Molecular modelling of a psychrophilic β-galactosidase

An Antarctic strain of bacteria was isolated from the digestive tract of the crustacean Thysanoessa macrura and classified as Pseudoalteromonas sp. 22b based on 16SrRNA gene sequence and physiological as well as biochemical properties. This bacterium turned out to be a good producer of a cold-adapted β-galactosidase. The enzyme displays high catalytic and molecular adaptation to low temperatures. Here we present a homology model of the psychrophilic β-galactosidase based on the structural template of the mesophilic β-galactosidase from Escherichia coli (PDB code: 1JZ7, resolution 1.5 Å). Our aim was to identify and characterize potential cold-adaptational features of the target psychrophilic β-galactosidase at the level of the three-dimensional structure rather than solely from the analysis of the amino acid sequence. We report the results of comparisons between the psychrophilic and mesophilic β-galactosidases and point out similarities and differences in the catalytic site and in other parts of the structure. The model allowed us to pinpoint a number of characteristics that are frequently observed in psychrophilic enzymes and allowed interpretation of the results of immunochemical and biochemical analyses.     

Molecular modelling of phthalates – PPARs interactions

Di(2-ethylhexyl) phthalate (DEHP) is the most widely plasticizer for polyvinyl chloride (PVC) that is used in plastic tubes, in medical and paramedical devices as well as in food storage packaging. The toxicological profile of DEHP has been evaluated in a number of experimental animal models and has been extensively documented. Its toxicity is in part linked to the activation of the peroxisome proliferator-activated receptor α (PPAR_α). As a response, an intensive research for a new, biologically inert plasticizer has been initiated. Among the alternative studied, tri(2-ethylhexyl) trimellitate (TEHTM) or trioctyl trimellitate (TOTM) has attracted increasing interest. However, very little information is available on their biological effects. We proceeded to dock TOTM, DEHP and its metabolites in order to identify compounds that are likely to interact with PPAR_α and PPAR_γ binding sites. The results obtained hint that TOTM is not able to bind to PPARs and should therefore be safer than DEHP.     

Experience of experimental modelling of Huntington’s disease

Huntington’s disease (HD) is an autosomal dominant neurodegenerative disorder characterized by choreic involuntary movements, decline in cognitive functions, behavioral disturbances, and progressive neuronal death affecting primarily the striatum. The fatal nature of HD makes it important to search for new effective methods of its treatment, which requires the development of experimental models of the disease. These models can be created using 3-nitropropionic acid (3-NPA), which is a neurotoxin causing typical changes in motor skills and memory impairment in animals due to induction of oxidative stress, impaired glutathione defense, and destruction of striatal cells. We modeled HD in rats by chronic daily intraperitoneal administration of 3-NPA for 17 days. Systemic administration of a low dose of 3-NPA (10 mg/kg) induced hyperactivity of animals in the open field test (including movement redundancy as a hyperkinesia analogue) and had no effect on the behavior of the animals in the X-maze test. On the contrary, rats administered with a toxic dose of 3-NPA (20 mg/kg) exhibited a significant decrease in their motor activity and a cognitive decline in behavioral tests. A histopathological analysis revealed damage and loss of neurons and a decrease in expression of dopaminergic markers (tyrosine hydroxylase and plasma membrane dopamine transporter) in the striatum. The gliotoxic effect of 3-NPA was also found in the striatum, which was confirmed by immunohistochemical staining for astrocytic proteins: GFAP, glutamine synthetase, and aquaporin-4. This HD model may be helpful for testing new experimental therapies at different stages of HD-like neurodegeneration, including therapies based on cell neurotransplantation.     

A functional�Cstructural modelling approach to autoregulation of nodulation

Background and Aims

Autoregulation of nodulation is a long-distance shoot–root signalling regulatory system that regulates nodule meristem proliferation in legume plants. However, due to the intricacy and subtleness of the signalling nature in plants, molecular and biochemical details underlying mechanisms of autoregulation of nodulation remain largely unknown. The purpose of this study is to use functional–structural plant modelling to investigate the complexity of this signalling system. There are two major challenges to be met: modelling the 3D architecture of legume roots with nodulation and co-ordinating signalling-developmental processes with various rates.

Methods

Soybean (Glycine max) was chosen as the target legume. Its root system was observed to capture lateral root branching and nodule distribution patterns. L-studio, a software tool supporting context-sensitive L-system modelling, was used for the construction of the architectural model and integration with the internal signalling.

Key Results

A branching pattern with regular radial angles was found between soybean lateral roots, from which a root mapping method was developed to characterize the laterals. Nodules were mapped based on ‘nodulation section’ to reveal nodule distribution. A root elongation algorithm was then developed for simulation of root development. Based on the use of standard sub-modules, a synchronization algorithm was developed to co-ordinate multi-rate signalling and developmental processes.

Conclusions

The modelling methods developed here not only allow recreation of legume root architecture with lateral branching and nodulation details, but also enable parameterization of internal signalling to produce different regulation results. This provides the basis for using virtual experiments to help in investigating the signalling mechanisms at work.     

Mathematical modelling — a management tool for aquatic ecosystems?

Mathematical modelling may serve as a rational and powerful tool in the management of complex ecosystems. However, ecosystem models are drastic simplifications of the real world. As a rule they are based on a rather incomplete and scattered knowledge of the system in question. Furthermore, ecological systems and in particular marine systems are characterised by a high degree of complexity, spatial and functional heterogeneity, nonlinearity, complex behavioural features such as adptation and self-organisation, and a considerable stochastic element. Nevertheless, if management is to be based on predictions from mathematical models — and it has to be based on some kind of model in at least a broad sense — we need an estimate of prediction accuracy in terms of the management variables and constraints. One possible approach to model uncertainty is a probabilistic interpretation of model predictions, generated by use of Monte-Carlo techniques. Fuzzy data sets and ranges are used. The resulting model response allows the derivation of measures for model credibility. Probability distributions can be computed for certain system states under (un)certain input conditions, representing the effects of insufficient data and structural uncertainty on model-based predictions. Such analysis indicates that prediction uncertainty increases, not only with the uncertainty in the data, but also with increasing distance from the empirical conditions, and with time. Present ecoystem models can be a tool for qualitative discrimination between different management alternatives, rather than a credible means for detailed quantitative predictions of system response to a wide range of input conditions.     

Individual-based modelling in ecology: what makes the difference?

Is individual-based modelling really a new approach in ecology? A large part of the uncertainty surrounding this question is a consequence of imprecisely delimited boundaries between classical and individual-based modelling. Genuine 'individual-based' models describe a population made up of individuals that may differ from one another; they also describe changes in numbers of individuals rather than in the population density, and take resource dynamics explicitly into account. Individual-based models that fulfil these criteria will not characterize ecological systems as 'stable' systems in their ideal form, with equilibrium states represented by points in the phase space.     

Light distribution in a novel photobioreactor – modelling for optimization

The paper reports a novel photobioreactor developed to achievehomogeneous and flexible illumination inside the reactor. This is toovercome the problem of studying kinetics in standard photobioreactors,which are characterized by strong light gradients and light fluxes that cannotbe controlled. The reactor is used for the study of microalgal kinetics formodelling purposes.The new reactor combines the advantages of a stirred reactor(homogeneity) and a plate reactor (short path length). The light inputsystem consists of an external light source, a fibre-optical ring-light and alight emitting tube. Light is generated in a light source arranged externallyand directed into the reactor using optical fibres. The fibres are spread ina ring-light to provide a uniform illumination in the concentrically arrangedcylinder. Any focusable light source can be applied; by using a shuttermodule, light fluctuations can be generated in a wide range of frequencies.In order to change the light quality, spectral filters are placed between thelamp and the optical fibre.A model based approach was used to optimize the illumination: lightdistribution was calculated employing a Monte-Carlo simulation. Lightemission characteristics, reflection, refraction, scattering in the suspensionand on rough surfaces were studied numerically. Propositions were derivedhow to optimize the reactor, e.g. now to achieve higher light intensities anda more uniform illumination. Finally, mean photon flux densities of 100± 15 mol m^-1 s^-1 were achieved at theilluminated surface.The simulation results revealed that the light distribution at constantbiomass concentration is mainly determined by the geometrical parametersof the lightening device mentioned above and that any simplifications leadto serious misinterpretations.     

Plankton functional type modelling: running before we can walk?

Biogeochemical cycling in marine systems is intimately linkedto the activity of specific plankton functional types (PFTs)such as diatoms, coccolithophores and nitrogen fixers, therebyproviding a focus for contemporary modelling studies. Incorporatingextra complexity beyond simple nutrient-phytoplankton-zooplankton-detritus(NPZD) models is, however, fraught with difficulties: poorlyunderstood ecology; lack of data; aggregating diversity withinfunctional groups into meaningful state variables and constants;sensitivity of output to the parameterizations in question andtheir physical and chemical environment. Although regional modelsaddressing the seasonal succession of plankton types have achievedsome degree of success, predicted distributions of PFTs in globalbiogeochemical models have thus far been less than convincing.While the continued articulation of detail in ecosystem modelsis surely the way forward, I argue that this can only be sowith due care and attention to the formulations employed anda healthy dose of scepticism regarding model outcomes. Futuredirections should emphasize building up complexity gradually,objective assessment of the resulting parameterizations, andvariety in approach such as the use of empirical alternativesto the fully dynamic representation of PFTs in models. Written responses to this article should be submitted to RogerHarris at rph{at}pml.ac.uk within two months of publication. Forfurther information, please see the Editorial ‘Horizons’in Journal of Plankton Research, Volume 26, Number 3, Page 257.     

Molecular modelling studies of new potential human DNA polymerase α inhibitors

The human polymerase α (pol α) is a promising target for the therapy of cancer e.g. of the skin. The authors recently built a homology model of the active site of human DNA pol α. This 3D model was now used for molecular modelling studies with eight novel analogues of 2-butylanilino-dATP, which is a highly selective nucleoside inhibitor of mammalian pol α. Our results suggest that a higher hydrophobicity of a carbohydrate side chain (pointing into a spacious hydrophobic cavity) may enhance the strength of the interaction with the target protein. Moreover, acyclic acyclovir-like derivatives outperformed those with a sugar-moiety, indicating that structural flexibility and higher conformational adaptability has a positive effect on the receptor affinity. Cytotoxicity tests confirmed our theoretical findings. Besides, one of our most promising compounds in the molecular modelling studies revealed high selectivity for the SCC-25 cell line derived from squamous cell carcinoma in man.     

Where is positional uncertainty a problem for species distribution modelling?

Species data held in museum and herbaria, survey data and opportunistically observed data are a substantial information resource. A key challenge in using these data is the uncertainty about where an observation is located. This is important when the data are used for species distribution modelling (SDM), because the coordinates are used to extract the environmental variables and thus, positional error may lead to inaccurate estimation of the species–environment relationship. The magnitude of this effect is related to the level of spatial autocorrelation in the environmental variables. Using local spatial association can be relevant because it can lead to the identification of the specific occurrence records that cause the largest drop in SDM accuracy. Therefore, in this study, we tested whether the SDM predictions are more affected by positional uncertainty originating from locations that have lower local spatial association in their predictors. We performed this experiment for Spain and the Netherlands, using simulated datasets derived from well known species distribution models (SDMs). We used the K statistic to quantify the local spatial association in the predictors at each species occurrence location. A probabilistic approach using Monte Carlo simulations was employed to introduce the error in the species locations. The results revealed that positional uncertainty in species occurrence data at locations with low local spatial association in predictors reduced the prediction accuracy of the SDMs. We propose that local spatial association is a way to identify the species occurrence records that require treatment for positional uncertainty. We also developed and present a tool in the R environment to target observations that are likely to create error in the output from SDMs as a result of positional uncertainty.     

Molecular modelling studies of new potential human DNA polymerase α inhibitors

The human polymerase α (pol α) is a promising target for the therapy of cancer e.g. of the skin. The authors recently built a homology model of the active site of human DNA pol α. This 3D model was now used for molecular modelling studies with eight novel analogues of 2-butylanilino-dATP, which is a highly selective nucleoside inhibitor of mammalian pol α. Our results suggest that a higher hydrophobicity of a carbohydrate side chain (pointing into a spacious hydrophobic cavity) may enhance the strength of the interaction with the target protein. Moreover, acyclic acyclovir-like derivatives outperformed those with a sugar-moiety, indicating that structural flexibility and higher conformational adaptability has a positive effect on the receptor affinity. Cytotoxicity tests confirmed our theoretical findings. Besides, one of our most promising compounds in the molecular modelling studies revealed high selectivity for the SCC-25 cell line derived from squamous cell carcinoma in man.