Isolation and1H-NMR spectroscopic identification of the glucose-containing lipid-linked precursor oligosaccharide ofN-linked carbohydrate chains

The lipid-linked precursor ofN-type glycoprotein oligosaccharides was isolated from porcine thyroid microsomes after in cubation with UDP[³H] Glucose. The carbohydrate was released from dolichol pyrophosphate by mild acid hydrolysis, purified by gel filtration and characterized by 500-MHz¹H-NMR spectroscopy in combination with enzymatic degradation. The parent oligosaccharide was found to be Glc₃Man₉Glc-NAc₂. The three glucose residues are present in the linear sequence Glcα1-2Glα1-3 Glc, the latter being α(1-3)-linked to one of the mannose residues. In order to establish the branch location of the triglucosyl unit, the parent compound was digested with jack-bean α-mannosidase. The oligosaccharide product was purified by gel filtration, and identified by¹H-NMR as Glc₃Man₅GlcNAc₂ lacking the mannose residues A, D₂, B and D₃. Therefore, the structure of the precursor oligosaccharide is as follows: $$\begin{gathered} c b a D_1 C 4 \hfill \\ Glc\alpha 1 - 2Glc\alpha 1 - 3Glc\alpha 1 - 3Man\alpha 1 - 2Man\alpha 1 - 2Man\alpha 1 \hfill \\ 3 \swarrow 3 2 1 \hfill \\ Man\alpha 1 - 2Man\alpha 1 Man\beta 1 - 4GlcNAc\beta 1 - 4GlcNAc \hfill \\ D_{2 } A 3 6 \hfill \\ Man\alpha 1 \hfill \\ 6 \hfill \\ Man\alpha 1 - 2Man\alpha 1 \nwarrow 4 \hfill \\ D_3 B \hfill \\ \end{gathered} $$      

Sequential Application of Ligand and Structure Based Modeling Approaches to Index Chemicals for Their hH4R Antagonism

The human histamine H₄ receptor (hH₄R), a member of the G-protein coupled receptors (GPCR) family, is an increasingly attractive drug target. It plays a key role in many cell pathways and many hH₄R ligands are studied for the treatment of several inflammatory, allergic and autoimmune disorders, as well as for analgesic activity. Due to the challenging difficulties in the experimental elucidation of hH₄R structure, virtual screening campaigns are normally run on homology based models. However, a wealth of information about the chemical properties of GPCR ligands has also accumulated over the last few years and an appropriate combination of these ligand-based knowledge with structure-based molecular modeling studies emerges as a promising strategy for computer-assisted drug design. Here, two chemoinformatics techniques, the Intelligent Learning Engine (ILE) and Iterative Stochastic Elimination (ISE) approach, were used to index chemicals for their hH₄R bioactivity. An application of the prediction model on external test set composed of more than 160 hH₄R antagonists picked from the chEMBL database gave enrichment factor of 16.4. A virtual high throughput screening on ZINC database was carried out, picking ∼4000 chemicals highly indexed as H₄R antagonists'' candidates. Next, a series of 3D models of hH₄R were generated by molecular modeling and molecular dynamics simulations performed in fully atomistic lipid membranes. The efficacy of the hH₄R 3D models in discrimination between actives and non-actives were checked and the 3D model with the best performance was chosen for further docking studies performed on the focused library. The output of these docking studies was a consensus library of 11 highly active scored drug candidates. Our findings suggest that a sequential combination of ligand-based chemoinformatics approaches with structure-based ones has the potential to improve the success rate in discovering new biologically active GPCR drugs and increase the enrichment factors in a synergistic manner.     

Trio under threat: can we secure the future of rhinos,elephants and tigers in Malaysia?

Three of Malaysia’s endangered large mammal species are experiencing contrasting futures. Populations of the Sumatran rhino (Dicerorhinus sumatrensis) have dwindled to critically low numbers in Peninsular Malaysia (current estimates need to be revised) and the state of Sabah (less than 40 individuals estimated). In the latter region, a bold intervention involving the translocation of isolated rhinos is being developed to concentrate them into a protected area to improve reproduction success rates. For the Asian elephant (Elephas maximus), recently established baselines for Peninsular Malaysia (0.09 elephants/km² estimated from one site) and Sabah (between 0.56 and 2.15 elephants/km² estimated from four sites) seem to indicate globally significant populations based on dung count surveys. Similar surveys are required to monitor elephant population trends at these sites and to determine baselines elsewhere. The population status of the Malayan tiger (Panthera tigris jacksoni) in Peninsular Malaysia, however, remains uncertain as only a couple of scientifically defensible camera-trapping surveys (1.66 and 2.59 tigers/100 km² estimated from two sites) have been conducted to date. As conservation resources are limited, it may be prudent to focus tiger monitoring and protection efforts in priority areas identified by the National Tiger Action Plan for Malaysia. Apart from reviewing the conservation status of rhinos, elephants and tigers and threats facing them, we highlight existing and novel conservation initiatives, policies and frameworks that can help secure the long-term future of these iconic species in Malaysia.     

New vistas in GPCR 3D structure prediction

Human G-protein coupled receptors (hGPCRs) comprise the most prominent family of validated drug targets. More than 50% of approved drugs reveal their therapeutic effects by targeting this family. Accurate models would greatly facilitate the process of drug discovery and development. However, 3-D structure prediction of GPCRs remains a challenge due to limited availability of resolved structure. The X-ray structures have been solved for only four such proteins. The identity between hGPCRs and the potential templates is mostly less than 30%, well below the level at which sequence alignment can be done regularly. In this study, we analyze a large database of human G-protein coupled receptors that are members of family A in order to optimize usage of the available crystal structures for molecular modeling of hGPCRs. On the basis of our findings in this study, we propose to regard specific parts from the trans-membrane domains of the reference receptor helices as appropriate template for constructing models of other GPCRs, while other residues require other techniques for their remodeling and refinement. The proposed hypothesis in the current study has been tested by modeling human β2-adrenergic receptor based on crystal structures of bovine rhodopsin (1F88) and human A2A adenosine receptor (3EML). The results have shown some improvement in the quality of the predicted models compared to Modeller software.     

Increased expression of costimulatory markers CD134 and CD80 on interleukin-17 producing T cells in patients with systemic lupus erythematosus

Introduction  

There is growing evidence that interleukin 17 (IL-17) producing T cells are involved in the pathogenesis of systemic lupus erythematosus (SLE). Previous studies showed that increased percentages of T-cell subsets expressing the costimulatory molecules CD80 and CD134 are associated with disease activity and renal involvement in SLE. The aim of this study was to investigate the distribution and phenotypical characteristics of IL-17 producing T-cells in SLE, in particular in patients with lupus nephritis, with emphasis on the expression of CD80 and CD134.     

Reference-free detection of isolated SNPs

Detecting single nucleotide polymorphisms (SNPs) between genomes is becoming a routine task with next-generation sequencing. Generally, SNP detection methods use a reference genome. As non-model organisms are increasingly investigated, the need for reference-free methods has been amplified. Most of the existing reference-free methods have fundamental limitations: they can only call SNPs between exactly two datasets, and/or they require a prohibitive amount of computational resources. The method we propose, discoSnp, detects both heterozygous and homozygous isolated SNPs from any number of read datasets, without a reference genome, and with very low memory and time footprints (billions of reads can be analyzed with a standard desktop computer). To facilitate downstream genotyping analyses, discoSnp ranks predictions and outputs quality and coverage per allele. Compared to finding isolated SNPs using a state-of-the-art assembly and mapping approach, discoSnp requires significantly less computational resources, shows similar precision/recall values, and highly ranked predictions are less likely to be false positives. An experimental validation was conducted on an arthropod species (the tick Ixodes ricinus) on which de novo sequencing was performed. Among the predicted SNPs that were tested, 96% were successfully genotyped and truly exhibited polymorphism.