Inte:Ligand (Austria)

The increasing loads in distribution grids lead to higher currents. To measure these, the transformation ratio of the current transformers (CTs) needs to be increased. This can be done by replacing the existing CTs with new ones or by changing the transformation ratio of the existing CTs to a higher ratio. The second option comes with less costs but with a higher measurement error. One of the sub-grids that is affected has an isolated start point. To detect the earth fault direction, the protection devices currently use the earth fault current 3I0 by summing up the three secondary phase currents in Holmgreen formation. The motivation of this paper is to find out whether the accuracy of the existing CTs with higher transformation ratio is still enough to reliably detect the earth fault direction. To do so, three different measurement setups were compared: 3 conventional CTs (CCT) in Holmgreen connection, a cable-type CT (CA), and a calibrated cable-type CT (CCA) as reference. With a specific test setup, it was possible to inject realistic primary currents from a network calculation into the different CT configurations. After analysing the measurement data, it was possible to confirm that using existing CTs with a higher transformation ratio is still sufficient.

ABSTRACTHerein we report the in silico discovery of 13 novel micromolar potent inhibitors of the SARS‐CoV‐2 NSP13 helicase validated in cellular antiviral and biophysical ThermoFluor assays. The compounds, discovered using a novel fragment‐based pharmacophore virtual screening workflow named FragmentScout, enable the advancement of novel antiviral agents. FragmentScout uses publicly accessible structural data of the SARS‐CoV‐2 NSP13 helicase, which was previously generated at the Diamond LightSource by XChem high‐throughput crystallographic fragment screening. The workflow generates a joint pharmacophore query for each binding site, thereby aggregating the pharmacophore feature information present in each experimental fragment pose. The joint pharmacophore query is then used to search 3D conformational databases using the Inte:ligand LigandScout XT software. The FragmentScout in silico workflow offers a novel tool for identifying micromolar hits from millimolar fragments in fragment‐based lead discovery. It is anticipated that this workflow will enhance systematic data mining of the growing collection of XChem datasets.

GABAA receptors, members of the pentameric ligand-gated ion channel superfamily, are widely expressed in the central nervous system and mediate a broad range of pharmaco-toxicological effects including bidirectional changes to seizure threshold. Thus, detection of GABAA receptor-mediated seizure liabilities is a big, partly unmet need in early preclinical drug development. This is in part due to the plethora of allosteric binding sites that are present on different subtypes of GABAA receptors and the critical lack of screening methods that detect interactions with any of these sites. To improve in silico screening methods, we assembled an inventory of allosteric binding sites based on structural data. Pharmacophore models representing several of the binding sites were constructed. These models from the NeuroDeRisk IL Profiler were used for in silico screening of a compiled collection of drugs with known GABAA receptor interactions to generate testable hypotheses. Amoxapine was one of the hits identified and subjected to an array of in vitro assays to examine molecular and cellular effects on neuronal excitability and in vivo locomotor pattern changes in zebrafish larvae. An additional level of analysis for our compound collection is provided by pharmacovigilance alerts using FAERS data. Inspired by the Adverse Outcome Pathway framework, we postulate several candidate pathways leading from specific binding sites to acute seizure induction. The whole workflow can be utilized for any compound collection and should inform about GABAA receptor-mediated seizure risks more comprehensively compared to standard displacement screens, as it rests chiefly on functional data.

Body weight and fat are major performance variables in many sports. Extreme weight reduction can lead to severe medical problems. Accurate body composition measurements are fundamental for both medical and performance optimization. Relative body weight in terms of mass index (MI1 = 0.53 M/(hs)), and in terms of body mass index (BMI = M/h2) were determined (h:stature, s:sitting height, M:body mass). Subcutaneous adipose tissue (SAT) was measured using a recently standardized ultrasound (US) method. US thickness sums from eight body sites were measured in 26 female and 35 male judokas of various weight classes. Comparisons of US and skinfold results indicate that the latter can be severely misleading in competitive judokas. Mean MI1 of females was 22.8 kg m−2 (BMI:22.9 kg m−2), males: 26.7 kg m−2 (BMI:26.5 kg m−2), but individual differences MI1‐BMI were larger than 0.5 kg m−2 in 13 and larger than 1.0 kg m−2 in three cases. Medians of SAT thickness sums DI were three‐times higher in females (66.1 mm) than in males (21.8 mm), and the fat patterning differed significantly. Females had 8.6% (median) fibrous structures embedded in SAT, and males 20.2%. Both MI and BMI were not correlated with SAT. Mean pre‐competition weight loss was 4.3% (ie, 3.0 kg), and maximum was 9.2% (7.4 kg), indicating that modifications of weigh‐in procedures are urgently needed. DI‐values mirror the athletes' potential to reduce ballast fat instead of short‐term weight reduction by dehydration; however, weight loss and SAT measured some weeks before the competitions were not correlated. Further, US measurements and medical longitudinal observations are required for discussing the large individual variations and possible fat minimum demands.

Parallel Screening has been introduced as an in silico method to predict the potential biological activities of compounds by screening them with a multitude of pharmacophore models. This study presents an early application example employing a Pipeline Pilot-based screening platform for automatic large-scale virtual activity profiling. An extensive set of HIV protease inhibitor pharmacophore models was used to screen a selection of active and inactive compounds. Furthermore, we aimed to address the usually critically eyed point, whether it is possible in a parallel screening system to differentiate between similar molecules/molecules acting on closely related proteins, and therefore we incorporated a collection of other protease inhibitors including aspartic protease inhibitors. The results of the screening experiments show a clear trend toward most extensive retrieval of known active ligands, followed by the general protease inhibitors and lowest recovery of inactive compounds.