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.     

Effect of eCG on the pregnancy rate of ewes transcervically inseminated with frozen-thawed semen outside the breeding season

An experiment was conducted to determine whether factors affecting pregnancy rate out-of-season are associated more with transcervical artificial insemination (T-AI) procedures or with the reproductive state of the ewe. Twenty Finncross ewes were treated with progesterone sponges, and at sponge removal (0 h) 10 ewes were treated with eCG. Blood samples were collected for LH and progesterone analyses, and follicular development was monitored using ultrasonography. Ewes were inseminated from 48 to 52 h with 200 million motile frozen-thawed spermatozoa. The incidence of estrus, LH surges and ovulation was greater (P < 0.01) and intervals to these responses were shorter (P < 0.01) in the eCG-treated ewes. The number of follicles > 5 mm was higher (P < 0.05) in eCG-treated than control ewes. Progesterone concentrations increased and remained elevated through Day 19 in 7 eCG-treated and in 1 control ewe, and these ewes were pregnant based upon ultrasonographic examination. The results demonstrate that the T-AI technique using frozen-thawed semen produces a relatively high (70%) pregnancy rate out-of-season. The pregnancy rate was found to reflect primarily the reproductive condition of the ewe.     

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.     

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.