Inverse agonist properties of atypical antipsychotic drugs

Mechanisms of action of several atypical antipsychotic drugs have been examined at the D-2 dopamine receptor expressed in CHO cells. The drugs tested were found to exhibit inverse agonist activity at the D-2 dopamine receptor based on their effects to potentiate forskolin-stimulated cyclic AMP (cAMP) accumulation. Each of the antipsychotic drugs tested (clozapine, olanzapine, quetiapine and risperidone) increased cAMP accumulation to the same extent. The increase in cAMP was also similar to that seen with typical antipsychotic drugs. Inverse agonism at the D-2 dopamine receptor seems, therefore, to be a property common to all classes of antipsychotic drugs. The effect of sodium ions on the binding of the drugs to the receptor was also assessed. Each of the atypical antipsychotic drugs tested here bound with higher affinity in the absence of sodium ions. Previous studies have shown that some antipsychotic drugs are insensitive to sodium ions and some bind with higher affinity in the presence of sodium ions. Given that all of these antipsychotic drugs are inverse agonists, it may be concluded that this sodium ion sensitivity is unrelated to mechanisms of inverse agonism. (C) 2004 Elsevier Inc. All rights reserved.

Investigation of the mechanism of agonist and inverse agonist action at D-2 dopamine receptors

This study investigated, for the D-2 dopamine receptor, the relation between the ability of agonists and inverse agonists to stabilise different states of the receptor and their relative efficacies. K-i values for agonists were determined in competition, versus the binding of the antagonist [H-3]spiperone. Competition data were fitted best by a two-binding site model (with the exception of bromocriptine, for which a one-binding site model provided the best fit) and agonist affinities for the higher (K-h) (G protein-coupled) and lower affinity (K-l) (G protein-uncoupled) sites determined. Ki values for agonists were also determined in competition versus the binding of the agonist [H-3]N-propylnorapomorphine (NPA) to provide a second estimate of K-h,. Maximal agonist effects (E-max) and their potencies (EC50) were determined from concentration-response curves for agonist stimulation of guanosine-5'-O-(3-[S-32] thiotriphosphate) ([S-35]GTPgammaS) binding. The ability of agonists to stabilise the G protein-coupled state of the receptor (K-l/K-h, determined from ligand-binding assays) did not correlate with either of two measures of relative efficacy (relative E-max, Kl/EC50) of agonists determined in [S-35]GTPgammaS-binding assays, when the data for all of the compounds tested were analysed For a subset of compounds, however, there was a relation between K-l/K-h and E-max.. Competition-binding data versus [H-3]spiperone and [H-3]NPA for a range of inverse agonists were fitted best by a one-binding site model. K-i values for the inverse agonists tested were slightly lower in competition versus [H-3]NPA compared to [H-3]spiperone. These data do not provide support for the idea that inverse agonists act by binding preferentially to the ground state of the receptor. (C) 2004 Elsevier Inc. All rights reserved.

Use of a novel Hill-climbing genetic algorithm in protein folding simulations

We have developed a novel Hill-climbing genetic algorithm (GA) for simulation of protein folding. The program (written in C) builds a set of Cartesian points to represent an unfolded polypeptide's backbone. The dihedral angles determining the chain's configuration are stored in an array of chromosome structures that is copied and then mutated. The fitness of the mutated chain's configuration is determined by its radius of gyration. A four-helix bundle was used to optimise simulation conditions, and the program was compared with other, larger, genetic algorithms on a variety of structures. The program ran 50% faster than other GA programs. Overall, tests on 100 non-redundant structures gave comparable results to other genetic algorithms, with the Hill-climbing program running from between 20 and 50% faster. Examples including crambin, cytochrome c, cytochrome B and hemerythrin gave good secondary structure fits with overall alpha carbon atom rms deviations of between 5 and 5.6 Angstrom with an optimised hydrophobic term in the fitness function. (C) 2003 Elsevier Ltd. All rights reserved.

Inverse agonism of the antipsychotic drugs at the D-2 dopamine receptor

The antipsychotic drugs had been assumed to act as antagonists at D-2 dopamine receptors but recently these drugs have been shown to possess inverse agonist properties at this receptor. Inverse agonism may be demonstrated from the ability of these drugs to potentiate forskolin-stimulated cAMP accumulation or to suppress agonist-independent [S-35]GTPgammaS binding. The antipsychotic drugs tested generally appear as full inverse agonists in these assays regardless of chemical or therapeutic class. The mechanism of inverse agonism of the antipsychotic drugs is still unclear but may involve stabilisation of the ground state of the D-2 receptor. (C) 2003 Elsevier Science B.V All rights reserved.

Chromatographic alignment of LC-MS and LC-MS/MS datasets by genetic algorithm feature extraction

Liquid chromatography-mass spectrometry (LC-MS) datasets can be compared or combined following chromatographic alignment. Here we describe a simple solution to the specific problem of aligning one LC-MS dataset and one LC-MS/MS dataset, acquired on separate instruments from an enzymatic digest of a protein mixture, using feature extraction and a genetic algorithm. First, the LC-MS dataset is searched within a few ppm of the calculated theoretical masses of peptides confidently identified by LC-MS/MS. A piecewise linear function is then fitted to these matched peptides using a genetic algorithm with a fitness function that is insensitive to incorrect matches but sufficiently flexible to adapt to the discrete shifts common when comparing LC datasets. We demonstrate the utility of this method by aligning ion trap LC-MS/MS data with accurate LC-MS data from an FTICR mass spectrometer and show how hybrid datasets can improve peptide and protein identification by combining the speed of the ion trap with the mass accuracy of the FTICR, similar to using a hybrid ion trap-FTICR instrument. We also show that the high resolving power of FTICR can improve precision and linear dynamic range in quantitative proteomics. The alignment software, msalign, is freely available as open source.

Quantitative pulsed phase thermography applied to steel plates

Pulsed Phase Thermography (PPT) has been proven effective on depth retrieval of flat-bottomed holes in different materials such as plastics and aluminum. In PPT, amplitude and phase delay signatures are available following data acquisition (carried out in a similar way as in classical Pulsed Thermography), by applying a transformation algorithm such as the Fourier Transform (FT) on thermal profiles. The authors have recently presented an extended review on PPT theory, including a new inversion technique for depth retrieval by correlating the depth with the blind frequency fb (frequency at which a defect produce enough phase contrast to be detected). An automatic defect depth retrieval algorithm had also been proposed, evidencing PPT capabilities as a practical inversion technique. In addition, the use of normalized parameters to account for defect size variation as well as depth retrieval from complex shape composites (GFRP and CFRP) are currently under investigation. In this paper, steel plates containing flat-bottomed holes at different depths (from 1 to 4.5 mm) are tested by quantitative PPT. Least squares regression results show excellent agreement between depth and the inverse square root blind frequency, which can be used for depth inversion. Experimental results on steel plates with simulated corrosion are presented as well. It is worth noting that results are improved by performing PPT on reconstructed (synthetic) rather than on raw thermal data.

Antipsychotic drug action: antagonism, inverse agonism or partial agonism

The positive, psychotic symptoms of schizophrenia can be treated by antipsychotic drugs and it has been assumed that these are antagonists at the D-2 and D-3 dopamine receptors in the brain. Recently, the D-2/D-3 partial agonist aripiprazole has been introduced as an antipsychotic drug. It has also been realized that, using in vitro assays, the other antipsychotic drugs are in fact inverse agonists at D-2/D-3 dopamine receptors. This raises questions about how these disparate drugs can achieve a similar clinical outcome. In this review, I shall consider the efficacies of these drugs in signalling assays and how these efficacies might affect treatment outcomes. It seems that the treatment outcome might depend on the overall level of cell stimulation, which is in turn dependent on the level of residual dopamine and the efficacy of the drug in signalling assays.

Mechanisms of inverse agonist action at D-2 dopamine receptors

1 Mechanisms of inverse agonist action at the D-2(short) dopamine receptor have been examined. 2 Discrimination of G-protein-coupled and -uncoupled forms of the receptor by inverse agonists was examined in competition ligand-binding studies versus the agonist [H-3]NPA at a concentration labelling both G-protein-coupled and -uncoupled receptors. 3 Competition of inverse agonists versus [H-3] NPA gave data that were fitted best by a two-binding site model in the absence of GTP but by a one-binding site model in the presence of GTP. K-i values were derived from the competition data for binding of the inverse agonists to G-protein-uncoupled and -coupled receptors. K-coupled and K-uncoupled were statistically different for the set of compounds tested ( ANOVA) but the individual values were different in a post hoc test only for (+)-butaclamol. 4 These observations were supported by simulations of these competition experiments according to the extended ternary complex model. 5 Inverse agonist efficacy of the ligands was assessed from their ability to reduce agonist-independent [S-35]GTPγ S binding to varying degrees in concentration-response curves. Inverse agonism by (+)-butaclamol and spiperone occurred at higher potency when GDP was added to assays, whereas the potency of (-)-sulpiride was unaffected. 6 These data show that some inverse agonists ((+)-butaclamol, spiperone) achieve inverse agonism by stabilising the uncoupled form of the receptor at the expense of the coupled form. For other compounds tested, we were unable to define the mechanism.

Inverse effectiveness, multisensory integration, and the bodily self: some statistical considerations

A recent report in Consciousness and Cognition provided evidence from a study of the rubber hand illusion (RHI) that supports the multisensory principle of inverse effectiveness (PoIE). I describe two methods of assessing the principle of inverse effectiveness ('a priori' and 'post-hoc'), and discuss how the post-hoc method is affected by the statistical artefact of,regression towards the mean'. I identify several cases where this artefact may have affected particular conclusions about the PoIE, and relate these to the historical origins of 'regression towards the mean'. Although the conclusions of the recent report may not have been grossly affected, some of the inferential statistics were almost certainly biased by the methods used. I conclude that, unless such artefacts are fully dealt with in the future, and unless the statistical methods for assessing the PoIE evolve, strong evidence in support of the PoIE will remain lacking. (C) 2009 Elsevier Inc. All rights reserved.

Inverse problems in dynamic cognitive modeling

Inverse problems for dynamical system models of cognitive processes comprise the determination of synaptic weight matrices or kernel functions for neural networks or neural/dynamic field models, respectively. We introduce dynamic cognitive modeling as a three tier top-down approach where cognitive processes are first described as algorithms that operate on complex symbolic data structures. Second, symbolic expressions and operations are represented by states and transformations in abstract vector spaces. Third, prescribed trajectories through representation space are implemented in neurodynamical systems. We discuss the Amari equation for a neural/dynamic field theory as a special case and show that the kernel construction problem is particularly ill-posed. We suggest a Tikhonov-Hebbian learning method as regularization technique and demonstrate its validity and robustness for basic examples of cognitive computations.

Variable step LMS algorithm using the accumulated instantaneous error concept

The convergence speed of the standard Least Mean Square adaptive array may be degraded in mobile communication environments. Different conventional variable step size LMS algorithms were proposed to enhance the convergence speed while maintaining low steady state error. In this paper, a new variable step LMS algorithm, using the accumulated instantaneous error concept is proposed. In the proposed algorithm, the accumulated instantaneous error is used to update the step size parameter of standard LMS is varied. Simulation results show that the proposed algorithm is simpler and yields better performance than conventional variable step LMS.

Finding the smallest eigenvalue by the inverse Monte Carlo method with refinement

Finding the smallest eigenvalue of a given square matrix A of order n is computationally very intensive problem. The most popular method for this problem is the Inverse Power Method which uses LU-decomposition and forward and backward solving of the factored system at every iteration step. An alternative to this method is the Resolvent Monte Carlo method which uses representation of the resolvent matrix [I -qA](-m) as a series and then performs Monte Carlo iterations (random walks) on the elements of the matrix. This leads to great savings in computations, but the method has many restrictions and a very slow convergence. In this paper we propose a method that includes fast Monte Carlo procedure for finding the inverse matrix, refinement procedure to improve approximation of the inverse if necessary, and Monte Carlo power iterations to compute the smallest eigenvalue. We provide not only theoretical estimations about accuracy and convergence but also results from numerical tests performed on a number of test matrices.