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PubMed2006

Characterizing the conformational ensemble of monomeric polyglutamine.

Studies of synthetic polyglutamine peptides in vitro have established that polyglutamine peptides aggregate via a classic nucleation and growth mechanism. Chen and colleagues [Proc Natl Acad Sci U S A 2002;99:11884-11889] have found that monomeric polyglutamine, which is a disordered statistical coil in solution, is the critical nucleus for aggregation. Therefore, nucleation of beta-sheet-rich aggregates requires an initial disorder to order transition, which is a highly unfavorable thermodynamic reaction. The questions of interest to us are as follows: What are the statistical fluctuations that drive beta-sheet formation in monomeric polyglutamine? How do these fluctuations vary with chain length? And why is this process thermodynamically unfavorable, that is, why is monomeric polyglutamine disordered? To answer these questions we use multiple molecular dynamics simulations to provide quantitative characterization of conformational ensembles for two short polyglutamine peptides. We find that the ensemble for polyglutamine is indeed disordered. However, the disorder is inherently different from that of denatured proteins and the average compactness and magnitude of conformational fluctuations increase with chain length. Most importantly, the effective concentration of sidechain primary amides around backbone units is inherently high and peptide units are solvated either by hydrogen bonds to sidechains or surrounding water molecules. Due to the multiplicity of backbone solvation modes the probability associated with any specific backbone conformation is small, resulting in a conformational entropy bottleneck which makes beta-sheet formation in monomeric polyglutamine thermodynamically unfavorable.

Algorithms↗

PubMed2006

De novo ligand design to an ensemble of protein structures.

We describe a combinatorial method for de novo ligand design to an ensemble of receptor structures. Receptor conformations, protonation states, and structural water molecules are considered consistently within the framework of de novo ligand design. The method relies on Monte Carlo optimization to search the space of ligand structures, conformations, and rigid-body movements as well as receptor models. The method is applied to an ensemble of HIV protease and human collagenase receptor models. Ligand structures generated de novo exhibit the correct hydrogen-bonding pattern in the core of the active site, with hydrophobic groups extending into the receptor S1 and S1' pocket space. Furthermore, it is shown that known ligands are recovered in the correct binding mode and in the native, most tightly binding receptor model.

Binding Sites↗

PubMed1997

Consciousness and cognition may be mediated by multiple independent coherent ensembles.

Short-term or working memory (WM) provides temporary storage of information in the brain after an experience and is associated with conscious awareness. Neurons sensitive to the multiple stimulus attributes comprising an experience are distributed within many brain regions. Such distributed cell assemblies, activated by an event, are the most plausible system to represent the WM of that event. Studies with a variety of imaging technologies have implicated widespread brain regions in the mediation of WM for different categories of information. Each kind of WM may thus be expected to involve many brain regions rather than a local, uniquely dedicated set of cells. Neurons in a distributed "cell assembly" may be self-selected by their temporally coherent activations. The process by which this fragmented representation of the recent past is reassembled to accomplish essentially automatic and reliable recognition of a recurrent event constitutes an important problem. One plausible mechanism to achieve the identification of past with previous events would require that the representational system mediating WM must coexist in spatial extent and somehow overlap in temporal activation with cell ensembles registering input from subsequent events. The detection of such a postulated mechanism required an experimental approach which would focus upon spatial patterns of coherent activation while information about different events was stored in WM and retrieved, rather than focusing upon the temporal sequences of activation in localized regions of interest. For this purpose, the familiar delayed matching from sample (DMS) task was modified. A series of information-free flashes, or "noncontingent probes," was presented before an initial series of visual information items, the Priming Sample, which were to be held in WM during a Delay Period. A second series of visual information items were then presented, the Matching Sample. The task required detection of any item in the second series which had been absent from the initial series. Thirty such trials with a particular category of visual information constituted a single task. Several DMS tasks with this standardized design, but with different categories of visual information, were presented within each test session. The information categories included letters of the alphabet, single digit numbers, or faces from a school yearbook. Event-related potentials (ERPs), were computed from 21 standardized electrode placements, separately for information-free probes and for information items in each interval of the trials within a task. Because each electrode is particularly sensitive to coherent activation of neurons in the immediately underlying brain regions, topographic maps were constructed and interpolated across the surface of the scalp. The momentary fluctuations of the resulting voltage "landscapes" throughout the task were then subjected to quantitative analysis. Distinctive landscapes sometimes persisted for prolonged periods, implying sustained engagement of very large populations of neurons. "Difference landscapes" were constructed by subtraction of topographic maps evoked by noncontingent probes during the Delay Period from maps of probe ERPs before the presentation of the initial information in the Priming Sample. Such probe difference landscapes displayed recurrent high similarity to momentary landscapes elicited during subsequent presentation of the information items in the Matching Sample. It seemed as if the distributed cell assembly continuously engaged by mediation of WM of the diverse attributes of the initial stimuli was being dynamically compared to the ensembles engaged by registration of the subsequent stimuli. Spatial Principal Component Analysis was applied to the sequences of momentary voltage landscapes observed throughout trials of each task. This method sought a small number of spatial patterns with which these large sets of inhomogeneous spatial distributions of voltage co

Adult↗

PubMed1997

Molecular docking to ensembles of protein structures.

Until recently, applications of molecular docking assumed that the macromolecular receptor exists in a single, rigid conformation. However, structural studies involving different ligands bound to the same target biomolecule frequently reveal modest but significant conformational changes in the target. In this paper, two related methods for molecular docking are described that utilize information on conformational variability from ensembles of experimental receptor structures. One method combines the information into an "energy-weighted average" of the interaction energy between a ligand and each receptor structure. The other method performs the averaging on a structural level, producing a "geometry-weighted average" of the inter-molecular force field score used in DOCK 3.5. Both methods have been applied in docking small molecules to ensembles of crystal and solution structures, and we show that experimentally determined binding orientations and computed energies of known ligands can be reproduced accurately. The use of composite grids, when conformationally different protein structures are available, yields an improvement in computational speed for database searches in proportion to the number of structures.

Computer Simulation↗

PubMed1999

Exploring structures in protein folding funnels with free energy functionals: the transition state ensemble.

We use free energy functionals that account for the partial ordering of residues in the transition state ensemble to characterize the free energy surfaces for fast folding proteins. We concentrate on chymotrypsin inhibitor and lambda-repressor. We show how the explicit cooperativity that can arise from many body forces, such as side-chain ordering or hydrophobic surface burial, determines the crossover from folding with a large delocalized nucleus and the specific small classical nucleus of the type envisioned in nucleation growth scenarios. We compare the structural correlations present in the transition state ensemble obtained from free energy functionals with those inferred from experiment using extrathermodynamic free energy relations for folding time obtained via protein engineering kinetics experiments. We also use the free energy functionals to examine both the size of barriers and multidimensional representations of the free energy profiles in order to address the question of appropriate reaction coordinates for folding.

DNA-Binding Proteins↗

PubMed2002

Stiffness of the distal loop restricts the structural heterogeneity of the transition state ensemble in SH3 domains.

Protein engineering experiments and Phi(F)-value analysis of SH3 domains reveal that their transition state ensemble (TSE) is conformationally restricted, i.e. the fluctuations in the transition state (TS) structures are small. In the TS of src SH3 and alpha-spectrin SH3 the distal loop and the associated hairpin are fully structured, while the rest of the protein is relatively disordered. If native structure predominantly determines the folding mechanism, the findings for SH3 folds raise the question: What are the features of the native topology that determine the nature of the TSE? We propose that the presence of stiff loops in the native state that connect local structural elements (such as the distal hairpin in SH3 domains) conformationally restricts TSE. We validate this hypothesis using the simulations of a "control" system (16 residue beta-hairpin forming C-terminal fragment of the GBl protein) and its variants. In these fragments the role of bending rigidity in determining the nature of the TSE can be directly examined without complications arising from interactions with the rest of the protein. The TSE structures in the beta-hairpins are determined computationally using cluster analysis and limited Phi(F)-value analysis. Both techniques prove that the conformational heterogeneity decreases as the bending rigidity of the loop increases. To extend this finding to SH3 domains a measure of bending rigidity based on loop curvature, which utilizes native structures in the Protein Data Bank (PDB), is introduced. Using this measure we show that, with few exceptions, the ordering of stiffness of the distal, n-src, and RT loops in the 29 PDB structures of SH3 domains is conserved. Combining the simulation results for beta-hairpins and the analysis of PDB structures for SH3 domains, we propose that the stiff distal loop restricts the conformational fluctuations in the TSE. We also predict that constraining the distal loop to be preformed in the denatured ensemble should not alter the nature of TSE. On the other hand, if the amino and carboxy terminals are cross-linked to form a circular polypeptide chain, the pathways and TSs are altered. These contrasting scenarios are illustrated using simulations of cross-linked WT beta-hairpin fragments. Computations of bending rigidities for immunoglobulin-like domain proteins reveal no clear separation in the stiffness of their loops. In the beta-sandwich proteins, which have large fractions of non-local native contacts, the nature of the TSE cannot be apparently determined using purely local structural characteristics. Nevertheless, the measure of loop stiffness still provides qualitative predictions of the ordered regions in the TSE of Ig27 and TenFn3.

Amino Acid Sequence↗

PubMed1982

Motor command in the ventrolateral thalamic nucleus: neuronal variability can be overcome by ensemble average.

The variability and stationarity of single unit activity and reaction times in a simple reaction time task were investigated by means of unit recordings from the ventrolateral thalamic nucleus in the cat. The study was carried out on eight neurons recorded over many trials and displaying an increase in activity correlated with the performed reaction time. The stationarity of the correlation appeared to be better than that of the unit activity or reaction time taken alone. In this stationary process the neuronal variability is considerable, and the investigator has to use time averages over many trials to be able to extract information from the single unit data. Since the nervous system does not required repeated presentations of a stimulus to trigger a movement, it must be using parallel processing of information throught ensemble averages. A simulation of an ensemble average based upon the data from these eight neurons showed that such a process can be efficient. An evaluation of the number of neurons required to obtain a quasi deterministic neuronal command of the reaction time value, gave the speculative figure of 70. This figure could represent the dimension of the set of neurons with the same characteristics involved in the motor command.

Animals↗

PubMed1985

The influence of clothing ensembles on the lower critical temperature.

This paper describes the effect of clothing insulation on the lower critical temperature (LCT). Twelve young adult females were exposed to a temperature of 10 degrees C for 2 1/2 h. LCT was estimated at five different clothing conditions according to the intersect method. The total weights of clothing ensembles (CW) of the five conditions were 0.45, 0.52, 0.82, 1.34, and 2.56 kg, and their thermal insulating values (I) were 0.44, 0.60, 0.77, 1.21, and 2.14 clo, respectively. LCT of the five clothing ensembles were estimated to be 26.4, 25.4, 23.5, 21.5, and 17.5 degrees C, respectively. The regression equation of the logarithm of LCT on CW was calculated as logLCT = 1.4469-0.08283 CW and that on I was log LCT = 1.4613-0.10526 I, respectively. The rate of changes in LCT is suggested to be dependent on the clothing conditions as for the following equations: dLCT/dCW = -5.34 exp(-0.1907 CW) or dLCT/dI = -7.01 exp(-0.2424 I).

Adolescent↗

PubMed1995

Comparison of two cool vests on heat-strain reduction while wearing a firefighting ensemble.

This study evaluated the effectiveness of a six-pack versus a four-pack cool vest in reducing heat strain in men dressed in firefighting ensemble, while resting and exercising in a warm/humid environment [34.4 degrees C (day bulb), 28.9 degrees C (wet bulb)]. Male volunteers (n = 12) were monitored for rectal temperature (Tre), mean skin temperature (Tsk), heart rate, and energy expenditure during three test trials: control (no cool vest), four-pack vest, and six-pack vest. The cool vests were worn under the firefighting ensemble and over Navy dungarees. The protocol consisted of two cycles of 30 min seated rest and 30 min walking on a motorized treadmill (1.12 m.s-1, 0% grade). Tolerance time for the control trial (93 min) was significantly less than both vest trials (120 min). Throughout heat exposure, energy expenditure varied during rest and exercise, but no differences existed among all trials (P > 0.05). During the first 60 min of heat exposure, physiological responses were similar for the four-pack and six-pack vests. However, during the second 60 min of heat exposure the six-pack vest had a greater impact on reducing heat strain than the four-pack vest. Peak Tre and Tsk at the end of heat exposure for 6-pack vest [mean (SD) 38.0(0.3) degrees C and 36.8(0.7) degrees C] were significantly lower compared to four-pack [38.6(0.4) degrees C and 38.1(0.5) degrees C] and controls [38.9(0.5) degrees C and 38.4(0.5) degrees C].(ABSTRACT TRUNCATED AT 250 WORDS)

Adult↗

PubMed2004

Decoding of path-guided apparent motion from neural ensembles in posterior parietal cortex.

We compared quantitatively the psychometric capacity of human subjects to detect path-guided apparent motion (PAM) and the accuracy of cell ensembles in area 7a to code the same type of stimuli. Nine human subjects performed a detection task of PAM. They were instructed to indicate with a key-press whether they perceived a circularly moving object when five stimuli were flashed successively at the vertices of a regular pentagon. The stimuli were presented along a low contrast circular path with one of 33 speeds (150-600 degrees /s). The average psychometric curve revealed that the threshold for PAM detection was 314 degrees /s. The minimum and maximum thresholds for individual subjects were 277 degrees and 378 degrees /s, respectively. In addition, the activity of cells in area 7a that were modulated by the stimulus position in real or apparent motion was used in a multivariate linear regression analysis to recover the stimulus position over time. Real stimulus motion was decoded successfully from neural ensemble activity at all speeds. In contrast, the decoding of PAM was poor at low stimulus speeds but improved markedly above 300 degrees /s: in fact, this was very close to the threshold above for human subjects to perceive continuous stimulus motion in this condition. These results suggest that the posterior parietal cortex is part of a high-level system that is directly involved in the dynamic representation of complex motion.

Adult↗

PubMed2006

Morphological assembly mechanisms in Neotropical bat assemblages and ensembles within a landscape.

Empirical studies on bat assemblages have shown that richness is not appreciably influenced by local processes such as ecological interactions. However, most of these studies have been done in large areas that include high heterogeneity, and they analyse all bat species within such areas, and thus they may be not reflecting local but supra-community conditions. We followed an ecomorphological approach to assess how bat assemblages of species from the families Phyllostomidae and Mormoopidae, and ensembles of frugivorous bats, are assembled in local habitats within a single landscape. We measured the volume of the space defined by wing morphology and quantified the average distance between species within such a volume. Then, we related these measures to local richness. Such relationships were contrasted against relationships with random assemblages to test for statistical differences. At the ensemble level of organization, we found that the frugivorous bat morphological assembly mechanism is different from random patterns, and it corresponds to the volume-increasing model. On the other hand, bat assembly mechanisms may be ubiquitous at the assemblage level, because groups of species coexisting in a local habitat and delimited only by phylogeny include more than one ecological group with no potential to interact. Assembling processes are crucial to an understanding of species diversity in local communities, and ecomorphological analyses are very promising tools that may help in their study.

Analysis of Variance↗

PubMed1996

Competition and the canonical ensemble.

Gibbs' canonical ensemble model from equilibrium statistical mechanics furnishes solutions to Eigen's phenomenological rate equations under constant total organization in cases with or without mutability. The evolution of species with mutation under constant total organization reduces to the evolution of substantial virtual species without mutation under the same constant total organization. Application of the canonical ensemble model provides an exact correspondence between thermodynamic and biological parameters. In particular, evolutionary time, as the analog of temperature, emerges as a statistical aggregate of the condition of the evolving system.

Biological Evolution↗

PubMedDate not supplied

An efficient method for detecting connectivity in neural ensembles.

Modern technology is allowing researchers to collect data from neural ensembles with a large number of units, and the analysis of interaction between these units can be very time consuming. Estimation of pairwise connectivity is the most common method of determining the neural 'network' but usually necessitates the production of numerous histograms for each pair considered. We present a method which will indicate which pairs in a network represent potential connections and thereby simplify the postexperimental analysis. The technique uses cross-interval information to create an n x n matrix which represents all possible connections in an n neuron ensemble and can be calculated recursively on-line. The performance of this technique is analyzed with respect to data size and strength of the connections. It is compared to 2 similar techniques that are also presented here, one in which perfect knowledge of the timing of the excitation is known, and one in which the timing can be bounded.

Computer Simulation↗

PubMed2006

Hum-PLoc: a novel ensemble classifier for predicting human protein subcellular localization.

Predicting subcellular localization of human proteins is a challenging problem, especially when unknown query proteins do not have significant homology to proteins of known subcellular locations and when more locations need to be covered. To tackle the challenge, protein samples are expressed by hybridizing the gene ontology (GO) database and amphiphilic pseudo amino acid composition (PseAA). Based on such a representation frame, a novel ensemble classifier, called "Hum-PLoc", was developed by fusing many basic individual classifiers through a voting system. The "engine" of these basic classifiers was operated by the KNN (K-nearest neighbor) rule. As a demonstration, tests were performed with the ensemble classifier for human proteins among the following 12 locations: (1) centriole; (2) cytoplasm; (3) cytoskeleton; (4) endoplasmic reticulum; (5) extracell; (6) Golgi apparatus; (7) lysosome; (8) microsome; (9) mitochondrion; (10) nucleus; (11) peroxisome; (12) plasma membrane. To get rid of redundancy and homology bias, none of the proteins investigated here had > or = 25% sequence identity to any other in a same subcellular location. The overall success rates thus obtained via the jackknife cross-validation test and independent dataset test were 81.1% and 85.0%, respectively, which are more than 50% higher than those obtained by the other existing methods on the same stringent datasets. Furthermore, an incisive and compelling analysis was given to elucidate that the overwhelmingly high success rate obtained by the new predictor is by no means due to a trivial utilization of the GO annotations. This is because, for those proteins with "subcellular location unknown" annotation in Swiss-Prot database, most (more than 99%) of their corresponding GO numbers in GO database are also annotated with "cellular component unknown". The information and clues for predicting subcellular locations of proteins are actually buried into a series of tedious GO numbers, just like they are buried into a pile of complicated amino acid sequences although with a different manner and "depth". To dig out the knowledge about their locations, a sophisticated operation engine is needed. And the current predictor is one of these kinds, and has proved to be a very powerful one. The Hum-PLoc classifier is available as a web-server at http://202.120.37.186/bioinf/hum.

Algorithms↗

PubMed2026

Quantifying the peripheral surface information entropy from conformational ensembles of globular protein-peptide complexes.

Predicting favorable protein-peptide binding events remains a central challenge in biophysics, with continued uncertainty surrounding how nonlocal effects shape the global energy landscape. Here, we introduce peripheral surface information entropy, SΨ, a quantitative measure of the statistical variability in apolar and charged non-interacting surface (NIS) proportions across conformational ensembles. Within the Gibbs free-energy relation ΔG = ΔH - TΔS, SΨ is proposed as a computationally tractable entropic proxy rather than a direct thermodynamic observable or stand-alone estimator of binding affinity. Using energy-directed molecular docking via HADDOCK3 and explicit-solvent molecular dynamics simulations, it is demonstrated that favorable binding partners exhibit emergent, low-entropy N-states (discrete macrostates in NIS state space) indicative of preferential apolar/charged surface configurations. Across dozens of peptides and multiple receptor systems (WW, PDZ, and MDM2 domains), dominant N-states persisted under varied docking parameters and initial conditions. A meta-ensemble of 657 complexes from 36 experiments over 15 years confirmed the presence of dominant NIS modes independent of in silico methodology, suggesting an evolutionary selection pressure toward specific NIS fingerprints. These findings establish SΨ as a thermoinformatic descriptor that encodes favorable binding constraints into unique statistical signatures of the NIS.

Entropy↗

PubMed2005

Comparison of the current RefSeq, Ensembl and EST databases for counting genes and gene discovery.

Large amounts of refined sequence material in the form of predicted, curated and annotated genes and expressed sequences tags (ESTs) have recently been added to the NCBI databases. We matched the transcript-sequences of RefSeq, Ensembl and dbEST in an attempt to provide an updated overview of how many unique human genes can be found. The results indicate that there are about 25000 unique genes in the union of RefSeq and Ensembl with 12-18% and 8-13% of the genes in each set unique to the other set, respectively. About 20% of all genes had splice variants. There are a considerable number of ESTs (2200000) that do not match the identified genes and we used an in-house pipeline to identify 22 novel genes from Genscan predictions that have considerable EST coverage. The study provides an insight into the current status of human gene catalogues and shows that considerable refinement of methods and datasets is needed to come to a conclusive gene count.

Alternative Splicing↗

PubMed2005

Reconstruction of the src-SH3 protein domain transition state ensemble using multiscale molecular dynamics simulations.

We use an integrated computational approach to reconstruct accurately the transition state ensemble (TSE) for folding of the src-SH3 protein domain. We first identify putative TSE conformations from free energy surfaces generated by importance sampling molecular dynamics for a fully atomic, solvated model of the src-SH3 protein domain. These putative TSE conformations are then subjected to a folding analysis using a coarse-grained representation of the protein and rapid discrete molecular dynamics simulations. Those conformations that fold to the native conformation with a probability (P(fold)) of approximately 0.5, constitute the true transition state. Approximately 20% of the putative TSE structures were found to have a P(fold) near 0.5, indicating that, although correct TSE conformations are populated at the free energy barrier, there is a critical need to refine this ensemble. Our simulations indicate that the true TSE conformations are compact, with a well-defined central beta sheet, in good agreement with previous experimental and theoretical studies. A structured central beta sheet was found to be present in a number of pre-TSE conformations, however, indicating that this element, although required in the transition state, does not define it uniquely. An additional tight cluster of contacts between highly conserved residues belonging to the diverging turn and second beta-sheet of the protein emerged as being critical elements of the folding nucleus. A number of commonly used order parameters to identify the transition state for folding were investigated, with the number of native Cbeta contacts displaying the most satisfactory correlation with P(fold) values.

Models, Molecular↗

PubMed2004

PSTH-based classification of sensory stimuli using ensembles of single neurons.

The problem of understanding how ensembles of neurons code for somatosensory information has been defined as a classification problem: given the response of a population of neurons to a set of stimuli, which stimulus generated the response on a single-trial basis? Multivariate statistical techniques such as linear discriminant analysis (LDA) and artificial neural networks (ANNs), and different types of preprocessing stages, such as principal and independent component analysis, have been used to solve this classification problem, with surprisingly small performance differences. Therefore, the goal of this project was to design a new method to maximize computational efficiency rather than classification performance. We developed a peri-stimulus time histogram (PSTH)-based method, which consists of creating a set of templates based on the average neural responses to stimuli and classifying each single trial by assigning it to the stimulus with the 'closest' template in the Euclidean distance sense. The PSTH-based method is computationally more efficient than methods as simple as linear discriminant analysis, performs significantly better than discriminant analyses (linear, quadratic or Mahalanobis) when small binsizes are used (1 ms) and as well as LDA with any other binsize, is optimal among other minimum-distance classifiers and can be optimally applied on raw neural data without a previous stage of dimension reduction. We conclude that the PSTH-based method is an efficient alternative to more sophisticated methods such as LDA and ANNs to study how ensemble of neurons code for discrete sensory stimuli, especially when datasets with many variables are used and when the time resolution of the neural code is one of the factors of interest.

Action Potentials↗