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As a result of globalization, large-scale modern-day businesses extend across borders as they engage in multinational enterprises. Such enterprises must conduct operations in disparate, culturally diverse contexts, which present challenges for implementing human resource management activities, such as whether to standardize or localize activities across borders. The current study focuses on recruitment activities, as they represent firms’ initial efforts to attract highly qualified talent. However, the extant recruitment literature has primarily been conducted in a single context or in Westernized societies; thus, it is unclear how organizations recruit across borders. Drawing on signaling theory, we explore how Fortune 1000 firms use recruiting signals in their domestic and international operations. In general, we find that firms standardize the recruiting signals across their domestic and international operations. Yet, the amount that each signal is emphasized differs in domestic and international operations and is contingent upon language. Furthermore, cultural distance between the home and host country largely does not explain the standardization of the recruiting signals. We summarize the findings and provide direction intended to guide future research.

For over 30 years, researchers have examined social influence using status characteristics theory (Berger and Conner, 1974). While research has investigated beauty and attractiveness as status characteristics (e.g., Webster and Driskell, 1983), there is a dearth of research that examines whether obesity has status value using status characteristics theory. The current paper reviews the literature on, demonstrating how they are related to status characteristics. Next, this paper demonstrates how the effects of both gender and obesity can be explained by considering them as status characteristics, which have the potential to create subsequent status beliefs and stigma. Finally, this study reports empirical findings that support obesity as a status characteristic. We find an effect for obesity on ratings of diffuse status, and effects for both obesity and gender on ratings of influence.

Polyglutamine is a naturally occurring peptide found within several proteins in neuronal cells of the brain, and its aggregation has been implicated in several neurodegenerative diseases, including Huntington's disease. The resulting aggregates have been demonstrated to possess β-sheet structure, and experimental evidence has demonstrated that aggregation begins with a nucleus composed of a single peptide. In this paper, we computationally examined the structural tendencies of mutant polyglutamine peptides that were studied experimentally, and found to aggregate with varying efficiencies. Low-energy structures were generated for each peptide by simulated annealing molecular dynamics, and were analyzed quantitatively by various geometry-based methods. In all simulations, the carboxy-terminal end of each peptide was constrained to a β-turn-β-strand structure to simulate a situation in which β-structure formation has initiated due to interaction with a seed or a growing oligomer/aggregate. Our results suggest the experimentally-observed inhibition of aggregation to be due to localized conformational restraint on the peptide backbone, which in turn confines the peptide to native coil structure, discouraging transition towards the β-sheet structure required for aggregation.

We perform potential energy calculations on mutant polyglutamine peptides that were studied experimentally, and found to aggregate with varying efficiencies. Low-energy structures were generated for each peptide by simulated annealing molecular dynamics, and were analyzed by molecular mechanics and by all-electron fragment molecular orbital energy calculations. In order to make a comparison between the two sets of potential energies, we devised a means of computing molecular-mechanical analogues of the quantum-mechanical energies. Our results suggest that in accordance with a previous paper (VanSchouwen et al., submitted for publication [16] ) the experimentally-observed inhibition of aggregation is due to localized, geometry-based effects on peptide structure, with little appreciable perturbation from longer-range non-bonded effects.

Catharanthus roseus is the sole commercial source of the monoterpenoid indole alkaloids (MIAs), vindoline and catharanthine, components of the commercially important anticancer dimers, vinblastine and vincristine. Carborundum abrasion technique was used to extract leaf epidermis–enriched mRNA, thus sampling the epidermome, or complement, of proteins expressed in the leaf epidermis. Random sequencing of the derived cDNA library established 3655 unique ESTs, composed of 1142 clusters and 2513 singletons. Virtually all known MIA pathway genes were found in this remarkable set of ESTs, while only four known genes were found in the publicly available Catharanthus EST data set. Several novel MIA pathway candidate genes were identified, as demonstrated by the cloning and functional characterization of loganic acid O-methyltransferase involved in secologanin biosynthesis. The pathways for triterpene biosynthesis were also identified, and metabolite analysis showed that oleanane-type triterpenes were localized exclusively to the cuticular wax layer. The pathways for flavonoid and very-long-chain fatty acid biosynthesis were also located in this cell type. The results illuminate the biochemical specialization of Catharanthus leaf epidermis for the production of multiple classes of metabolites. The value and versatility of this EST data set for biochemical and biological analysis of leaf epidermal cells is also discussed.

Sixteen fluorescent analogues of the lipid-soluble antioxidant vitamin α-tocopherol were prepared incorporating fluorophores at the terminus of ω-functionalized 2- n -alkyl-substituted chromanols ( 1a – d and 4a – d ) that match the methylation pattern of α-tocopherol, the most biologically active form of vitamin E. The fluorophores used include 9-anthroyloxy (AO), 7-nitrobenz-2-oxa-1,3-diazole (NBD), N -methyl anthranilamide (NMA), and dansyl (DAN). The compounds were designed to function as fluorescent reporter ligands for protein-binding and lipid transfer assays. The fluorophores were chosen to maximize the fluorescence changes observed upon moving from an aqueous environment (low fluorescence intensity) to an hydrophobic environment such as a protein’s binding site (high fluorescence intensity). Compounds 9d (anthroyloxy) and 10d (nitrobenzoxadiazole), having a C9-carbon chain between the chromanol and the fluorophore, were shown to bind specifically and reversibly to recombinant human tocopherol transfer protein (α-TTP) with dissociation constants of approximately 280 and 60 nM, respectively, as compared to 25 nM for the natural ligand 2 R ,4′ R ,8′ R -α-tocopherol. Thus, compounds have been prepared that allow the investigation of the rate of α-TTP-mediated inter-membrane transfer of α-tocopherol and to investigate the mechanism of α-TTP function at membranes of different composition.

Calculated energy differences between cis- and trans- fused bicyclic ketones are provided for bicyclo(3.3.0)octanones, bi- cyclo(4.3.0)nonanones, bicyclo(5.3.0)decanones, bicyclo(6.3.0)un- decanones and the corresponding hydrocarbons with and without angular methyl groups. The calculations were performed for HF/6- 31G* and MP2/6-31G* optimized geometries. The latter were used for subsequent single-point energy MP2/6-311G* calculations. Whenever possible, the calculated energy differences were com- pared with experimental data and found to correspond well. The results of the calculations provide a complete picture of expected energetic differences in bicyclic ketone series and will be useful in both instruction and synthetic planning. Anyone who has ever taught a course on natural product synthesis has had a need to illustrate conformational equi- libria relationships and energy differences in cis- and trans-fused ring systems. The latter topic becomes very relevant in discussions of strategy and tactics of design in terpene total synthesis. Intuitively, most of us are aware that bicyclo(3.3.0)octanes prefer cis fusion by a sufficient energy margin to obviate any need for concern in synthet- ic sequences that are subject to thermodynamic control. With larger rings this situation becomes less clear and in the area of perhydroazulene terpenoid synthesis, for ex- ample, the energetic differences between cis- and trans- fused ketones are such that stereospecific construction of either diastereomer poses serious problems in situations where bridge enolization occurs. In the bicyclo(4.3.0)de- canes placement of a carbonyl next to the ring junction is almost always required for introduction of further substit- uents and is frequently introduced to such a position by ring expansion, ring contraction, or cycloaddition tactics. Mixtures of diastereomers result in thermodynamically controlled processes or through further manipulation of products and serious tactical obstacles must be overcome in maintaining stereocontrolled preparation of targets. The primary literature, as well as monographs that focus on stereochemistry, cover the energetics of ring fusion to some extent. However, the data is relatively diffused throughout the published work in physical organic chem- istry and, to our knowledge, no single publication offers a comparative view of the commonly encountered ring sys- tems. Some attempts at discussion of this topic have been made in Mundy's book 2 and in Eliel's stereochemistry text 3 but most available data is dispersed throughout the primary literature. The purpose of this manuscript is to provide calculated energy differences of bicyclo(m.3.0)alkanones as iso- meric pairs with respect to the ring fusion. Whenever available, the calculations are compared with experimen- tal data from the literature for either the ketone or the parent hydrocarbon or both. It is hoped that this compila- tion is of equal use to instructors as it is to practitioners of synthesis. The calculated energies and their differences are present- ed in Table 1, Table 2, Table 3, and Table 4. Table 1 Energy Differences between cis- and trans- Bicyclo(3.3.0)octanes, cis- and trans-Bicyclo(3.3.0)octan-1-ones, and their Angularly Methylated Derivatives 8

A comparative molecular field analysis (CoMFA) was used to model the efficacy with which the Rhodococcus erythropolis mono-oxygenase, DszC, catalyzes the enantioselective sulfoxidation of a broad range of substrates. Experimentally determined values of both the yield and enantiomeric excess for this reaction were employed to create these CoMFA models. A highly predictive CoMFA model was constructed for the prediction of enantiomeric excess of the sulfoxide product. The predictive ability of the model was demonstrated by both cross-validation of the training set ( q 2 = 0.74) and for an external test set of substrates. The enantiomeric excesses of the members of the test set, which also included two amino acid sulfides that were structurally distinct from the membership of the training set, were predicted well by the CoMFA model. Product yield was not modelled well by any CoMFA model. Different models comparing the likely bioactive conformations of the substrates suggest that most compounds assume an ‘extended’ conformation upon binding. Contour diagrams illustrating significant substrate–enzyme interactions suggest that the model, which predicts the enantiomeric excess, is consistent with previous conclusions regarding the effect of various substrate substitutions on the enantiopurity of the product of the biotransformation.

Background It has been established that individuals who score high on measures of psychopathy demonstrate difficulty when performing tasks requiring the interpretation of other's emotional states. The aim of this study was to elucidate the relation of emotion and cognition to individual differences on a standard psychopathy personality inventory (PPI) among a nonpsychiatric population. Methods Twenty participants completed the PPI. Following survey completion, a mean split of their scores on the emotional–interpersonal factor was performed, and participants were placed into a high or low group. Functional magnetic resonance imaging data were collected while participants performed a recognition task that required attention be given to either the affect or identity of target stimuli. Results No significant behavioral differences were found. In response to the affect recognition task, significant differences between high- and low-scoring subjects were observed in several subregions of the frontal cortex, as well as the amygdala. No significant differences were found between the groups in response to the identity recognition condition. Conclusions Results indicate that participants scoring high on the PPI, although not behaviorally distinct, demonstrate a significantly different pattern of neural activity (as measured by blood oxygen level–dependent contrast)in response to tasks that require affective processing. The results suggest a unique neural signature associated with personality differences in a nonpsychiatric population.

A number of short, Monte Carlo simulated annealing runs are performed on a highly frustrated 69-mer off-lattice model protein, consisting of a chain of 69 beads that are either hydrophobic, hydrophilic, or neutral in nature, and which demonstrably folds into a six-stranded β-barrel structure. We employ an iterative, consensus-based scheme to cluster the 725 nonbonded distances between the hydrophobic beads using, in tandem, Ward’s method for hierarchical clustering and k-means partitional clustering. We also independently analyze the same data using computer-automated histogram filtering, a technology designed to cluster high-dimensional data, without the tedium and subjectivity required by our iterative implementation of the two classical clustering methods. The memberships of low-energy clusters obtained from both classical clustering and automated histogram filtering approaches are remarkably similar. Nonbonded distance constraints are derived from these clusters and from small sets of the original unc...

A number of short simulated annealing runs are performed on a highly-frustrated 46-“residue” off-lattice model protein. We perform, in an iterative fashion, a principal component analysis of the 946 nonbonded interbead distances, followed by two varieties of cluster analyses: hierarchical and k-means clustering. We identify several distinct sets of conformations with reasonably consistent cluster membership. Nonbonded distance constraints are derived for each cluster and are employed within a distance geometry approach to generate many new conformations, previously unidentified by the simulated annealing experiments. Subsequent analyses suggest that these new conformations are members of the parent clusters from which they were generated. Furthermore, several novel, previously unobserved structures with low energy were uncovered, augmenting the ensemble of simulated annealing results, and providing a complete distribution of low-energy states. The computational cost of this approach to generating low-energy conformations is small when compared to the expense of further Monte Carlo simulated annealing runs.A number of short simulated annealing runs are performed on a highly-frustrated 46-“residue” off-lattice model protein. We perform, in an iterative fashion, a principal component analysis of the 946 nonbonded interbead distances, followed by two varieties of cluster analyses: hierarchical and k-means clustering. We identify several distinct sets of conformations with reasonably consistent cluster membership. Nonbonded distance constraints are derived for each cluster and are employed within a distance geometry approach to generate many new conformations, previously unidentified by the simulated annealing experiments. Subsequent analyses suggest that these new conformations are members of the parent clusters from which they were generated. Furthermore, several novel, previously unobserved structures with low energy were uncovered, augmenting the ensemble of simulated annealing results, and providing a complete distribution of low-energy states. The computational cost of this approach to generating low-ener...

The present report used functional magnetic resonance imaging (fMRI) to examine the neural correlates of thought suppression. Subjects were imaged while alternately (i) attempting to suppress a particular thought, (ii) attempting to suppress all thoughts, or (iii) thinking freely about any thought. Suppression of a particular thought, when compared to the free-thought control condition, revealed greater activation in the anterior cingulate. When the task of suppressing all conscious thoughts was compared to free-thought, a more distributed network of brain regions, including the anterior cingulate and the insula, was activated. These findings are consistent with previous research on cognitive control and may provide potential insights into psychological disorders involving recurring, intrusive thoughts.

A questionnaire, designed to assess bleeding predispositions in tonsillectomy and/or adenoidectomy patients, was administered to 236 otherwise healthy children. For comparative purposes, 114 patients with bleeding disorders were also studied. An unsupervised non-metric clustering technique was used in an attempt to classify bleeders against non-bleeders based solely on the responses to the questionnaire. Non-metric techniques are essential for the classification process because of the large number of missing attribute values in the patient data set. As a benchmark, a supervised inductive machine learning strategy was also used to classify the patients. Performance results are compared and contrasted between the techniques across different subsets of the patient data. These techniques are also evaluated as a methodology for determining the relative significance of attributes vis-à-vis the reduction of the dimensionality of a large medical data set. In this investigation, the classification rate achieved using the non-metric technique (73%) was only marginally poorer than the rate using the supervised technique (76%). Moreover, these results were obtained with an accompanying 80% reduction in the number of attributes used to perform the analysis.

The phylloquinone acceptor PhQ(A) in photosystem I binds to the protein through a single H-bond to the backbone nitrogen of PsaA-L722. Here, we investigate the effect of this H-bond on the electron transfer (ET) kinetics by substituting threonine for PsaA-L722. Room temperature spin-polarized transient EPR measurements show that in the PsaA-L722T mutant, the rate of PhQ(A)(-) to F(X) ET increases and the hyperfine coupling to the 2-methyl group of PhQ(A) is much larger than in the wild type. Molecular dynamics simulations and ONIOM type electronic structure calculations indicate that it is possible for the OH group of the Thr side chain to form an H-bond to the carbonyl oxygen atom, O(4) of the phylloquinone, and that this results in an increase in the 2-methyl hyperfine couplings as observed in the transient EPR data. The Arrhenius plot of the PhQ(A)(-) to F(X) ET in the PsaA-L722T mutant suggests that the increased rate is probably the result of a slight change in the electronic coupling between PhQ(A)(-) and F(X). The strong deviation from Arrhenius behavior observed at ∼200 K can be reproduced using a semiclassical model, which takes the zero-point energy of the mode coupled to the ET into account. However, since the change in slope of the Arrhenius plot occurs at the protein glass transition temperature, it is argued that it could be the result of a change in the protein relaxation dynamics at this temperature rather than quantum mechanical effects.

Responses to threat occur via two known independent processing routes. We propose that early, reflexive processing is predominantly tuned to the detection of congruent combinations of facial cues that signal threat, whereas later, reflective processing is predominantly tuned to incongruent combinations of threat. To test this prediction, we examined responses to threat–gaze expression pairs (anger versus fear expression by direct versus averted gaze). We report on two functional magnetic resonance imaging (fMRI) studies, one employing prolonged presentations (2 s) of threat–gaze pairs to allow for reflective processing (Study 1), and one employing severely restricted (33 ms), backward masked presentations of threat–gaze pairs to isolate reflexive neural responding (Study 2). Our findings offer initial support for the conclusion that early, reflexive responses to threat are predominantly tuned to congruent threat–gaze pairings, whereas later reflective responses are predominantly tuned to ambiguous threat–gaze pairings. These findings highlight a distinct dual function in threat perception.

We present our results from a series of long canonical ensemble Monte Carlo simulations on the counterion and solvent distribution functions in regions close to a high charge density negatively charged polyelectrolyte. The simulations are all for the «salt free» solution; i.e., a neutralizing number of counterions are present, but there is no additional supporting electrolyte

Given the principal component analysis (PCA) of a molecular dynamics (MD) conformational trajectory for a model protein, we perform orthogonal Procrustean rotation to "best fit" the PCA squared-loading matrix to that of a target matrix computed for a related but different molecular system. The sum of squared deviations of the elements of the rotated matrix from those of the target, known as the error of fit (EOF), provides a quantitative measure of the dissimilarity between the two conformational samples. To estimate precision of the EOF, we perform bootstrap resampling of the molecular conformations within the trajectories, generating a distribution of EOF values for the system and target. The average EOF per variable is determined and visualized to ascertain where, locally, system and target sample properties differ. We illustrate this approach by analyzing MD trajectories for the wild-type and four selected mutants of the beta1 domain of protein G.

Purpose: To describe and evaluate priority setting in an Acute Care hospital in Argentina, using Accountability for Reasonableness, an ethical framework for fair priority setting. Methods: Case Study involving key informant interviews and document review. Thirty respondents were identified using a snowball sampling strategy. A modified thematic approach was used in analyzing the data. Results: Priorities are primarily determined at the Department of Health. The committee which is supposed to set priorities within the hospital was thought not to have much influence. Decisions were based on government policies and objectives, personal relationships, economic, political, historical and arbitrary reasons. Decisions at the DOH were publicized through internet; however, apart from the tenders and a general budget, details of hospital decisions were not publicized. CATA provided an accessible but ineffective forum for appeals. There were no clear mechanisms for appeals and leadership to ensure adherence to a fair process. Conclusions: In spite of their efforts to ensure fairness, Priority setting in the study hospital did not meet all the four conditions of a fair process. Policy discussions on improving legitimacy and fairness provided an opportunity for improving fairness in the hospital and Accountability for Reasonableness might be a useful framework for analysis and for identifying and improving strategies.

Global measures of structural diversity within a distribution of biopolymers, such as the radius of gyration and percent native contacts, have proven useful in the analysis of simulation data for protein folding. In this paper we describe a statistical-based methodology to quantify the local structural variability of a distribution of biopolymers, applied to 46- and 69-"residue" off-lattice, three-color model proteins. Each folds into beta-barrel structures. First we perform a principal component analysis of all interbead distance variables for a large number of independent, converged Boltzmann-distributed samples of conformations collected at each of a wide range of temperatures. Next, the principal component vectors are subjected to orthogonal (varimax) rotation. The results are displayed on so-called "squared-loading" plots. These provide a quantitative measure of the contribution to the sample variance of the position of each residue relative to the others. Dominant structural elements, those having the largest structural diversity within the sampled distribution, are responsible for peaks and shoulders observed in the specific heat versus temperature curves, generated using the weighted histogram analysis method. The loading plots indicate that the local-structural diversity of these systems changes gradually with temperature through the folding transition but radically changes near the collapse transition temperature. The analysis of the structural overlap order statistic suggests that the 46-mer thermodynamic folding transition involves the native state and at least three other nearly native intermediates. In the case of the 46-mer protein model, data are generated at sufficiently low temperatures that squared-loading plots, coupled with cluster analysis, provide a local and energetic description of its glassy state.

This chapter reviews automated histogram filtering (AHF), a recently developed approach to cluster analysis, and describes two applications of this methodology, illustrating its power as a tool for analysis of biomolecular simulation data. The first is to cluster low-energy conformations of a model protein, generated by Monte Carlo-simulated annealing. From ensuing cluster memberships, we arrive at distance constraints to serve as input to distance-geometry software. Additional low-energy structures are subsequently generated by the latter software with remarkable efficiency. The second application is to cluster molecular dynamics snapshots of an all-atom model of the response regulator protein Spo0F of Bacillus subtilis . Two clusters are uncovered, reflecting our having sampled two distinct basins on the potential energy surface. We subject snapshots for each cluster to AHF cluster analysis, and perform an orthogonal rotation of the dominant so-called ‘principal components’. We monitor the loadings of each interatomic distance variable along the rotated principal components. To visualize our results, we construct squared-loadings plots, revealing secondary structural elements that undergo concerted motions along so-called ‘collective coordinates’. Dominant collective coordinates are found to be associated with contiguous stretches of amino acid residues implicated in the biological functioning of Spo0F.

We investigated whether individual differences in racial bias among white participants predict the recruitment, and potential depletion, of executive attentional resources during contact with black individuals. White individuals completed an unobtrusive measure of racial bias, then interacted with a black individual, and finally completed an ostensibly unrelated Stroop color-naming test. In a separate functional magnetic resonance imaging (fMRI) session, subjects were presented with unfamiliar black male faces, and the activity of brain regions thought to be critical to executive control was assessed. We found that racial bias predicted activity in right dorsolateral prefrontal cortex (DLPFC) in response to black faces. Furthermore, activity in this region predicted Stroop interference after an actual interracial interaction, and it statistically mediated the relation between racial bias and Stroop interference. These results are consistent with a resource depletion account of the temporary executive dysfunction seen in racially biased individuals after interracial contact.

The amygdala is thought to be part of a neural system responsive to potential threat ( [1][1] ). Consistent with this is the amygdala's well-documented sensitivity to fear faces. What is puzzling, however, is the paucity of evidence for a similar involvement of the amygdala in the processing of

Intracellular trafficking of hydrophobic ligands is often mediated by specific binding proteins. The CRAL-TRIO motif is common to several lipid binding proteins including the cellular retinaldehyde binding protein (CRALBP), the alpha-tocopherol transfer protein (alpha-TTP), yeast phosphatidylinositol transfer protein (Sec14p), and supernatant protein factor (SPF). To examine the ligand specificity of these proteins, we measured their affinity toward a variety of hydrophobic ligands using a competitive [(3)H]-RRR-alpha-tocopherol binding assay. Alpha-TTP preferentially bound RRR-alpha-tocopherol over all other tocols assayed, exhibiting a K(d) of 25 nM. Binding affinities of other tocols for alphaTTP closely paralleled their ability to inhibit in vitro intermembrane transfer and their potency in biological assays. All other homologous proteins studied bound alpha-tocopherol but with pronouncedly weaker (10-fold) affinities than alpha-TTP. Sec14p demonstrated a K(d) of 373 nM for alpha-tocopherol, similar to that for its native ligand, phosphatidylinositol (381 nM). Human SPF had the highest affinity for phosphatidylinositol (216 nM) and gamma-tocopherol (268 nM) and significantly weaker affinity for alpha-tocopherol (K(d) 615 nM). SPF bound [(3)H]-squalene more weakly (879 nM) than the other ligands. Our data suggest that of all known CRAL-TRIO proteins, only alphaTTP is likely to serve as the physiological mediator of alpha-tocopherol's biological activity. Further, ligand promiscuity observed within this family suggests that caution should be exercised when suggesting protein function(s) from measurements utilizing a single ligand.

We introduce and apply a new classification strategy we call computerized consensus diagnosis (CCD). Its purpose is to provide robust, reliable classification of biomedical data. The strategy involves the cross-validated training of several classifiers of diverse conceptual and methodological origin on the same data, and appropriately combining their outcomes. The strategy is tested on proton magnetic resonance spectra of human thyroid biopsies, which are successfully allocated to normal or carcinoma classes. We used Linear Discriminant Analysis, a Neural Net-based method, and Genetic Programming as independent classifiers on two spectral regions, and chose the median of the six classification outcomes as the consensus. This procedure yielded 100% specificity and 100% sensitivity on the training sets, and 100% specificity and 98% sensitivity on samples of known malignancy in the test sets. We discuss the necessary steps any classification approach must take to guarantee reliability, and stress the importance of fuzziness and undecidability in robust classification.

We propose fuzzy clustering as a method to analyze molecular dynamics (MD) trajectories, especially of proteins and polypeptides. A fuzzy cluster analysis locates classes of similar three-dimensional conformations explored during a molecular dynamics simulation. The method can be readily applied to results from both equilibrium and nonequilibrium simulations, with clustering on either global or local structural parameters. The potential of this technique is illustrated by results from fuzzy cluster analyses of trajectories from MD simulations of various fragments of human parathyroid hormone (PTH). For large molecules, it is more efficient to analyze the clustering of root-mean-square distances between conformations comprising the trajectory. We found that the results of the clustering analysis were unambiguous, in terms of the optimal number of clusters of conformations, for the majority of the trajectories examined. The conformation closest to the cluster center can be chosen as being representative of the class of structures making up the cluster, and can be further analyzed, for example, in terms of its secondary structure. The CPU time used by the cluster analysis was negligible compared to the MD simulation time. © 1992 Wiley-Liss, Inc.

Functionally relevant motion of proteins has been associated with a number of atoms moving in a concerted fashion along so-called "collective coordinates." We present an approach to extract collective coordinates from conformations obtained from molecular dynamics simulations. The power of this technique for differentiating local structural fluctuations between classes of conformers obtained by clustering is illustrated by analyzing nanosecond-long trajectories for the response regulator protein Spo0F of Bacillus subtilis, generated both in vacuo and using an implicit-solvent representation. Conformational clustering is performed using automated histogram filtering of the inter-C(alpha) distances. Orthogonal (varimax) rotation of the vectors obtained by principal component analysis of these interresidue distances for the members of individual clusters is key to the interpretation of collective coordinates dominating each conformational class. The rotated loadings plots isolate significant variation in interresidue distances, and these are associated with entire mobile secondary structure elements. From this we infer concerted motions of these structural elements. For the Spo0F simulations employing an implicit-solvent representation, collective coordinates obtained in this fashion are consistent with the location of the protein's known active sites and experimentally determined mobile regions.

We report results for the dielectric constant of TIP4P and SPC water from Monte Carlo simulations at elevated temperatures. The dielectric constants from these simulations, which are much less time-consuming than those carried out at room temperature, can nevertheless be reliably extrapolated to room temperature. We find that the temperature-dependence of the Kirkwood g-factor, gk, of the TIP4P model is qualitatively the same as that of real water.

Measurements of steady-state currents in thin-layer cells provide an opportunity to apply a stringent test of theories of electrochemical transport by simultaneous diffusion and migration. We have applied such a test and find the theory to be vindicated.

We show that the classical Metropolis Monte Carlo (MMC) algorithm converges very slowly when applied to the primitive electrolyte environment for a high charge-density polyelectrolyte. This slowness of convergence, which is due to the large density inhomogeneity around the polyelectrolyte, produces noticeable errors in the ion distribution functions for MMC runs of 1.3 × 106 trial steps started from nonequilibrium distributions. We report that an algorithm which we call DSMC (for density-scaled Monte Carlo) overcomes this problem and provides relatively rapid convergence in this application. We suggest that DSMC should be well-suited for other Monte Carlo simulations on physical systems where large density inhomogeneities occur.

Estimation des fractions molaires apparaissant dans le modele lineaire qui est utilise pour decrire les donnees spectrales de masse

Studies of a cell consisting of a sheet of a porous medium soaked with an aqueous electrolyte solution containing the mercurous ion and sandwiched between mercury pools show that steady-state electrolysis may be attained in the absence of convection. Several different porous matrices have been studied and, in some cases, a very simple model of the pore structure predicts behaviour close to that observed experimentally.

The jackknife test of Rothstein et al. is applied to discrimination between several different models used to compute the rotationally inelastic cross sections for the Ar-N 2 system. The modified exponential models are the best models, except for the case where the energy gap is small, when power laws are best.

For simulations on systems that invlove a physical inhomogeneity at infinite dilution, the usual periodic boundary conditions are inappropriate. In previous studies on such systems, surfaces have been re-introduced in order to contain the particles of the sample. When smooth surfaces are used to contain liquids, undesirable structural artifacts in the liquid are promoted by these surfaces. In this study a rigid but structurally liquid-like containing surface, that we call a glassy wall boundary, is introduced, in an attempt to solve this problem. It serves as a containing surface, but “looks” nearly liquid-like to molecules in the mobile liquid near it. We illustrate the properties of this boundary for a system that consists of an isolated polyion surrounded by SPC water at 300K and ∼ 1 gcm−3. We show that this boundary reduces or eliminates some of the problems caused by a smooth surface.