Modeling shifts in the rate and pattern of subthalamopallidal network activity during deep brain stimulation

Deep brain stimulation (DBS) of the subthlamic nucleus (STN) represents an effective treatment for medically refractory Parkinson’s disease; however, understanding of its effects on basal ganglia network activity remains limited. We constructed a computational model of the subthalamopallidal network, trained it to fit in vivo recordings from parkinsonian monkeys, and evaluated its response to STN DBS. The network model was created with synaptically connected single compartment biophysical models of STN and pallidal neurons, and stochastically defined inputs driven by cortical beta rhythms. A least mean square error training algorithm was developed to parameterize network connections and minimize error when compared to experimental spike and burst rates in the parkinsonian condition. The output of the trained network was then compared to experimental data not used in the training process. We found that reducing the influence of the cortical beta input on the model generated activity that agreed well with recordings from normal monkeys. Further, during STN DBS in the parkinsonian condition the simulations reproduced the reduction in GPi bursting found in existing experimental data. The model also provided the opportunity to greatly expand analysis of GPi bursting activity, generating three major predictions. First, its reduction was proportional to the volume of STN activated by DBS. Second, GPi bursting decreased in a stimulation frequency dependent manner, saturating at values consistent with clinically therapeutic DBS. And third, ablating STN neurons, reported to generate similar therapeutic outcomes as STN DBS, also reduced GPi bursting. Our theoretical analysis of stimulation induced network activity suggests that regularization of GPi firing is dependent on the volume of STN tissue activated and a threshold level of burst reduction may be necessary for therapeutic effect.     

Assessment of selenium bioavailability from naturally produced high-selenium soy foods in selenium-deficient rats

We assessed the bioavailability of selenium (Se) from a protein isolate and tofu (bean curd) prepared from naturally produced high-Se soybeans. The Se concentrations of the soybeans, the protein isolate and tofu were 5.2 ± 0.2, 11.4 ± 0.1 and 7.4 ± 0.1 mg/kg, respectively. Male weanling Sprague–Dawley rats were depleted of Se by feeding them a 30% Torula yeast-based diet (4.1 μg Se/kg) for 56 days, and then they were replenished with Se for an additional 50 days by feeding them the same diet containing 14, 24 or 30 μg Se/kg from the protein isolate or 13, 23 or 31 μg Se/kg from tofu, respectively. l-Selenomethionine (SeMet) was used as a reference. Selenium bioavailability was determined on the basis of the restoration of Se-dependent enzyme activities and tissue Se concentrations in Se-depleted rats, comparing those responses for the protein isolate and tofu to those for SeMet by using a slope-ratio method. Dietary supplementation with the protein isolate or tofu resulted in linear or log-linear, dose-dependent increases in glutathione peroxidase activities in blood and liver and in thioredoxin reductase activity in liver. Furthermore, supplementation with the protein isolate or tofu resulted in linear or log-linear, dose-dependent increases in the Se concentrations of plasma, liver, muscle and kidneys. These results indicated an overall bioavailability of approximately 101% for Se from the protein isolate and 94% from tofu, relative to SeMet. We conclude that Se from naturally produced high-Se soybeans is highly bioavailable in this model and that high-Se soybeans may be a good dietary source of Se.     

Biological origins of normal-chain hydrocarbons: a pathway model based on cuticular wax analyses of maize silks

Long-chain normal hydrocarbons (e.g. alkanes, alkenes and dienes) are rare biological molecules and their biosynthetic origins are obscure. Detailed analyses of the surface lipids that accumulate on maize silks have revealed that these hydrocarbons constitute a large portion (>90%) of the cuticular waxes that coat this organ, which contrasts with the situation on maize seedling leaves, where the cuticular waxes are primary alcohols and aldehydes. The normal hydrocarbons that occur on silks are part of a homologous series of alkanes, alkenes and dienes of odd-number carbon atoms, ranging between 19 and 33 in number. The alkenes and dienes consist of a homologous series, each of which has double bonds situated at defined positions of the alkyl chains: alkenes have double bonds situated at the sixth, ninth or 12th positions, and dienes have double bonds situated at the sixth and ninth, or ninth and twelfth positions. Finding a homologous series of unsaturated aldehydes and fatty acids suggests that these alkenes and dienes are biosynthesized by a series of parallel pathways of fatty-acid elongation and desaturation reactions, which are followed by sequential reduction and decarbonylation. In addition, the silk cuticular waxes contain metabolically related unsaturated long-chain methylketones, which probably arise via a decarboxylation mechanism. Finally, metabolite profiling analyses of the cuticular waxes of two maize inbred lines (B73 and Mo17), and their genetic hybrids, have provided insights into the genetic control network of these biosynthetic pathways, and that the genetic regulation of these pathways display best-parent heterotic effects.     

GO‐At : in silico prediction of gene function in Arabidopsis thaliana by combining heterogeneous data

Despite recent advances, accurate gene function prediction remains an elusive goal, with very few methods directly applicable to the plant Arabidopsis thaliana. In this study, we present GO‐At (gene ontology prediction in A. thaliana), a method that combines five data types (co‐expression, sequence, phylogenetic profile, interaction and gene neighbourhood) to predict gene function in Arabidopsis. Using a simple, yet powerful two‐step approach, GO‐At first generates a list of genes ranked in descending order of probability of functional association with the query gene. Next, a prediction score is automatically assigned to each function in this list based on the assumption that functions appearing most frequently at the top of the list are most likely to represent the function of the query gene. In this way, the second step provides an effective alternative to simply taking the ‘best hit’ from the first list, and achieves success rates of up to 79%. GO‐At is applicable across all three GO categories: molecular function, biological process and cellular component, and can assign functions at multiple levels of annotation detail. Furthermore, we demonstrate GO‐At’s ability to predict functions of uncharacterized genes by identifying ten putative golgins/Golgi‐associated proteins amongst 8219 genes of previously unknown cellular component and present independent evidence to support our predictions. A web‐based implementation of GO‐At ( http://www.bioinformatics.leeds.ac.uk/goat ) is available, providing a unique resource for plant researchers to make predictions for uncharacterized genes and predict novel functions in Arabidopsis.     

6-Phenyl-1H-imidazo[4,5-c]pyridine-4-carbonitrile as cathepsin S inhibitors

6-Phenyl-1H-imidazo[4,5-c]pyridine-4-carbonitrile analogues were identified as potent and selective cathepsin S inhibitor against both purified enzyme and in human JY cell based cellular assays. This core has a very stable thio-trapping nitrile war-head in comparison with the well reported pyrimidine-2-carbonitrile cysteine cathepsin inhibitors. Compound 47 is also very potent in in vivo mouse spleenic Lip10 accumulation assays.     

The development of benzimidazoles as selective rho kinase inhibitors

Rho Kinase (ROCK) is a serine/threonine kinase whose inhibition could prove beneficial in numerous therapeutic areas. We have developed a promising class of ATP-competitive inhibitors based upon a benzimidazole scaffold, which show excellent potency toward ROCK (IC₅₀ <10 nM). This report details the optimization of selectivity for ROCK over other related kinases such as Protein kinase A (PKA).     

Antimalarial activity of azadipeptide nitriles

Azadipeptide nitriles—novel cysteine protease inhibitors—display structure-dependent antimalarial activity against both chloroquine-sensitive and chloroquine-resistant lines of cultured Plasmodium falciparum malaria parasites. Inhibition of parasite’s hemoglobin-degrading cysteine proteases was also investigated, revealing the azadipeptide nitriles as potent inhibitors of falcipain-2 and -3. A correlation between the cysteine protease-inhibiting activity and the antimalarial potential of the compounds was observed. These first generation azadipeptide nitriles represent a promising new class of compounds for antimalarial drug development.     

Interaction of aminoadamantane derivatives with the influenza A virus M2 channel-Docking using a pore blocking model

Interaction of aminoadamantanes with the influenza A virus M2 proton channel was analyzed by docking simulations of a series of synthetic aminoadamantane derivatives, of differing binding affinity, into the crystal structure of the transmembrane (M2TM) pore. The pore blocking model tested in the ‘gas phase’ describes qualitatively the changes on the relative binding affinities of the compounds (although a series of highly hydrophobic ligands which seem to have little capacity for different specific interactions with their receptor). The docking calculations predicted poses in which the adamantane ring is surrounded mainly by the alkyl side chains of Val27 or Ala30 and the ligand’s amino group is generally hydrogen bonded with hydroxyls of Ser31 or carbonyls of Val27 or carbonyls of Ala30, the former (Ser31) being the most stable and most frequently observed. The binding of the ligand is a compromise between hydrogen bonding ability, which is elevated by a primary amino group, and apolar interactions, which are increased by the ability of the lipophilic moiety to adequately fill a hydrophobic pocket within the M2TM pore. A delicate balance of these hydrophobic contributions is required for optimal interaction.     

A comparative analysis of the fluorescence properties of the wild-type and active site mutants of the hepatitis C virus autoprotease NS2-3

Hepatitis C virus encodes an autoprotease, NS2-3, which is required for processing of the viral polyprotein between the non-structural NS2 and NS3 proteins. This protease activity is vital for the replication and assembly of the virus and therefore represents a target for the development of anti-viral drugs. The mechanism of this auto-processing reaction is not yet clear but the protease activity has been shown to map to the C-terminal region of NS2 and the N-terminal serine protease region of NS3. The NS2-3 precursor can be expressed in Escherichia coli as inclusion bodies, purified as denatured protein and refolded, in the presence of detergents and the divalent metal ion zinc, into an active form capable of auto-cleavage. Here, intrinsic tryptophan fluorescence has been used to assess refolding in the wild-type protein and specific active site mutants. We also investigate the effects on protein folding of alterations to the reaction conditions that have been shown to prevent auto-cleavage. Our data demonstrate that these active site mutations do not solely affect the cleavage activity of the HCV NS2-3 protease but significantly affect the integrity of the global protein fold.     

Modulation of cellulosome composition in Clostridium cellulolyticum: Adaptation to the polysaccharide environment revealed by proteomic and carbohydrate‐active enzyme analyses

Clostridium cellulolyticum is a model mesophilic anaerobic bacterium that efficiently degrades plant cell walls. The recent genome release offers the opportunity to analyse its complete degradation system. A total of 148 putative carbohydrate‐active enzymes were identified, and their modular structures and activities were predicted. Among them, 62 dockerin‐containing proteins bear catalytic modules from numerous carbohydrate‐active enzymes' families and whose diversity reflects the chemical and structural complexity of the plant carbohydrate. The composition of the cellulosomes produced by C. cellulolyticum upon growth on different substrates (cellulose, xylan, and wheat straw) was investigated by LC MS/MS. The majority of the proteins encoded by the cip‐cel operon, essential for cellulose degradation, were detected in all cellulosome preparations. In the presence of wheat straw, the natural and most complex of the substrates studied, additional proteins predicted to be involved in hemicellulose degradation were produced. A 32‐kb gene cluster encodes the majority of these proteins, all harbouring carbohydrate‐binding module 6 or carbohydrate‐binding module 22 xylan‐binding modules along dockerins. This newly identified xyl‐doc gene cluster, specialised in hemicellulose degradation, comes in addition of the cip‐cel operon for plant cell wall degradation. Hydrolysis efficiencies determined on the different substrates corroborates the finding that cellulosome composition is adapted to the growth substrate.