Detection of bacteriocin activity in bacteria using hydrophobic grid membrane filters

Seven known bacteriocin-producing bacterial strains were examined using three newly developed bacteriocin detection methods employing hydrophobic gridmembrane niters (HGMF): (i) filtration, (ii) multiple square inoculation, and (iii) one square inoculation, and the three reference methods: (i) simultaneous direct cross-streak, (ii) deferred direct cross-streak, and (iii) agar disc. The HGMF membrane multiple square inoculation method detected bacteriocin activity in all seven strains. This method also yielded similar or slightly better results than those obtained using the deferred direct cross-streak or agar disc methods. Bacteriocin activity was observed in six of seven and four of seven strains using the one square inoculation and filtration methods, respectively, with corresponding inhibiting zones measuring 2–24 and 6–20 mm in diameter.     

Collaborative grid infrastructure for molecular simulations: The eMinerals minigrid as a prototype integrated compute and data grid

This paper describes a prototype grid infrastructure, called the “eMinerals minigrid”, for molecular simulation scientists. which is based on an integration of shared compute and data resources. We describe the key components, namely the use of Condor pools, Linux/Unix clusters with PBS and IBM's LoadLeveller job handling tools, the use of Globus for security handling, the use of Condor-G tools for wrapping globus job submit commands, Condor's DAGman tool for handling workflow, the Storage Resource Broker for handling data, and the CCLRC dataportal and associated tools for both archiving data with metadata and making data available to other workers.     

Computational investigations of gram-negative bacteria phosphopantetheine adenylyltransferase inhibitors using 3D-QSAR,molecular docking and molecular dynamic simulations

Abstract

Phosphopantetheine adenylyltransferase (PPAT) has been recognized as a promising target to develop novel antimicrobial agents, which is a hexameric enzyme that catalyzes the penultimate step in coenzyme A biosynthesis. In this work, molecular modeling study was performed with a series of PPAT inhibitors using molecular docking, three-dimensional qualitative structure-activity relationship (3D-QSAR) and molecular dynamic (MD) simulations to reveal the structural determinants for their bioactivities. Molecular docking study was applied to understand the binding mode of PPAT with its inhibitors. Subsequently, 3D-QSAR model was constructed to find the features required for different substituents on the scaffolds. For the best comparative molecular field analysis (CoMFA) model, the Q² and R² values of which were calculated as 0.702 and 0.989, while they were calculated as 0.767 and 0.983 for the best comparative molecular similarity index analysis model. The statistical data verified the significance and accuracy of our 3D-QSAR models. Furthermore, MD simulations were carried out to evaluate the stability of the receptor–ligand contacts in physiological conditions, and the results were consistent with molecular docking studies and 3D-QSAR contour map analysis. Binding free energy was calculated with molecular mechanics generalized born surface area approach, the result of which coincided well with bioactivities and demonstrated that van der Waals accounted for the largest portion. Overall, our study provided a valuable insight for further research work on the recognition of potent PPAT inhibitors.

Communicated by Ramaswamy H. Sarma     

Modeling the adaptive potential of isolated populations: experimental simulations using Drosophila

The genetic variability underlying many morphological and stress resistance traits may largely depend on the effects of genetic drift balanced by polygenic mutation. This model of adaptive potential has played a central role in the minimum viable population size concept and has been used to predict the effective population size necessary to prevent extinction within changing environments. However, there have been few long-term experimental studies of adaptive potential within isolated populations, and no study has thus far provided an experimental test of the drift-mutation model of quantitative genetic variation. Using the sternopleural bristle number of Drosophila melanogaster as a model quantitative trait, we performed repeated measurements of adaptive potential on 15 replicate populations of two and 10 male-female pairs over 30 and 77 generations, respectively. Declines in adaptive potential were analyzed by comparing observed and expected changes in realized heritability over time. The only significant model deviation occurred immediately after bottlenecks of two pairs, in which greater than expected declines in realized heritability were observed. This result suggests that changes in allelic diversity during bottleneck events may be as important as changes in heterozygosity in determining adaptive potential. Drift-mutation model expectations were otherwise realized over all generations. Our results validate the use of the drift-mutation model as a tool for understanding the dynamics of adaptive potential for peripheral fitness characters, but suggest caution in applying this model to recently bottlenecked populations.     

Virtual screening using molecular simulations

Effective virtual screening relies on our ability to make accurate prediction of protein-ligand binding, which remains a great challenge. In this work, utilizing the molecular-mechanics Poisson-Boltzmann (or Generalized Born) surface area approach, we have evaluated the binding affinity of a set of 156 ligands to seven families of proteins, trypsin β, thrombin α, cyclin-dependent kinase (CDK), cAMP-dependent kinase (PKA), urokinase-type plasminogen activator, β-glucosidase A, and coagulation factor Xa. The effect of protein dielectric constant in the implicit-solvent model on the binding free energy calculation is shown to be important. The statistical correlations between the binding energy calculated from the implicit-solvent approach and experimental free energy are in the range of 0.56-0.79 across all the families. This performance is better than that of typical docking programs especially given that the latter is directly trained using known binding data whereas the molecular mechanics is based on general physical parameters. Estimation of entropic contribution remains the barrier to accurate free energy calculation. We show that the traditional rigid rotor harmonic oscillator approximation is unable to improve the binding free energy prediction. Inclusion of conformational restriction seems to be promising but requires further investigation. On the other hand, our preliminary study suggests that implicit-solvent based alchemical perturbation, which offers explicit sampling of configuration entropy, can be a viable approach to significantly improve the prediction of binding free energy. Overall, the molecular mechanics approach has the potential for medium to high-throughput computational drug discovery.     

Onset-potency relationship of nondepolarizing muscle relaxants: a reexamination using simulations

Nondepolarizing muscle relaxants (MRs) display an inverse onset-potency relationship, that is, less potent MRs display a more rapid onset. We have conducted the current investigation to estimate the impact of variable pharmacokinetic or pharmacodynamic properties of the MRs on potency and onset time, and on the onset-potency relationship. Using a model of neuromuscular transmission, we changed either the affinity of MRs for the postsynaptic receptors or the pharmacokinetic properties of the MRs. The elimination rate constant, k(10), which defines the systemic clearance, was assigned one of 9 values and the transport rate constant, k(12), one of 5 values. The transport rate constant into the effect compartment was constant (k(e1) = 0.2 min(-1)). Only one parameter was altered at a time. With constant pharmacokinetics, a 100-fold decrease in affinity caused a proportional decrease in potency, but little change (0.02 min) in onset time. With constant affinity, increasing the clearance from 1 to 250 mL x kg(-1) x min(-1) shortened the onset time from 7.2 to 0.7 min and decreased the potency 12-fold. In a double logarithmic plot, the onset-potency relationship was linear. Lesser affinities produce a nearly parallel rightward shift of the regression lines. The inverse onset-potency relationship may be explained by the pharmacokinetic factors producing changes in both the potency and onset times.     

Thermal unfolding simulations of apo-calmodulin using leap-dynamics

The simulation method leap-dynamics (LD) has been applied to protein thermal unfolding simulations to investigate domain-specific unfolding behavior. Thermal unfolding simulations of the 148-residue protein apo-calmodulin with implicit solvent were performed at temperatures 290 K, 325 K, and 360 K and compared with the corresponding molecular dynamics trajectories in terms of a number of calculated conformational parameters. The main experimental results of unfolding are reproduced in showing the lower stability of the C-domain: at 290 K, both the N- and C-domains are essentially stable; at 325 K, the C-domain unfolds, whereas the N-domain remains folded; and at 360 K, both domains unfold extensively. This behavior could not be reproduced by molecular dynamics simulations alone under the same conditions. These results show an encouraging degree of convergence between experiment and LD simulation. The simulations are able to describe the overall plasticity of the apo-calmodulin structure and to reveal details such as reversible folding/unfolding events within single helices. The results show that by using the combined application of a fast and efficient sampling routine with a detailed molecular dynamics force field, unfolding simulations of proteins at atomic resolution are within the scope of current computational power.     

Characterising model dynamics using sparse grid interpolation: Parameter estimation of cholera

Sparse grid interpolation is a popular numerical discretization technique for the treatment of high dimensional, multivariate problems. We consider the case of using time-series data to calibrate epidemiological models from both phenomenological and mechanistic perspectives using this computational tool. By capturing the dynamics underlying both global and local spaces, our algorithm identifies potentially optimal regions of the parameter space and directs computational effort towards resolving the dynamics and resulting fits of these regions. We demonstrate how sparse grid interpolants can be effectively deployed to fit available data and discriminate between competing hypotheses to explain the current cholera epidemic in Yemen.     

Assessing the performance of DNA barcoding using posterior predictive simulations

Accurate estimates of biodiversity are required for research in a broad array of biological subdisciplines including ecology, evolution, systematics, conservation and biodiversity science. The use of statistical models and genetic data, particularly DNA barcoding, has been suggested as an important tool for remedying the large gaps in our current understanding of biodiversity. However, the reliability of biodiversity estimates obtained using these approaches depends on how well the statistical models that are used describe the evolutionary process underlying the genetic data. In this study, we utilize data from the Barcode of Life Database and posterior predictive simulations to assess the performance of DNA barcoding under commonly used substitution models. We demonstrate that the success of DNA barcoding varies widely across DNA substitution models and that model choice has a substantial impact on the number of operational taxonomic units identified (changing results by ~4–31%). Additionally, we demonstrate that the widely followed practice of a priori assuming the Kimura 2‐parameter model for DNA barcoding is statistically unjustified and should be avoided. Using both data‐based and inference‐based test statistics, we detect variation in model performance across taxonomic groups, clustering algorithms, genetic divergence thresholds and substitution models. Taken together, these results illustrate the importance of considering both model selection and model adequacy in studies quantifying biodiversity.     

Princeton_TIGRESS: Protein geometry refinement using simulations and support vector machines

Protein structure refinement aims to perform a set of operations given a predicted structure to improve model quality and accuracy with respect to the native in a blind fashion. Despite the numerous computational approaches to the protein refinement problem reported in the previous three CASPs, an overwhelming majority of methods degrade models rather than improve them. We initially developed a method tested using blind predictions during CASP10 which was officially ranked in 5th place among all methods in the refinement category. Here, we present Princeton_TIGRESS, which when benchmarked on all CASP 7,8,9, and 10 refinement targets, simultaneously increased GDT_TS 76% of the time with an average improvement of 0.83 GDT_TS points per structure. The method was additionally benchmarked on models produced by top performing three‐dimensional structure prediction servers during CASP10. The robustness of the Princeton_TIGRESS protocol was also tested for different random seeds. We make the Princeton_TIGRESS refinement protocol freely available as a web server at http://atlas.princeton.edu/refinement . Using this protocol, one can consistently refine a prediction to help bridge the gap between a predicted structure and the actual native structure. Proteins 2014; 82:794–814. © 2013 Wiley Periodicals, Inc.     

Accurate detection of protein:ligand binding sites using molecular dynamics simulations

Accurate prediction of location of cavities and surface grooves in proteins is important, as these are potential sites for ligand binding. Several currently available programs for cavity detection are unable to detect cavities near the surface or surface grooves. In the present study, an optimized molecular dynamics based procedure is described for detection and quantification of interior cavities as well as surface pockets. This is based on the observation that the mobility of water in such pockets is significantly lower than that of bulk water. The algorithm efficiently detects surface grooves that are sites of protein-ligand and protein-protein interaction. The algorithm was also used to substantially improve the performance of an automated docking procedure for docking monomers of nonobligate protein-protein complexes. In addition, it was applied to predict key residues involved in the binding of the E. coli toxin CcdB with its inhibitor. Predictions were subsequently validated by mutagenesis experiments.     

Prediction of the stability of coiled coils using molecular dynamics simulations

We have performed 40–80 ns-long molecular dynamics (MD) simulations of the GCN4 leucine zipper and synthetic coiled coils using the GROMOS96 (43a2) and OPLS-AA force fields, with the aim of predicting coiled coil stability. Starting with an initial configuration of two peptides placed in an ideal coiled coil configuration, we find that changing the amino acid sequence modestly or decreasing peptide length can lead to a decrease in the final α-helicity of coiled coils, although for peptides as long or longer than 16 residues, the values of helicity do not decrease to the low values seen in the experimental results of Lumb et al. (Biochemistry. 1994, 33, 7361–7367) or of Su et al. (Biochemistry. 1994, 33, 15501–15510), presumably because the simulations are not long enough. We find, however, that helicity correlates positively with the number of close hydrophobic interactions between the two peptides, showing that stable coiled coils in the simulations are tightly packed. The minimum interhelical distances are 0.50–0.66 nm for charged groups, indicating that favorable charge interactions are also important for the stability of the coiled coil.     

Enzymatic reduction of chromate: comparative studies using sulfate-reducing bacteria

Various sulfate-reducing bacteria of the genera Desulfovibrio and Desulfomicrobium were tested and compared for enzymatic reduction of chromate. Our study demonstrated that the ability to reduce chromate is widespread among sulfate-reducing bacteria. Among them, Desulfomicrobium norvegicum reduced Cr(VI) with the highest reaction rate. This strain grew in the presence of up to 500 μM chromate, but Cr(VI) reduction in the absence of sulfate was not associated with growth. The presence of chromate induced morphological changes and leakage of periplasmic proteins into the medium. The ability of isolated polyheme cytochromes c from sulfate- and sulfur-reducing bacteria to reduce chromate was also analyzed. Tetraheme cytochrome c ₃(M _r. 13,000) from Desulfomicrobium norvegicum showed twice as much activity as either tetraheme cytochrome c ₃ from Desulfovibrio vulgaris strain Hildenborough or triheme cytochrome c ₇ from Desulfuromonas acetoxidans. Results with cytochromes c ₃ and other c-type cytochromes altered by site-directed mutagenesis indicated that negative redox potential hemes are crucial for metal reductase activity. The present study also demonstrated that the (Fe) hydrogenase from sulfate-reducing bacteria could reduce chromate. Received: 14 April 2000 / Received revision: 6 July 2000 / Accepted: 9 July 2000     

Intersegmental coordination in the lamprey: simulations using a network model without segmental boundaries

Swimming in vertebrates such as eel and lamprey involves the coordination of alternating left and right activity in each segment. Forward swimming is achieved by a lag between the onset of activity in consecutive segments rostrocaudally along the spinal cord. The intersegmental phase lag is approximately 1% of the cycle duration per segment and is independent of the swimming frequency. Since the lamprey has approximately 100 spinal segments, at any given time one wave of activity is propagated along the body. Most previous simulations of intersegmental coordination in the lamprey have treated the cord as a chain of coupled oscillators or well-defined segments. Here a network model without segmental boundaries is described which can produce coordinated activity with a phase lag. This ‘continuous’ pattern-generating network is composed of a column of 420 excitatory interneurons (E1 to E420) and 300 inhibitory interneurons (C1 to C300) on each half of the simulated spinal cord. The interneurons are distributed evenly along the simulated spinal cord, and their connectivity is chosen to reflect the behavior of the intact animal and what is known about the length and strength of the synaptic connections. For example, E100 connects to all interneurons between E51 and E149, but at varying synaptic strengths, while E101 connects to all interneurons between E52 and E150. This unsegmented E-C network generates a motor pattern that is sampled by output elements similar to motoneurons (M cells), which are arranged along the cell column so that they receive input from seven E and five C interneurons. The M cells thus represent the summed excitatory and inhibitory input at different points along the simulated spinal cord and can be regarded as representing the ventral root output to the myotomes along the spinal cord. E and C interneurons have five simulated compartments and Hodgkin-Huxley based dynamics. The simulated network produces rhythmic output over a wide range of frequencies (1–11 Hz) with a phase lag constant over most of the length, with the exception of the ‘cut’ ends due to reduced synaptic input. As the inhibitory C interneurons in the simulation have more extensive caudal than rostral projections, the output of the simulation has positive phase lags, as occurs in forward swimming. However, unlike the biological network, phase lags in the simulation increase significantly with burst frequency, from 0.5% to 2.3% over the range of frequencies of the simulation. Local rostral or caudal increases in excitatory drive in the simulated network are sufficient to produce motor patterns with increased or decreased phase lags, respectively. Received: 15 December 1995 / Accepted in revised form: 17 September 1996     

Forward-time simulations of non-random mating populations using simuPOP

Computer simulations play an important role in studies of non-random mating populations. Because of implementation difficulties, only very limited types of non-random mating schemes are provided in the currently available simulation programs. Starting with version 0.8.5, simuPOP provides a few mating schemes that can be used to simulate arbitrary non-random mating models. This article describes the concepts and methods behind these mating schemes and demonstrates their uses in a few examples, including partial self-mating, positive assortative mating, non-random outbreeding, and simulation of overlapping generations in age-structured populations. AVAILABILITY: simuPOP is freely available at http://simupop.sourceforge.net, distributed under a GPL license. Cited examples are in the doc/cookbook directory of a simuPOP distribution.     

Solving navigational uncertainty using grid cells on robots

To successfully navigate their habitats, many mammals use a combination of two mechanisms, path integration and calibration using landmarks, which together enable them to estimate their location and orientation, or pose. In large natural environments, both these mechanisms are characterized by uncertainty: the path integration process is subject to the accumulation of error, while landmark calibration is limited by perceptual ambiguity. It remains unclear how animals form coherent spatial representations in the presence of such uncertainty. Navigation research using robots has determined that uncertainty can be effectively addressed by maintaining multiple probabilistic estimates of a robot's pose. Here we show how conjunctive grid cells in dorsocaudal medial entorhinal cortex (dMEC) may maintain multiple estimates of pose using a brain-based robot navigation system known as RatSLAM. Based both on rodent spatially-responsive cells and functional engineering principles, the cells at the core of the RatSLAM computational model have similar characteristics to rodent grid cells, which we demonstrate by replicating the seminal Moser experiments. We apply the RatSLAM model to a new experimental paradigm designed to examine the responses of a robot or animal in the presence of perceptual ambiguity. Our computational approach enables us to observe short-term population coding of multiple location hypotheses, a phenomenon which would not be easily observable in rodent recordings. We present behavioral and neural evidence demonstrating that the conjunctive grid cells maintain and propagate multiple estimates of pose, enabling the correct pose estimate to be resolved over time even without uniquely identifying cues. While recent research has focused on the grid-like firing characteristics, accuracy and representational capacity of grid cells, our results identify a possible critical and unique role for conjunctive grid cells in filtering sensory uncertainty. We anticipate our study to be a starting point for animal experiments that test navigation in perceptually ambiguous environments.     

Physiological assessment of bacteria using fluorochromes

This minireview focuses on the application of fluorogenic compounds in the detection of bacteria with particular emphasis on the assessment of physiological activity using epifluorescence microscopy. Microbiological applications of several related methods will also be reviewed.