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PubMedDate not supplied

Ensemble methods for classification in cheminformatics.

We describe the application of ensemble methods to binary classification problems on two pharmaceutical compound data sets. Several variants of single and ensembles models of k-nearest neighbors classifiers, support vector machines (SVMs), and single ridge regression models are compared. All methods exhibit robust classification even when more features are given than observations. On two data sets dealing with specific properties of drug-like substances (cytochrome P450 inhibition and "Frequent Hitters", i.e., unspecific protein inhibition), we achieve classification rates above 90%. We are able to reduce the cross-validated misclassification rate for the Frequent Hitters problem by a factor of 2 compared to previous results obtained for the same data set with different modeling techniques.

Journal Article↗

PubMedDate not supplied

POEM: Parameter Optimization using Ensemble Methods: application to target specific scoring functions.

In computational biology processes such as docking, binding, and folding are often described by simplified, empirical models. These models are fitted to physical properties of the process by adjustable parameters. An appropriate choice of these parameters is crucial for the quality of the models. Locating the best choices for the parameters is often is a difficult task, depending on the complexity of the model. We describe a new method and program, POEM (Parameter Optimization using Ensemble Methods), for this task. In POEM we combine the DOE (Design Of Experiment) procedure with ensembles of different regression methods. We apply the method to the optimization of target specific scoring functions in molecular docking. The method consists of an iterative procedure that uses alternate evaluation and prediction steps. During each cycle of optimization we fit an approximate function to a defined loss function landscape and improve the quality of this fit from cycle to cycle by constantly augmenting our data set. As test applications we fitted the FlexX and Screenscore scoring functions to the kinase and ATPase protein classes. The results are promising: Starting from random parameters we are able to locate parameter sets which show superior performance compared to the original values. The POEM approach converges quickly and the approximated loss function landscapes are smooth, thus making the approach a suitable method for optimizations on rugged landscapes.

Adenosine Triphosphatases↗

PubMedDate not supplied

Modeling of cyclin-dependent kinase inhibition by 1H-pyrazolo[3,4-d]pyrimidine derivatives using artificial neural network ensembles.

Artificial neural network ensembles were used for modeling the cyclin-dependent kinase inhibition of 1H-pyrazolo[3,4-d]pyrimidine derivatives. The structural characteristics of these inhibitors were encoded in relevant 3D-spatial descriptors extracted by genetic algorithm feature selection. Bayesian-regularized multilayer neural networks, trained by the back-propagation algorithm, were developed using these variables as inputs. The predictive power of the model was tested by leave-one-out cross validation. In addition, for a more rigorous measure of the predictive capacity, multiple validation sets were randomly generated as members of neural network ensembles, which makes doing averaged predictions feasible. In this way, the predictive power was analyzed accounting for the averaged test set R values and test set mean-square errors. Otherwise, Kohonen self-organizing maps were used as an additional tool for the same modeling. The location of the inhibitors in a map facilitates the analysis of the connection between compounds and serves as a useful tool for qualitative predictions.

Algorithms↗

PubMedDate not supplied

Amino Acid Sequence Autocorrelation vectors and ensembles of Bayesian-Regularized Genetic Neural Networks for prediction of conformational stability of human lysozyme mutants.

Development of novel computational approaches for modeling protein properties from their primary structure is a main goal in applied proteomics. In this work, we reported the extension of the autocorrelation vector formalism to amino acid sequences for encoding protein structural information with modeling purposes. Amino Acid Sequence Autocorrelation (AASA) vectors were calculated by measuring the autocorrelations at sequence lags ranging from 1 to 15 on the protein primary structure of 48 amino acid/residue properties selected from the AAindex database. A total of 720 AASA descriptors were tested for building predictive models of the thermal unfolding Gibbs free energy change of human lysozyme mutants. In this sense, ensembles of Bayesian-Regularized Genetic Neural Networks (BRGNNs) were used for obtaining an optimum nonlinear model for the conformational stability. The ensemble predictor described about 88% and 68% variance of the data in training and test sets, respectively. Furthermore, the optimum AASA vector subset was shown not only to successfully model unfolding thermal stability but also to distribute wild-type and mutant lysozymes on a stability Self-organized Map (SOM) when used for unsupervised training of competitive neurons.

Algorithms↗

PubMed2005

Reconciling trajectory ensemble receptor model results with emissions.

Several approaches have been developed that use ensembles of air parcel back trajectories to identify likely source regions for contaminants observed at a downwind receptor site. Although the results of these models have appeared to provide results that agree with known sources, there have not been efforts to make direct comparisons between the results of such analyses with emissions inventories. In this paper, the results of residence time analysis (RTA) of data from Underhill, VT and from Brigantine, NJ are compared to the average estimated emissions of coal- and oil-fired power plants. Excellent correspondence was found between the areas of highest probability identified in the trajectory ensemble analyses and the averaged emission intensities.

Air Movements↗

PubMed2004

A heterobimetallic ruthenium(II)-copper(II) donor-acceptor complex as a chemodosimetric ensemble for selective cyanide detection.

A trinuclear heterobimetallic Ru(II)-Cu(II) donor-acceptor complex, [Ru(II)((t)Bubpy)(CN)(4)-[Cu(II)(dien)](2)](ClO(4))(2) ((t)Bubpy = 4,4'-di-tert-butyl-2,2'-bipyridine; dien = diethylenetriamine) (1), has been synthesized and successfully used as an chemodosimetric ensemble for the specific detection of cyanide in aqueous DMF. X-ray crystallography, solid and solution IR spectroscopy, and conductivity measurements reveal that complex 1 is a one-dimensional polymer in the crystalline state and dissociates into its [Ru(II)((t)Bubpy)(CN)(2)[(CN)Cu(II)(dien)L](2)](2+) (L = solvent) monomeric units in polar solvents. The MLCT transition and luminescence properties of the solvatochromic [Ru(II)((t)Bubpy)(CN)(4)](2)(-) donor are perturbed by the coordination of two Cu(II) acceptors but restored in the presence of CN(-). Spectroscopic and mass spectrometric studies confirm the cleavage of the cyano bridge between Ru(II) and Cu(II) of the chemodosimetric ensemble after the binding of cyanide to the Cu(II) centers. The overall binding constant, K(B), between 1 and CN(-) is measured to be (7.39 +/- 0.23) x 10(6) M(-2). A detection limit of 1.2 microM (0.03 ppm) of CN(-) in aqueous DMF (pH 7.4) is achievable. Thermodynamic evaluation shows that the analyte specificity of chemodosimeter 1 is attributable to the relative stability of the donor-acceptor complex to that of adducts formed between the acceptor metal center and the analytes.

Copper↗

PubMed2004

Ensemble approach for NMR structure refinement against (1)H paramagnetic relaxation enhancement data arising from a flexible paramagnetic group attached to a macromolecule.

Paramagnetic relaxation enhancement (PRE) measurements on (1)H nuclei have the potential to play an important role in NMR structure determination of macromolecules by providing unique long-range (10-35 A) distance information. Recent methodological advances for covalently attaching paramagnetic groups at specific sites on both proteins and nucleic acids have permitted the application of the PRE to various biological macromolecules. However, because artificially introduced paramagnetic groups are exposed to solvent and linked to the macromolecule by several freely rotatable bonds, they are intrinsically flexible. This renders conventional back-calculation of the (1)H-PRE using a single-point representation inaccurate, thereby severely limiting the utility of the (1)H-PRE as a tool for structure refinement. To circumvent these limitations, we have developed a theoretical framework and computational strategy with which to accurately back-calculate (1)H-PREs arising from flexible paramagnetic groups attached to macromolecules. In this scheme, the (1)H-PRE is calculated using a modified Solomon-Bloembergen equation incorporating a "model-free" formalism, based on a multiple-structure representation of the paramagnetic group in simulated annealing calculations. The ensemble approach for (1)H-PRE back-calculation was examined using several SRY/DNA complexes incorporating dT-EDTA-Mn(2+) at three distinct sites in the DNA, permitting a large data set comprising 435 experimental backbone and side-chain (1)H-PREs to be obtained in a straightforward manner from 2D through-bond correlation experiments. Calculations employing complete cross-validation demonstrate that the ensemble representation provides a means to accurately utilize backbone and side-chain (1)H-PRE data arising from a flexible paramagnetic group in structure refinement. The results of (1)H-PRE based refinement, in conjunction with previously obtained NMR restraints, indicate that significant gains in accuracy can be readily obtained. This is particularly significant in the case of macromolecular complexes where intermolecular translational restraints derived from nuclear Overhauser enhancement data may be limited.

Base Sequence↗

PubMed2005

Measuring pK(a) values in protein folding transition state ensembles by NMR spectroscopy.

Protein folding kinetic data have been obtained for the marginally stable N-terminal SH3 domain of the Drosophila protein drk as a function of pH in order to investigate the electrostatic properties of Asp8 in the folding transition state ensemble. The slow exchange between folded and unfolded forms of the protein gives rise to separate NMR resonances for both folded and unfolded states at equilibrium. As a result, kinetic data can be derived from magnetization transfer between these two states without the need for denaturants. Using the fact that ionization of Asp8 dominates the electrostatic behavior of the protein between pH 2 and 3, along with pKa values for titrating groups in both folded and unfolded states that have been determined in a previous study, values of 2.9 +/- 0.1 and 3.3 +/- 0.2 are obtained for the pKa of Asp8 in the transition state for the wild-type protein and for a His7Ala mutant, respectively. The data are consistent with the partial formation in the transition state ensemble of an Asp8 side chain carboxylate-a Lys21 backbone amide interaction that represents a highly conserved contact in folded SH3 domains.

Hydrogen-Ion Concentration↗

PubMed2006

Probing the transition state ensemble of a protein folding reaction by pressure-dependent NMR relaxation dispersion.

The F61A/A90G mutant of a redesigned form of apocytochrome b562 folds by an apparent two-state mechanism. We have used the pressure dependence of 15N NMR relaxation dispersion rate profiles to study the changes in volumetric parameters that accompany the folding reaction of this protein at 45 degrees C. The experiments were performed under conditions where the folding/unfolding equilibrium could be studied at each pressure without addition of denaturants. The exquisite sensitivity of the methodology to small changes in folding/unfolding rates facilitated the use of relatively low-pressure values (between 1 and 270 bar) so that pressure-induced changes to the unfolded state ensemble could be minimized. A volume change for unfolding of -81 mL/mol is measured (at 1 bar), a factor of 1.4 larger (in absolute value) than the volume difference between the transition state ensemble (TSE) and the unfolded state. Notably, the changes in the free energy difference between folded and unfolded states and in the activation free energy for folding were not linear with pressure. Thus, the difference in the isothermal compressibility upon unfolding (-0.11 mL mol(-1) bar(-1)) and, for the first time, the compressibility of the TSE relative to the unfolded state (0.15 mL mol(-1) bar(-1)) could be calculated. The results argue for a TSE that is collapsed but loosely packed relative to the folded state and significantly hydrated, suggesting that the release of water occurs after the rate-limiting step in protein folding. The notion of a collapsed and hydrated TSE is consistent with expectations based on earlier temperature-dependent folding studies, showing that the barrier to folding at 45 degrees C is entropic (Choy, W. Y.; Zhou, Z.; Bai, Y.; Kay, L. E. J. Am. Chem. Soc. 2005, 127, 5066-5072).

Cytochromes b↗

PubMed2006

Simulated unfolded-state ensemble and the experimental NMR structures of villin headpiece yield similar wide-angle solution X-ray scattering profiles.

With the advent of powerful synchrotron sources, solution X-ray scattering is being increasingly used to get basic information about the structure of polypeptides. The solution scattering technique essentially provides one-dimensional data, which are then interpreted in terms of a three-dimensional structure through model building. Here we calculate wide-angle solution scattering patterns for an ensemble of simulated unfolded structures of villin headpiece, which differ from the native structure by rmsd = 8.8 +/- 1.0 A and have only negligible amounts of native secondary structure. We show that the wide-angle solution scattering pattern of such an ensemble shares significant similarity with the one based on the experimental NMR structures of the molecule. Our results suggest that solution scattering in the wide-angle limit, by itself, provides very little information about the secondary structure content of a polypeptide or its side-chain packing.

Computer Simulation↗

PubMed1986

The ensemble approach to distance geometry: application to the nicotinic pharmacophore.

We develop an extension of conventional distance geometry techniques that treats two or more molecules as a single "ensemble". This extension can be used to find a common pharmacophore, i.e., the spatial arrangement of essential groups, from a small set of biologically active molecules. The approach can generate, in one step, coordinates for the set of molecules in their "active" conformations such that their essential groups are superimposed. As an example, we show how the nicotinic pharmacophore can be deduced from a set of four nicotinic agonists: nicotine, cytisine, ferruginine methiodide, and muscarone. Three essential groups in each agonist are chosen: the cationic center (A), an electronegative atom (B), and an atom (C) that forms a dipole with B. There is only one pharmacophore possible for the superposition of these essential groups: a triangle with sides 4.8 A (A-B), 4.0 A (A-C), and 1.2 A (B-C). The pharmacophore triangle, which is consistent with previous models in the literature, can also be achieved by the agonist trans-3,3'-bis[(trimethylammonio)methyl]azobenzene and the antagonists strychnine, trimethaphan, and dihydro-beta-erythroidine. An examination of the common volumes of agonists suggests a specific disposition of molecular volume relative to the pharmacophore triangle. We discuss the relative strengths and drawbacks of the ensemble approach vs. other conformational search methods.

Alkaloids↗

PubMed2005

Electrooxidation of carbon monoxide on gold nanoparticle ensemble electrodes: effects of particle coverage.

Gold nanoparticles were attached to amine-functionalized indium tin oxide substrate to form particle ensemble electrodes with controlled particle coverage. Electrooxidation of carbon monoxide (CO) on these particle ensemble electrodes was studied in CO-saturated alkaline solutions by means of cyclic voltammetry, with an emphasis on the effects of particle coverage. CO oxidation half-wave potential was found to decrease with increasing particle density. However, the current density was significantly larger at lower particle coverage electrodes. On the basis of a model for electron transfer on a partially covered electrode, the observations were explained in terms of the change in reactant mass transport pattern with varying particle coverages: CO diffusion is predominantly mixed spherical and linear at low particle coverages and changes to mostly linear at high particle coverages. The possibility of contributions from particle agglomeration is also briefly discussed.

Carbon Monoxide↗

PubMed2006

Ensemble and single-molecule fluorescence spectroscopy of a calcium-ion indicator dye.

The spectroscopic properties of Calcium Green 2 (CG-2), a dual-fluorophore Ca(2+) indicator dye, were characterized by a combination of steady state and time-resolved ensemble spectroscopic measurements, molecular mechanics calculations and single-molecule fluorescence spectroscopy. It was found that in Ca(2+) free solutions, CG-2 exists primarily as a highly quenched intramolecular dimer, but when bound to Ca(2+), the molecule adopts an extended, fluorescent conformation. The difference in emission properties of these two CG-2 conformations is explained in terms of simple exciton theory. Through single-molecule fluorescence measurements, we have shown that the bulk increase in ensemble fluorescence intensity correlates with a simple statistical increase in the number of fluorescent molecules in solution. In addition, we have also observed that the majority of CG-2 molecules photobleach in a single step, despite the molecule possessing two distinct fluorophores. A small fraction of molecules photobleach in multiple steps or show a series of transitions between emissive and nonemissive fluorescent states ("blinking"). We rationalize these photophysical phenomena using a simple model based on dipole-dipole Förster coupling between fluorophores in conjunction with irreversible photodamage to one of the constituent chromophores.

Algorithms↗

PubMed2006

Shape-selective fluorescent sensing ensemble using a tweezer-type metalloreceptor.

[reaction: see text] A fluorescent sensing ensemble for pyridine-derived compounds is described. The receptor portion of the ensemble is prepared from a bisimidazole pyridine which coordinates copper to form a well-defined cavity. Small heteroaromatic guests such as adenine bind strongly in the cavity. The fluorescent response is provided by a dye which is coordinated to the receptor and quenched by the metal ion. The dye is released upon guest binding providing up to 25-fold fluorescence increases.

Crystallography, X-Ray↗

PubMed1988

Relation between individual and ensemble release kinetics of indomethacin from microspheres.

Indomethacin microspheres based on a combination of ethylcellulose and polyethyleneglycol were prepared using the solvent evaporation process. Release profiles of ensemble and individual microspheres were measured. Both were found to follow first-order kinetics, in contrast to what was expected. This was attributed to the fact that all the particles showed the same kinetic pattern and had a greater degree of homogeneity in the payload, mean particle size and shape, and k1 values than in ensembles of microcapsules.

Indomethacin↗

PubMed2003

Interval timing and the encoding of signal duration by ensembles of cortical and striatal neurons.

This study investigated the firing patterns of striatal and cortical neurons in rats in a temporal generalization task. Striatal and cortical ensembles were recorded in rats trained to lever press at 2 possible criterion durations (10 s or 40 s from tone onset). Twenty-two percent of striatal and 15% of cortical cells had temporally specific modulations in their firing rate, firing at a significantly different rate around 10 s compared with 40 s. On 80% of trials, a post hoc analysis of the trial-by-trial consistency of the firing rates of an ensemble of neurons predicted whether a spike train came from a time window around 10 s versus around 40 s. Results suggest that striatal and cortical neurons encode specific durations in their firing rate and thereby serve as components of a neural circuit used to represent duration.

Animals↗

PubMed1999

Environment-specific expression of the immediate-early gene Arc in hippocampal neuronal ensembles.

We used fluorescent in-situ hybridization and confocal microscopy to monitor the subcellular distribution of the immediate-early gene Arc. Arc RNA appeared in discrete intranuclear foci within minutes of neuronal activation and subsequently disappeared from the nucleus and accumulated in the cytoplasm by 30 minutes. The time course of nuclear versus cytoplasmic Arc RNA accumulation was distinct, and could therefore be used to infer the activity history of individual neurons at two times. Following sequential exposure of rats to two different environments or to the same environment twice, the proportion of CA1 neurons with cytoplasmic, nuclear or overlapping Arc expression profiles matched predictions derived from ensemble neurophysiological recordings of hippocampal neuronal ensembles. Arc gene induction is thus specifically linked to neural encoding processes.

Animals↗

PubMed2004

Quantification of modelling uncertainties in a large ensemble of climate change simulations.

Comprehensive global climate models are the only tools that account for the complex set of processes which will determine future climate change at both a global and regional level. Planners are typically faced with a wide range of predicted changes from different models of unknown relative quality, owing to large but unquantified uncertainties in the modelling process. Here we report a systematic attempt to determine the range of climate changes consistent with these uncertainties, based on a 53-member ensemble of model versions constructed by varying model parameters. We estimate a probability density function for the sensitivity of climate to a doubling of atmospheric carbon dioxide levels, and obtain a 5-95 per cent probability range of 2.4-5.4 degrees C. Our probability density function is constrained by objective estimates of the relative reliability of different model versions, the choice of model parameters that are varied and their uncertainty ranges, specified on the basis of expert advice. Our ensemble produces a range of regional changes much wider than indicated by traditional methods based on scaling the response patterns of an individual simulation.

Journal Article↗