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PubMed2005

Determination of an ensemble of structures representing the intermediate state of the bacterial immunity protein Im7.

We present a detailed structural characterization of the intermediate state populated during the folding and unfolding of the bacterial immunity protein Im7. We achieve this result by incorporating a variety of experimental data available for this species in molecular dynamics simulations. First, we define the structure of the exchange-competent intermediate state of Im7 by using equilibrium hydrogen-exchange protection factors. Second, we use this ensemble to predict Phi-values and compare the results with the experimentally determined Phi-values of the kinetic refolding intermediate. Third, we predict chemical-shift measurements and compare them with the measured chemical shifts of a mutational variant of Im7 for which the kinetic folding intermediate is the most stable state populated at equilibrium. Remarkably, we found that the properties of the latter two species are predicted with high accuracy from the exchange-competent intermediate that we determined, suggesting that these three states are characterized by a similar architecture in which helices I, II, and IV are aligned in a native-like, but reorganized, manner. Furthermore, the structural ensemble that we obtained enabled us to rationalize the results of tryptophan fluorescence experiments in the WT protein and a series of mutational variants. The results show that the integration of diverse sets of experimental data at relatively low structural resolution is a powerful approach that can provide insights into the structural organization of this conformationally heterogeneous three-helix intermediate with unprecedented detail and highlight the importance of both native and non-native interactions in stabilizing its structure.

Biophysical Phenomena↗

PubMed2006

Understanding ensemble protein folding at atomic detail.

It has long been known that a protein's amino acid sequence dictates its native structure. However, despite significant recent advances, an ensemble description of how a protein achieves its native conformation from random coil under physiologically relevant conditions remains incomplete. Here we present a detailed all-atom model with a transferable potential that is capable of ab initio folding of entire protein domains using only sequence information. The computational efficiency of this model allows us to perform thousands of microsecond-time scale-folding simulations of the engrailed homeodomain and to observe thousands of complete independent folding events. We apply a graph-theoretic analysis to this massive data set to elucidate which intermediates and intermediary states are common to many trajectories and thus important for the folding process. This method provides an atomically detailed and complete picture of a folding pathway at the ensemble level. The approach that we describe is quite general and could be used to study the folding of proteins on time scales orders of magnitude longer than currently possible.

Algorithms↗

PubMed2002

The ensemble folding kinetics of protein G from an all-atom Monte Carlo simulation.

Protein G is folded with an all-atom Monte Carlo simulation by using a Gō potential. When folding is monitored by using burial of the lone tryptophan in protein G as the reaction coordinate, the ensemble kinetics is single exponential. Other experimental observations, such as the burst phase and mutational data, are also reproduced. However, more detailed analysis reveals that folding occurs over three distinct, three-state pathways. We show that, because of this tryptophan's asymmetric location in the tertiary fold, its burial (i) does not detect certain intermediates and (ii) may not correspond to the folding event. This finding demonstrates that ensemble averaging can disguise the presence of multiple pathways and intermediates when a non-ideal reaction coordinate is used. Finally, all observed folding pathways eventually converge to a common rate-limiting step, which is the formation of a specific nucleus involving hydrophobic core residues. These residues are conserved in the ubiquitin superfamily and in a phage display experiment, suggesting that fold topology is a strong determinant of the transition state.

Binding Sites↗

PubMed2000

Binding sites in Escherichia coli dihydrofolate reductase communicate by modulating the conformational ensemble.

To explore how distal mutations affect binding sites and how binding sites in proteins communicate, an ensemble-based model of the native state was used to define the energetic connectivities between the different structural elements of Escherichia coli dihydrofolate reductase. Analysis of this model protein has allowed us to identify two important aspects of intramolecular communication. First, within a protein, pair-wise couplings exist that define the magnitude and extent to which mutational effects propagate from the point of origin. These pair-wise couplings can be identified from a quantity we define as the residue-specific connectivity. Second, in addition to the pair-wise energetic coupling between residues, there exists functional connectivity, which identifies energetic coupling between entire functional elements (i.e., binding sites) and the rest of the protein. Analysis of the energetic couplings provides access to the thermodynamic domain structure in dihydrofolate reductase as well as the susceptibility of the different regions of the protein to both small-scale (e.g., point mutations) and large-scale perturbations (e. g., binding ligand). The results point toward a view of allosterism and signal transduction wherein perturbations do not necessarily propagate through structure via a series of conformational distortions that extend from one active site to another. Instead, the observed behavior is a manifestation of the distribution of states in the ensemble and how the distribution is affected by the perturbation.

Binding Sites↗

PubMed2002

An ensemble method for identifying regulatory circuits with special reference to the qa gene cluster of Neurospora crassa.

A chemical reaction network for the regulation of the quinic acid (qa) gene cluster of Neurospora crassa is proposed. An efficient Monte Carlo method for walking through the parameter space of possible chemical reaction networks is developed to identify an ensemble of deterministic kinetics models with rate constants consistent with RNA and protein profiling data. This method was successful in identifying a model ensemble fitting available RNA profiling data on the qa gene cluster.

Genes, Fungal↗

PubMed2000

Landscape approaches for determining the ensemble of folding transition states: success and failure hinge on the degree of frustration.

We present a method for determining structural properties of the ensemble of folding transition states from protein simulations. This method relies on thermodynamic quantities (free energies as a function of global reaction coordinates, such as the percentage of native contacts) and not on "kinetic" measurements (rates, transmission coefficients, complete trajectories); consequently, it requires fewer computational resources compared with other approaches, making it more suited to large and complex models. We explain the theoretical framework that underlies this method and use it to clarify the connection between the experimentally determined Phi value, a quantity determined by the ratio of rate and stability changes due to point mutations, and the average structure of the transition state ensemble. To determine the accuracy of this thermodynamic approach, we apply it to minimalist protein models and compare these results with the ones obtained by using the standard experimental procedure for determining Phi values. We show that the accuracy of both methods depends sensitively on the amount of frustration. In particular, the results are similar when applied to models with minimal amounts of frustration, characteristic of rapid-folding, single-domain globular proteins.

Kinetics↗

PubMed2000

Forecasting summertime surface-level ozone concentrations in the Lower Fraser Valley of British Columbia: an ensemble neural network approach.

Empirical models for predicting daily maximum hourly average ozone concentrations were developed for 10 monitoring stations in the Lower Fraser Valley (LFV) of British Columbia. According to data from 1991 to 1996, ensemble neural network models increased explained variance an average of 7% over multiple linear regression models using the same input variables. Without modification, all models performed poorly on days when the observed peak ozone concentration exceeded 82 parts per billion, the National Ambient Air Quality Objective. When numbers of extreme events in training data were increased using a histogram equalization process, models were able to forecast exceedances with improved accuracy. Modified generalized additive model (GAM) plots and associated measures of input variable importance and interaction were generated for a subset of the trained models and used to investigate relationships between input variables and ozone levels. The neural network models displayed a high degree of interaction among inputs, and it is likely the ability of these model types to account for interactions, rather than the nonlinearity of individual input variables, that explains their improved forecast skill. Inspection of GAM-style plots indicated that the relative importance of input variables in the ensemble neural network models varied with geographic location within the LFV. Four distinct groups of stations were identified, and rankings of inputs within the groups were generally consistent with physical intuition and results of prior studies.

Algorithms↗

PubMed2005

Classification ensembles for unbalanced class sizes in predictive toxicology.

This paper investigates the effects of the ratio of positive-to-negative samples on the sensitivity, specificity, and concordance. When the class sizes in the training samples are not equal, the classification rule derived will favor the majority class and result in a low sensitivity on the minority class prediction. We propose an ensemble classification approach to adjust for differential class sizes in a binary classifier system. An ensemble classifier consists of a set of base classifiers; its prediction rule is based on a summary measure of individual classifications by the base classifiers. Two re-sampling methods, augmentation and abatement, are proposed to generate different bootstrap samples of equal class size to build the base classifiers. The augmentation method balances the two class sizes by bootstrapping additional samples from the minority class, whereas the abatement method balances the two class sizes by sampling only a subset of samples from the majority class. The proposed procedure is applied to a data set to predict estrogen receptor binding activity and to a data set to predict animal liver carcinogenicity using SAR (structure-activity relationship) models as base classifiers. The abatement method appears to perform well in balancing sensitivity and specificity.

Discriminant Analysis↗

PubMed1993

Physiological evaluation of liquid-barrier, vapor-permeable protective clothing ensembles for work in hot environments.

Work clothes using fabrics with vapor-transmitting characteristics are in limited use in various industrial applications, and there is a growing interest in their purported ability to help reduce heat stress. This study was performed to compare two vapor-transmitting ensembles with other clothing ensembles previously tested. The evaluation was based on an established experimental protocol that determines the critical values of air temperature and water-vapor pressure so that an individual maintains thermal balance, while controlling other factors that contribute to worker heat stress (e.g., air motion and metabolism). There were no differences between the two vapor-transmitting garments in their effects on worker heat stress. When compared to the results of other studies, the two vapor-transmitting garments had critical environmental characteristics similar to two layers of cotton coveralls and they performed better from a heat stress standpoint than a disposable vapor-barrier suit worn over cloth coveralls.

Adult↗

PubMed2005

Respiratory demand during rigorous physical work in a chemical protective ensemble.

Protection afforded by a respirator filter depends on many factors, among them chemical or biological agent and flow rate. Filtration mechanisms, such as chemical adsorption, depend on sufficient residence time for the filter media to extract noxious agents from the airstream. Consequently, filter efficiency depends on inspiratory air velocities, among other factors. Filter designs account for this by adjusting bed depth and cross-sectional area to anticipated flow rates. Many military and commercial filters are designed and tested at 32-40 L/min. The present study investigated respiratory demand while U.S. Marines (n=32) completed operationally relevant tasks in chemical protective ensembles, including M-40 masks and C2A1 filters. Respiratory demand greatly exceeded current test conditions during the most arduous tasks: minute ventilation=96.4+/-18.9 L/min (mean+/-SD) with a maximum of 131.7 L/min observed in one subject. Mean peak inspiratory flow rate (PIF) reached 238.7+/-34.0 L/min with maximum PIF often exceeding 300 L/min (maximum observed value=356.3 L/min). The observed respiratory demand was consistent with data reported in previous laboratory studies of very heavy workloads. This study is among the few to report on respiratory demand while subjects perform operationally relevant tasking in chemical protective ensembles. The results indicate that military and industrial filters will probably encounter higher flow rates than previously anticipated during heavy exertion.

Adult↗

PubMed2005

Differential localization of ErbB receptor ensembles influences their signaling in hippocampal neurons.

Our studies indicate that ErbB complexes participate in both survival and synaptic plasticity signals of hippocampal neurons but in a manner that depends on the subcellular localization of the receptor ensembles. Using dissociated hippocampal cultures, we found that neurons, rather than glial cells, are the primary targets of ErbB receptor ligands such as epidermal growth factor and heregulin. Further investigation demonstrated that ErbB receptors distribute differentially in hippocampal neurons with the epidermal growth factor receptor confined to neural cell bodies and the p185(c-neu) and ErbB4 receptors distributed to both neural soma and neurites. Activation of ErbB receptor and downstream signaling molecules were observed in neurites only after heregulin stimulation. The receptor complex which mediated neurite located signals was the p185(c-neu)/ErbB4 heterodimer. Colocalization of p185(c-neu), but not epidermal growth factor receptor, with postsynaptic density protein 95 suggests that the heregulin signaling contributes to synapse specific activities. However, the epidermal growth factor receptor complex mediates physiological survival signals, as neuronal survival was enhanced by epidermal growth factor, rather than heregulin. Collectively, these studies indicate that different ErbB ensembles localize to different locations on the neuron to mediate distinct signals and functions.

Animals↗

PubMed2025

Structural basis of differential gene expression at eQTLs loci from high-resolution ensemble models of 3D single-cell chromatin conformations.

MOTIVATION: Techniques such as high-throughput chromosome conformation capture (Hi-C) have provided a wealth of information on nucleus organization and genome important for understanding gene expression regulation. Genome-Wide Association Studies have identified numerous loci associated with complex traits. Expression quantitative trait loci (eQTL) studies have further linked the genetic variants to alteration in expression levels of associated target genes across individuals. However, the functional roles of many eQTLs in noncoding regions remain unclear. Current joint analyses of Hi-C and eQTLs data lack advanced computational tools, limiting what can be learned from these data. RESULTS: We developed a computational method for simultaneous analysis of Hi-C and eQTL data, capable of identifying a small set of nonrandom interactions from all Hi-C interactions. Using these nonrandom interactions, we reconstructed large ensembles (×105) of high-resolution single-cell 3D chromatin conformations with thorough sampling, accurately replicating Hi-C measurements. Our results revealed many-body interactions in chromatin conformation at the single-cell level within eQTL loci, providing a detailed view of how 3D chromatin structures form the physical foundation for gene regulation, including how genetic variants of eQTLs affect the expression of associated eGenes. Furthermore, our method can deconvolve chromatin heterogeneity and investigate the spatial associations of eQTLs and eGenes at subpopulation level, revealing their regulatory impacts on gene expression. Together, ensemble modeling of thoroughly sampled single-cell chromatin conformations combined with eQTL data, helps decipher how 3D chromatin structures provide the physical basis for gene regulation, expression control, and aid in understanding the overall structure-function relationships of genome organization. AVAILABILITY AND IMPLEMENTATION: It is available at https://github.com/uic-liang-lab/3DChromFolding-eQTL-Loci.

Quantitative Trait Loci↗

PubMed2006

Ensembl 2006.

The Ensembl (http://www.ensembl.org/) project provides a comprehensive and integrated source of annotation of large genome sequences. Over the last year the number of genomes available from the Ensembl site has increased from 4 to 19, with the addition of the mammalian genomes of Rhesus macaque and Opossum, the chordate genome of Ciona intestinalis and the import and integration of the yeast genome. The year has also seen extensive improvements to both data analysis and presentation, with the introduction of a redesigned website, the addition of RNA gene and regulatory annotation and substantial improvements to the integration of human genome variation data.

Animals↗

PubMed2006

Homology modeling using parametric alignment ensemble generation with consensus and energy-based model selection.

The accuracy of a homology model based on the structure of a distant relative or other topologically equivalent protein is primarily limited by the quality of the alignment. Here we describe a systematic approach for sequence-to-structure alignment, called 'K*Sync', in which alignments are generated by dynamic programming using a scoring function that combines information on many protein features, including a novel measure of how obligate a sequence region is to the protein fold. By systematically varying the weights on the different features that contribute to the alignment score, we generate very large ensembles of diverse alignments, each optimal under a particular constellation of weights. We investigate a variety of approaches to select the best models from the ensemble, including consensus of the alignments, a hydrophobic burial measure, low- and high-resolution energy functions, and combinations of these evaluation methods. The effect on model quality and selection resulting from loop modeling and backbone optimization is also studied. The performance of the method on a benchmark set is reported and shows the approach to be effective at both generating and selecting accurate alignments. The method serves as the foundation of the homology modeling module in the Robetta server.

Amino Acid Sequence↗

PubMed2006

Ensembl 2007.

The Ensembl (http://www.ensembl.org/) project provides a comprehensive and integrated source of annotation of chordate genome sequences. Over the past year the number of genomes available from Ensembl has increased from 15 to 33, with the addition of sites for the mammalian genomes of elephant, rabbit, armadillo, tenrec, platypus, pig, cat, bush baby, common shrew, microbat and european hedgehog; the fish genomes of stickleback and medaka and the second example of the genomes of the sea squirt (Ciona savignyi) and the mosquito (Aedes aegypti). Some of the major features added during the year include the first complete gene sets for genomes with low-sequence coverage, the introduction of new strain variation data and the introduction of new orthology/paralog annotations based on gene trees.

Animals↗

PubMed2004

Can the confidence in long range atmospheric transport models be increased? The pan-european experience of ensemble.

Is atmospheric dispersion forecasting an important asset of the early-phase nuclear emergency response management? Is there a 'perfect atmospheric dispersion model'? Is there a way to make the results of dispersion models more reliable and trustworthy? While seeking to answer these questions the multi-model ensemble dispersion forecast system ENSEMBLE will be presented.

Air Movements↗

PubMed2006

Elucidating the digital control mechanism for DNA damage repair with the p53-Mdm2 system: single cell data analysis and ensemble modelling.

Recent experimental evidence about DNA damage response using the p53-Mdm2 system has raised some fundamental questions about the control mechanism employed. In response to DNA damage, an ensemble of cells shows a damped oscillation in p53 expression whose amplitude increases with increased DNA damage--consistent with 'analogue' control. Recent experimental results, however, show that the single cell response is a series of discrete pulses in p53; and with increase in DNA damage, neither the height nor the duration of the pulses change, but the mean number of pulses increase--consistent with 'digital' control. Here we present a system engineering model that uses published data to elucidate this mechanism and resolve the dilemma of how digital behaviour at the single cell level can manifest as analogue ensemble behaviour. First, we develop a dynamic model of the p53-Mdm2 system that produces non-oscillatory responses to a stress signal. Second, we develop a probability model of the distribution of pulses in a cell population, and combine the two with the simplest digital control algorithm to show how oscillatory responses whose amplitudes grow with DNA damage can arise from single cell behaviour in which each single pulse response is independent of the extent of DNA damage. A stochastic simulation of the hypothesized control mechanism reproduces experimental observations remarkably well.

Cell Physiological Phenomena↗

PubMed2002

A discrete model of neural ensembles.

A discrete model of an ensemble of identical stochastic integrate-and-fire neurons is used to study the patterns of activity in populations of neurons that exchange excitatory messages. In a regime with small interactions among the units, the effect of the message exchange is to reduce the dispersion of the firing period of the individual neurons. In a strong interaction regime, a number of activity clusters emerge in the ensemble. Neurons in each cluster fire periodically and in synchrony with each other. The number of these self-sustained firing states characterized by distinct firing patterns towards which the network can evolve is very large. Because of their stability with respect to intrinsic fluctuations in the dynamics of the stochastic neurons, these states could, in principle, be used to encode and process large amounts of information.

Action Potentials↗