Bioinformatics in crosslinking chemistry of collagen with selective cross linkers

<p>Abstract</p> <p>Background</p> <p>Identifying the molecular interactions using bioinformatics tools before venturing into wet lab studies saves the energy and time considerably. The present study summarizes, molecular interactions and binding energy calculations made for major structural protein, collagen of Type I and Type III with the chosen cross-linkers, namely, coenzyme Q₁₀, dopaquinone, embelin, embelin complex-1 & 2, idebenone, 5-O-methyl embelin, potassium embelate and vilangin.</p> <p>Results</p> <p>Molecular descriptive analyses suggest, dopaquinone, embelin, idebenone, 5-O-methyl embelin, and potassium embelate display nil violations. And results of docking analyses revealed, best affinity for Type I (- 4.74 kcal/mol) and type III (-4.94 kcal/mol) collagen was with dopaquinone.</p> <p>Conclusions</p> <p>Among the selected cross-linkers, dopaquinone, embelin, potassium embelate and 5-O-methyl embelin were the suitable cross-linkers for both Type I and Type III collagen and stabilizes the collagen at the expected level.</p

Antimycobacterial drug discovery using Mycobacteria-infected amoebae identifies anti-infectives and new molecular targets

Tuberculosis remains a serious threat to human health world-wide, and improved efficiency of medical treatment requires a better understanding of the pathogenesis and the discovery of new drugs. In the present study, we performed a whole-cell based screen in order to complete the characterization of 168 compounds from the GlaxoSmithKline TB-set. We have established and utilized novel previously unexplored host-model systems to characterize the GSK compounds, i.e. the amoeboid organisms D. discoideum and A. castellanii, as well as a microglial phagocytic cell line, BV2. We infected these host cells with Mycobacterium marinum to monitor and characterize the anti-infective activity of the compounds with quantitative fluorescence measurements and high-content microscopy. In summary, 88.1% of the compounds were confirmed as antibiotics against M. marinum, 11.3% and 4.8% displayed strong anti-infective activity in, respectively, the mammalian and protozoan infection models. Additionally, in the two systems, 13-14% of the compounds displayed pro-infective activity. Our studies underline the relevance of using evolutionarily distant pathogen and host models in order to reveal conserved mechanisms of virulence and defence, respectively, which are potential "universal" targets for intervention. Subsequent mechanism of action studies based on generation of over-expresser M. bovis BCG strains, generation of spontaneous resistant mutants and whole genome sequencing revealed four new molecular targets, including FbpA, MurC, MmpL3 and GlpK

Rab6 and Rab11 Regulate Chlamydia trachomatis Development and Golgin-84-Dependent Golgi Fragmentation

Many intracellular pathogens that replicate in special membrane bound compartments exploit cellular trafficking pathways by targeting small GTPases, including Rab proteins. Members of the Chlamydiaceae recruit a subset of Rab proteins to their inclusions, but the significance of these interactions is uncertain. Using RNA interference, we identified Rab6 and Rab11 as important regulators of Chlamydia infections. Depletion of either Rab6 or Rab11, but not the other Rab proteins tested, decreased the formation of infectious particles. We further examined the interplay between these Rab proteins and the Golgi matrix components golgin-84 and p115 with regard to Chlamydia-induced Golgi fragmentation. Silencing of the Rab proteins blocked Chlamydia-induced and golgin-84 knockdown-stimulated Golgi disruption, whereas Golgi fragmentation was unaffected in p115 depleted cells. Interestingly, p115-induced Golgi fragmentation could rescue Chlamydia propagation in Rab6 and Rab11 knockdown cells. Furthermore, transport of nutrients to Chlamydia, as monitored by BODIPY-Ceramide, was inhibited by Rab6 and Rab11 knockdown. Taken together, our results demonstrate that Rab6 and Rab11 are key regulators of Golgi stability and further support the notion that Chlamydia subverts Golgi structure to enhance its intracellular development

Downregulation of ETS Rescues Diabetes-Induced Reduction of Endothelial Progenitor Cells

Transplantation of vasculogenic progenitor cells (VPC) improves neovascularization after ischemia. However, patients with type 2 diabetes mellitus show a reduced VPC number and impaired functional activity. Previously, we demonstrated that p38 kinase inhibition prevents the negative effects of glucose on VPC number by increasing proliferation and differentiation towards the endothelial lineage in vitro. Moreover, the functional capacity of progenitor cells is reduced in a mouse model of metabolic syndrome including type 2 diabetes (Lepr(db)) in vivo.The aim of this study was to elucidate the underlying signalling mechanisms in vitro and in vivo. Therefore, we performed DNA-protein binding arrays in the bone marrow of mice with metabolic syndrome, in blood-derived progenitor cells of diabetic patients as well as in VPC ex vivo treated with high levels of glucose. The transcriptional activation of ETS transcription factors was increased in all samples analyzed. Downregulation of ETS1 expression by siRNA abrogated the reduction of VPC number induced by high-glucose treatment. In addition, we observed a concomitant suppression of the non-endothelial ETS-target genes matrix metalloproteinase 9 (MMP9) and CD115 upon short term lentiviral delivery of ETS-specific shRNAs. Long term inhibition of ETS expression by lentiviral infection increased the number of cells with the endothelial markers CD144 and CD105.These data demonstrate that diabetes leads to dysregulated activation of ETS, which blocks the functional activity of progenitor cells and their commitment towards the endothelial cell lineage

Targeting Protein-Protein Interactions for Parasite Control

Finding new drug targets for pathogenic infections would be of great utility for humanity, as there is a large need to develop new drugs to fight infections due to the developing resistance and side effects of current treatments. Current drug targets for pathogen infections involve only a single protein. However, proteins rarely act in isolation, and the majority of biological processes occur via interactions with other proteins, so protein-protein interactions (PPIs) offer a realm of unexplored potential drug targets and are thought to be the next-generation of drug targets. Parasitic worms were chosen for this study because they have deleterious effects on human health, livestock, and plants, costing society billions of dollars annually and many sequenced genomes are available. In this study, we present a computational approach that utilizes whole genomes of 6 parasitic and 1 free-living worm species and 2 hosts. The species were placed in orthologous groups, then binned in species-specific ortholgous groups. Proteins that are essential and conserved among species that span a phyla are of greatest value, as they provide foundations for developing broad-control strategies. Two PPI databases were used to find PPIs within the species specific bins. PPIs with unique helminth proteins and helminth proteins with unique features relative to the host, such as indels, were prioritized as drug targets. The PPIs were scored based on RNAi phenotype and homology to the PDB (Protein DataBank). EST data for the various life stages, GO annotation, and druggability were also taken into consideration. Several PPIs emerged from this study as potential drug targets. A few interactions were supported by co-localization of expression in M. incognita (plant parasite) and B. malayi (H. sapiens parasite), which have extremely different modes of parasitism. As more genomes of pathogens are sequenced and PPI databases expanded, this methodology will become increasingly applicable

Long-Term Effects of Autologous Bone Marrow Stem Cell Treatment in Acute Myocardial Infarction: Factors That May Influence Outcomes

AIMS: To investigate whether there are important sources of heterogeneity between the findings of different clinical trials which administer autologous stem cell treatment for acute myocardial infarction (AMI) and to evaluate what factors may influence the long-term effects of this treatment. METHODS AND RESULTS: MEDLINE (1950-January 2011), EMBASE (1974-January 2011), CENTRAL (The Cochrane Library 2011, Issue 1), CINAHL (1982-January 2011), and ongoing trials registers were searched for randomised trials of bone marrow stem cells as treatment for AMI. Hand-searching was used to screen recent, relevant conference proceedings (2005-2010/11). Meta-analyses were conducted using random-effects models and heterogeneity between subgroups was assessed using chi-squared tests. Planned analyses included length of follow-up, timing of cell infusion and dose, patient selection, small trial size effect, methodological quality, loss of follow-up and date of publication. Thirty-three trials with a total of 1,765 participants were included. There was no evidence of bias due to publication or time-lag, methodological quality of included studies, participant drop-out, duration of follow-up or date of the first disclosure of results. However, in long-term follow-ups the treatment seemed more effective when administered at doses greater than 10(8) cells and to patients with more severe heart dysfunction. CONCLUSIONS: Evaluation of heterogeneity between trials has not identified significant sources of bias in this study. However, clinical differences between trials are likely to exist which should be considered when undertaking future trials

Molecular MRI of Inflammation in Atherosclerosis

Inflammatory activity in atherosclerotic plaque is a risk factor for plaque rupture and atherothrombosis and may direct interventional therapy. Inflammatory activity can be evaluated at the (sub)cellular level using in vivo molecular MRI. This paper reviews recent progress in contrast-enhanced molecular MRI to visualize atherosclerotic plaque inflammation. Various MRI contrast agents, among others ultra-small particles of iron oxide, low-molecular-weight Gd-chelates, micelles, liposomes, and perfluorocarbon emulsions, have been used for in vivo visualization of various inflammation-related targets, such as macrophages, oxidized LDL, endothelial cell expression, plaque neovasculature, MMPs, apoptosis, and activated platelets/thrombus. An enzyme-activatable magnetic resonance contrast agent has been developed to study myeloperoxidase activity in inflamed plaques. Agents creating contrast based on the chemical exchange saturation transfer mechanism were used for thrombus imaging. Transfer of these molecular MRI techniques to the clinic will critically depend on the safety profiles of these newly developed magnetic resonance contrast agents

Identification of novel targets for breast cancer by exploring gene switches on a genome scale

<p>Abstract</p> <p>Background</p> <p>An important feature that emerges from analyzing gene regulatory networks is the "switch-like behavior" or "bistability", a dynamic feature of a particular gene to preferentially toggle between two steady-states. The state of gene switches plays pivotal roles in cell fate decision, but identifying switches has been difficult. Therefore a challenge confronting the field is to be able to systematically identify gene switches.</p> <p>Results</p> <p>We propose a top-down mining approach to exploring gene switches on a genome-scale level. Theoretical analysis, proof-of-concept examples, and experimental studies demonstrate the ability of our mining approach to identify bistable genes by sampling across a variety of different conditions. Applying the approach to human breast cancer data identified genes that show bimodality within the cancer samples, such as estrogen receptor (ER) and ERBB2, as well as genes that show bimodality between cancer and non-cancer samples, where tumor-associated calcium signal transducer 2 (TACSTD2) is uncovered. We further suggest a likely transcription factor that regulates TACSTD2.</p> <p>Conclusions</p> <p>Our mining approach demonstrates that one can capitalize on genome-wide expression profiling to capture dynamic properties of a complex network. To the best of our knowledge, this is the first attempt in applying mining approaches to explore gene switches on a genome-scale, and the identification of TACSTD2 demonstrates that single cell-level bistability can be predicted from microarray data. Experimental confirmation of the computational results suggest TACSTD2 could be a potential biomarker and attractive candidate for drug therapy against both ER+ and ER- subtypes of breast cancer, including the triple negative subtype.</p