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.

Molecular modelling studies of binding of DACD derivatives into G-Quadruplex DNA: comparison of force field and quantum polarized ligand docking methods

The DNA G-qadruplexes are one of the targets being actively explored for anti-cancer therapy by inhibiting them through small molecules. This computational study was conducted to predict the binding strengths and orientations of a set of novel dimethyl-amino-ethyl-acridine (DACA) analogues that are designed and synthesized in our laboratory, but did not diffract in Synchrotron light.Thecrystal structure of DNA G-Quadruplex(TGGGGT)4(PDB: 1O0K) was used as target for their binding properties in our studies.We used both the force field (FF) and QM/MM derived atomic charge schemes simultaneously for comparing the predictions of drug binding modes and their energetics. This study evaluates the comparative performance of fixed point charge based Glide XP docking and the quantum polarized ligand docking schemes. These results will provide insights on the effects of including or ignoring the drug-receptor interfacial polarization events in molecular docking simulations, which in turn, will aid the rational selection of computational methods at different levels of theory in future drug design programs. Plenty of molecular modelling tools and methods currently exist for modelling drug-receptor or protein-protein, or DNA-protein interactionssat different levels of complexities.Yet, the capasity of such tools to describevarious physico-chemical propertiesmore accuratelyis the next step ahead in currentresearch.Especially, the usage of most accurate methods in quantum mechanics(QM) is severely restricted by theirtedious nature. Though the usage of massively parallel super computing environments resulted in a tremendous improvement in molecular mechanics (MM) calculations like molecular dynamics,they are still capable of dealing with only a couple of tens to hundreds of atoms for QM methods. One such efficient strategy that utilizes thepowers of both MM and QM are the QM/MM hybrid methods. Lately, attempts have been directed towards the goal of deploying several different QM methods for betterment of force field based simulations, but with practical restrictions in place. One of such methods utilizes the inclusion of charge polarization events at the drug-receptor interface, that is not explicitly present in the MM FF.

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.

Corticotropin-releasing factor binding protein dimerizes after association with ligand.

We have suggested recently that the fall in plasma CRF-binding protein (BP) during the last few weeks of pregnancy is a direct effect of association with its ligand because of the rapid decrease in plasma BP concentration seen in normal males reaching a nadir some 15 min after a bolus injection of synthetic CRF. In the present study, we have investigated the physicochemical properties of both natural and recombinant BP by gel filtration under physiological conditions and have shown that association of human CRF to this BP results in an increase in molecular weight consistent with the formation of a dimer form of the BP ligand complex. The dimer is more stable when the interaction occurs in the presence of serum or if a peptide with a higher affinity for the BP is substituted as ligand. Experimental evidence would also suggest that the dimer BP has a higher affinity for ligand than the monomeric form. We suggest that this dimerization occurs in vivo when CRF is released into the bloodstream and provides the trigger that causes the uptake of the complex at specific receptor sites.

A role for adhesion and degranulation-promoting adapter protein in collagen-induced platelet activation mediated via integrin α(2) β(1)

Platelet aggregation and phosphorylation of phospholipase Cγ2 induced by collagen were attenuated in ADAP(-/-) platelets. However, aggregation and signaling induced by collagen-related peptide (CRP), a GPVI-selective agonist, were largely unaffected. Platelet adhesion to CRP was also unaffected by ADAP deficiency. Adhesion to the α(2) β(1) -selective ligand GFOGER and to a peptide (III-04), which supports adhesion that is dependent on both GPVI and α(2) β(1), was reduced in ADAP(-/-) platelets. An impedance-based label-free detection technique, which measures adhesion and spreading of platelets, indicated that, in the absence of ADAP, spreading on GFOGER was also reduced. This was confirmed with non-fluorescent differential-interference contrast microscopy, which revealed reduced filpodia formation in ADAP(-/-) platelets adherent to GFOGER. This indicates that ADAP plays a role in mediating platelet activation via the collagen-binding integrin α(2) β(1). In addition, we found that ADAP(-/-) mice, which are mildly thrombocytopenic, have enlarged spleens as compared with wild-type animals. This may reflect increased removal of platelets from the circulation.

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.

The binding site distance test score: a robust method for the assessment of predicted protein binding sites

We propose a novel method for scoring the accuracy of protein binding site predictions – the Binding-site Distance Test (BDT) score. Recently, the Matthews Correlation Coefficient (MCC) has been used to evaluate binding site predictions, both by developers of new methods and by the assessors for the community wide prediction experiment – CASP8. Whilst being a rigorous scoring method, the MCC does not take into account the actual 3D location of the predicted residues from the observed binding site. Thus, an incorrectly predicted site that is nevertheless close to the observed binding site will obtain an identical score to the same number of nonbinding residues predicted at random. The MCC is somewhat affected by the subjectivity of determining observed binding residues and the ambiguity of choosing distance cutoffs. By contrast the BDT method produces continuous scores ranging between 0 and 1, relating to the distance between the predicted and observed residues. Residues predicted close to the binding site will score higher than those more distant, providing a better reflection of the true accuracy of predictions. The CASP8 function predictions were evaluated using both the MCC and BDT methods and the scores were compared. The BDT was found to strongly correlate with the MCC scores whilst also being less susceptible to the subjectivity of defining binding residues. We therefore suggest that this new simple score is a potentially more robust method for future evaluations of protein-ligand binding site predictions.

Combinatorial peptide ligand libraries and plant proteomics: a winning strategy at a price

The mechanism of action and properties of a solid-phase ligand library made of hexapeptides (combinatorial peptide ligand libraries or CPLL), for capturing the "hidden proteome", i.e. the low- and very low-abundance proteins constituting the vast majority of species in any proteome, as applied to plant tissues, are reviewed here. Plant tissues are notoriously recalcitrant to protein extraction and to proteome analysis. Firstly, rigid plant cell walls need to be mechanically disrupted to release the cell content and, in addition to their poor protein yield, plant tissues are rich in proteases and oxidative enzymes, contain phenolic compounds, starches, oils, pigments and secondary metabolites that massively contaminate protein extracts. In addition, complex matrices of polysaccharides, including large amount of anionic pectins, are present. All these species compete with the binding of proteins to the CPLL beads, impeding proper capture and identification / detection of low-abundance species. When properly pre-treated, plant tissue extracts are amenable to capture by the CPLL beads revealing thus many new species among them low-abundance proteins. Examples are given on the treatment of leaf proteins, of corn seed extracts and of exudate proteins (latex from Hevea brasiliensis). In all cases, the detection of unique gene products via CPLL capture is at least twice that of control, untreated sample.