Communication pathways from the anti-codon region to the aminoacylation site in Methionyl tRNA Synthetase: Molecular dynamics simulations and the structure network analysis

The enzymes of the family of tRNA synthetases perform their functions with high precision by synchronously recognizing the anticodon region and the aminoacylation region, which are separated by ?70 in space. This precision in function is brought about by establishing good communication paths between the two regions. We have modeled the structure of the complex consisting of Escherichia coli methionyl-tRNA synthetase (MetRS), tRNA, and the activated methionine. Molecular dynamics simulations have been performed on the modeled structure to obtain the equilibrated structure of the complex and the cross-correlations between the residues in MetRS have been evaluated. Furthermore, the network analysis on these simulated structures has been carried out to elucidate the paths of communication between the activation site and the anticodon recognition site. This study has provided the detailed paths of communication, which are consistent with experimental results. Similar studies also have been carried out on the complexes (MetRS + activated methonine) and (MetRS + tRNA) along with ligand-free native enzyme. A comparison of the paths derived from the four simulations clearly has shown that the communication path is strongly correlated and unique to the enzyme complex, which is bound to both the tRNA and the activated methionine. The details of the method of our investigation and the biological implications of the results are presented in this article. The method developed here also could be used to investigate any protein system where the function takes place through long-distance communication.

targetTB: A target identification pipeline for Mycobacterium tuberculosis through an interactome, reactome and genome-scale structural analysis

Background: Tuberculosis still remains one of the largest killer infectious diseases, warranting the identification of newer targets and drugs. Identification and validation of appropriate targets for designing drugs are critical steps in drug discovery, which are at present major bottle-necks. A majority of drugs in current clinical use for many diseases have been designed without the knowledge of the targets, perhaps because standard methodologies to identify such targets in a high-throughput fashion do not really exist. With different kinds of 'omics' data that are now available, computational approaches can be powerful means of obtaining short-lists of possible targets for further experimental validation. Results: We report a comprehensive in silico target identification pipeline, targetTB, for Mycobacterium tuberculosis. The pipeline incorporates a network analysis of the protein-protein interactome, a flux balance analysis of the reactome, experimentally derived phenotype essentiality data, sequence analyses and a structural assessment of targetability, using novel algorithms recently developed by us. Using flux balance analysis and network analysis, proteins critical for survival of M. tuberculosis are first identified, followed by comparative genomics with the host, finally incorporating a novel structural analysis of the binding sites to assess the feasibility of a protein as a target. Further analyses include correlation with expression data and non-similarity to gut flora proteins as well as 'anti-targets' in the host, leading to the identification of 451 high-confidence targets. Through phylogenetic profiling against 228 pathogen genomes, shortlisted targets have been further explored to identify broad-spectrum antibiotic targets, while also identifying those specific to tuberculosis. Targets that address mycobacterial persistence and drug resistance mechanisms are also analysed. Conclusion: The pipeline developed provides rational schema for drug target identification that are likely to have high rates of success, which is expected to save enormous amounts of money, resources and time in the drug discovery process. A thorough comparison with previously suggested targets in the literature demonstrates the usefulness of the integrated approach used in our study, highlighting the importance of systems-level analyses in particular. The method has the potential to be used as a general strategy for target identification and validation and hence significantly impact most drug discovery programmes.

The gasification of wood-char spheres in CO2---N2 mixtures: analysis and experiments

The gasification of charcoal spheres in an atmosphere of carbon-dioxide-nitrogen mixture involving diffusion and reactions in the pores is modelled and the results are compared with experiments of Standish and Tanjung and those performed in the laboratory on wood-char spheres to determine the effects of diameter, density, gas composition and flow. The results indicate that the conversion time, t(c) approximately d1.03 for large particles (> 5 mm), departing substantially from the t(c) approximately d2 law valid for diffusion limited conditions. The computational studies indicate that the kinetic limit for the particle is below 100 mum. The conversion time varies inversely as the initial char density as expected in the model. Predictions from the model show that there is no significant change in conversion time up to 60% N2 consistent with the CO2-N2 experiments. The variation of diameter and density with time are predicted. The peculiar dependence of conversion time on flow velocity in the experiments is sought to be explained by opposing free and forced convection heat transfer and the attempt is only partly successful. The studies also indicate that the dependence on the CO concentration with low CO2 is significant, indicating the need for multistep reaction mechanism against the generally accepted single-step reaction.

Analysis of natural cis- and trans-polyisoprene mixtures by near-infrared spectrophotometry

Natural trans- and cis-polyisoprenes and mixtures of these polymers were analysed by near-infrared spectrophotometry. The relative absorptivity data versus the amount of isomers in synthetic mixtures showed a non-linear behaviour. The results are compared with literature data from polyisoprenes extracted from other vegetal species. (C) 2000 Elsevier B.V. Ltd. All rights reserved.

Immunological responses and cytokine gene expression analysis to Cooperia punctata infections in resistant and susceptible Nelore cattle

Cellular and humoral immune response, as well as cytokine gene expression, was assessed in Nelore cattle with different degrees of resistance to Cooperia punctata natural infection. One hundred cattle (male, weaned, 11-12 months old), kept together on pasture, were evaluated. Faecal and blood samples were collected for parasitological and immunological assays. Based on nematode faecal egg counts (FEC) and worm burden, the seven most resistant and the eight most susceptible animals were selected. Tissue samples of the small intestine were collected for histological quantification of inflammatory cells and analysis of cytokine gene expression (IL-2, IL-4, IL-8, IL-1 2p35, IL-13, TNF-alpha, IFN-gamma, MCP-1, MCP-2, and MUC- 1) using real-time RT-PCR. Mucus samples were also collected for IgA levels determination. Serum IgG1 mean levels against C. punctata antigens were higher in the resistant group, but significant differences between groups were only observed 14 days after the beginning of the experiment against infective larvae (1-3) and 14 and 84 days against adult antigens. The resistant group also presented higher IgA levels against C. punctata (L3 and adult) antigens with significant difference 14 days after the beginning of the trial (P < 0.05). In the small-intestine mucosa, levels of IgA anti-L3 and anti-adult C. punctata were higher in the resistant group, compared with the susceptible group (P < 0.05). Gene expression of both T(H)2 cytokines (IL-4 and IL-13) in the resistant group and T(H)1 cytokines (IL-2, IL-1 2p35, IFN-gamma and MCP-1) in the susceptible group was up-regulated. Such results suggested that immune response to C. punctata was probably mediated by TH2 cytokines in the resistant group and by T(H)1 cytokines in the susceptible group. (C) 2008 Elsevier B.V. All rights reserved.

An immunocytochemical and in situ hybridization analysis of annexin 1 expression in rat mast cells: Modulation by inflammation and dexamethasone

The presence and localization of the anti-inflammatory protein annexin 1 (also known as lipocortin 1) in perivenular rat mast cells was investigated here. Using the rat mesenteric microvascular bed and a combination of morphologic techniques ranging from immunofluorescence to electron microscopy analyses, we detected the presence of annexin 1 in discrete intracellular sites, both in the nucleus and in the cytoplasm. In resting mast cells, most of the protein pool (approximately 80% of the cytosolic portion) was localized to cytoplasmic granules. In agreement with other cell types, treatment of rats with dexamethasone (0.2 mg/kg, ip) increased annexin 1 expression in mast cells, inducing a remarkable appearance of dusters of protein immunoreactivity. This effect was most likely the result of de novo protein synthesis as determined by an increase in mRNA seen by in situ hybridization. Triggering an ongoing experimental inflammatory response (0.3 mg of carrageenin, ip) increased annexin 1 mRNA and protein levels. In conclusion, we report for the first time the localization of annexin 1 in connective tissue mast cells, and its susceptibility not only to glucocorticoid hormone treatment, but also to an experimental acute inflammatory response.

Ureasil-polyether hybrid blend with tuneable hydrophilic/hydrophobic features based on U-PEO1900 and U-PPO400 mixtures

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

Crystallization and preliminary X-ray analysis of a Kunitz-type inhibitor, textilinin-1 from Pseudonaja textilis textilis

Textilinin-1 (Txln-1), a Kunitz-type serine protease inhibitor, is a 59-amino-acid polypeptide isolated from the venom of the Australian Common Brown snake Pseudonaja textilis textilis. This molecule has been suggested as an alternative to aprotinin, also a Kunitz-type serine protease inhibitor, for use as an anti-bleeding agent in surgical procedures. Txln-1 shares only 47% amino-acid identity to aprotinin; however, six cysteine residues in the two peptides are in conserved locations. It is therefore expected that the overall fold of these molecules is similar but that they have contrasting surface features. Here, the crystallization of recombinant textilinin-1 (rTxln-1) as the free molecule and in complex with bovine trypsin (229 amino acids) is reported. Two organic solvents, phenol and 1,4-butanediol, were used as additives to facilitate the crystallization of free rTxln-1. Crystals of the rTxln-1-bovine trypsin complex diffracted to 2.0 angstrom resolution, while crystals of free rTxln-1 diffracted to 1.63 angstrom resolution.

Age-Dependent Fragility and Life-Cycle Cost Analysis of Timber and Steel Distribution Poles Subjected to Hurricanes

Power distribution systems are susceptible to extreme damage from natural hazards especially hurricanes. Hurricane winds can knock down distribution poles thereby causing damage to the system and power outages which can result in millions of dollars in lost revenue and restoration costs. Timber has been the dominant material used to support overhead lines in distribution systems. Recently however, utility companies have been searching for a cost-effective alternative to timber poles due to environmental concerns, durability, high cost of maintenance and need for improved aesthetics. Steel has emerged as a viable alternative to timber due to its advantages such as relatively lower maintenance cost, light weight, consistent performance, and invulnerability to wood-pecker attacks. Both timber and steel poles are prone to deterioration over time due to decay in the timber and corrosion of the steel. This research proposes a framework for conducting fragility analysis of timber and steel poles subjected to hurricane winds considering deterioration of the poles over time. Monte Carlo simulation was used to develop the fragility curves considering uncertainties in strength, geometry and wind loads. A framework for life-cycle cost analysis is also proposed to compare the steel and timber poles. The results show that steel poles can have superior reliability and lower life-cycle cost compared to timber poles, which makes them suitable substitutes.

Limits of Visual Detection for Finasteride Polymorphs in Prepared Binary Mixtures: Analysis by X-ray Powder Diffraction

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)