamics Simulations of the TR alpha and TR beta LBDs in the absence and in the presence of the natural ligand Triac. The Simulations Show that the thermal unfolding of the LBD starts with the loss of native contacts and secondary Structure elements, while the Structure remains essentially compact, resembling a molten globule state. This differs From most protein denaturation simulations reported to date and suggests that the folding mechanism may start with the hydrophobic collapse of the TR LBDs. Our results reveal that the stabilities of the LBDs of the TR alpha and TR beta Subtypes are affected to different degrees by the binding of the isoform selective ligand Triac and that ligand binding confers protection against thermal denaturation and unfolding in a subtype specific manner. Our Simulations indicate two mechanisms by which the ligand stabilizes the LBD: (1) by enhancing the interactions between H8 and H 11, and the interaction of the region between H I and the Omega-loop with the core of the LBD, and (2) by shielding the hydrophobic H6 from hydration.

Conformational differences between the wild type and V30M mutant transthyretin modulate its binding to genistein: Implications to tetramer stability and ligand-binding

Transthyretin (TTR) is a tetrameric beta-sheet-rich transporter protein directly involved in human amyloid diseases. It was recently found that the isoflavone genistein (GEN) potently inhibits TTR amyloid fibril formation (Green et al., 2005) and is therefore a promising candidate for TTR amyloidosis treatment. Here we used structural and biophysical approaches to characterize genistein binding to the wild type (TTRwt) and to its most frequent amyloidogenic variant, the V30M mutant. In a dose-dependent manner, genistein elicited considerable increases in both mutant and TTRwt stability as demonstrated by high hydrostatic pressure (HHP) and acid-mediated dissociation/denaturation assays. TTR:GEN crystal complexes and isothermal titration calorimetry (ITC) experiments showed that the binding mechanisms of genistein to the TTRwt and to V30M are different and are dependent on apoTTR structure conformations. Furthermore, we could also identify potential allosteric movements caused by genistein binding to the wild type TTR that explains, at least in part, the frequently observed negatively cooperative process between the two sites of TTRwt when binding ligands. These findings show that TTR mutants may present different ligand recognition and therefore are of value in ligand design for inhibiting TTR amyloidosis. (C) 2010 Elsevier Inc. All rights reserved.

Whydration effects on DNA double helix stability modulates ligand binding to natural DNA in response to changes in water activity

In this work we present evidence that water molecules are actively involved on the control of binding affinity and binding site discrimination of a drug to natural DNA. In a previous study, the effect of water activity (a(w)) on the energetic parameters of actinomycin-D intercalation to natural DNA was determined using the osmotic stress method (39). This earlier study has shown evidence that water molecules act as an allosteric regulator of ligand binding to DNA via the effect of water activity on the long-range stability of the DNA secondary structure. In this work we have carried out DNA circularization experiments using the plasmid pUC18 in the absence of drugs and in the presence of different neutral solutes to evaluate the contribution of water activity to the energetics of DNA helix unwinding. The contribution of water to these independent reactions were made explicit by the description of how the changes in the free energy of ligand binding to DNA and in the free energy associated with DNA helix torsional deformation are linked to a(w) via changes in structural hydration. Taken together, the results of these studies reveal an extensive linkage between ligand binding affinity and site binding discrimination, and long range helix conformational changes and DNA hydration, This is strong evidence that water molecules work as a classical allosteric regulator of ligand binding to the DNA via its contribution to the stability of the double helix secondary structure, suggesting a possible mechanism by which the biochemical machinery of DNA processing takes advantage of the low activity of water into the cellular milieu.