The autoimmune disease-associated SNP rs917997 of IL18RAP controls IFNγ production by PBMC

AbstractType 1 Diabetes (T1D) is an autoimmune disorder characterized by aberrant T cell responses. Innate immune activation defects may facilitate a T helper 1 (Th1) phenotype. The cytokine IL-18 synergizes with IL-12 to induce IFNγ production and Th1 differentiation. The IL-18R subunit (IL18RAP) SNP rs917997 has been linked to decreased IL18RAP gene expression. Prior reports link rs917997 allele A with protection from T1D, and conversely with susceptibility to Celiac disease. However, few studies have investigated the IL-18 pathway in T1D. In this study, we analyzed responsiveness to IL-18 in T1D, and the effect of rs917997 genotype on IL18RAP gene expression post-activation. Upon IL-12 and IL-18 treatment, peripheral blood mononuclear cells from subjects carrying susceptibility alleles at rs917997 produced higher levels of IFNγ than those with protective genotypes. Additionally, the SNP modified IL18RAP surface protein expression by NK cells and gene expression in activated T cells. Taken together, these data suggest that the disease-associated rs917997 allele G permits hyperresponsiveness to IL-18, providing a novel target for therapeutic intervention in T1D

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Structural Insights into the Activation of Human Relaxin Family Peptide Receptor 1 by Small-Molecule Agonists

The GPCR relaxin family peptide receptor 1 (RXFP1) mediates the action of relaxin peptide hormone, including its tissue remodeling and antifibrotic effects. The peptide has a short half-life in plasma, limiting its therapeutic utility. However, small-molecule agonists of human RXFP1 can overcome this limitation and may provide a useful therapeutic approach, especially for chronic diseases such as heart failure and fibrosis. The first small-molecule agonists of RXFP1 were recently identified from a high-throughput screening, using a homogeneous cell-based cAMP assay. Optimization of the hit compounds resulted in a series of highly potent and RXFP1 selective agonists with low cytotoxicity, and excellent <i>in vitro</i> ADME and pharmacokinetic properties. Here, we undertook extensive site-directed mutagenesis studies in combination with computational modeling analysis to probe the molecular basis of the small-molecule binding to RXFP1. The results showed that the agonists bind to an allosteric site of RXFP1 in a manner that closely interacts with the seventh transmembrane domain (TM7) and the third extracellular loop (ECL3). Several residues were determined to play an important role in the agonist binding and receptor activation, including a hydrophobic region at TM7 consisting of W664, F668, and L670. The G659/T660 motif within ECL3 is crucial to the observed species selectivity of the agonists for RXFP1. The receptor binding and activation effects by the small molecule ML290 were compared with the cognate ligand, relaxin, providing valuable insights on the structural basis and molecular mechanism of receptor activation and selectivity for RXFP1

Advancement in remote sensing of wind energy

Azad, M ORCiD: 0000-0001-8258-6057In modern applications, wind turbines are gaining in height and becoming larger in size, as well as being installed in complex, mountainous, and hilly terrain to produce large amounts of energy for neighboring populations and industries. However, one must keep in mind that the efficiency of a wind farm is greatly affected by inaccurate wind resource assessment. Therefore, it is necessary to investigate wind resource potential to estimate how much energy is available at the site and how much power the wind turbine can produce, because the power output of a wind turbine scales cubically with the available wind speed. In this case, to achieve the highest possible efficiency from a wind farm and to install modern machines of even larger heights, it becomes necessary to study and precisely estimate wind resource potential and its economic feasibility. The investigation of wind resource at larger heights and at complex wind farms requires a more physical volume-based measurement. Ground-based remote-sensing techniques such as light detection and ranging and sound detection and ranging are becoming increasingly useful and popular in the wind energy sector for resource assessment as they help in reducing complexity, uncertainty, and technicality in modern wind farm development, because they provide volume measurement and measure the entire rotor field from top to bottom at each height, particularly at higher hub height, which is difficult to do using conventional techniques, traditional techniques, or meteorological mast techniques. The meteorological mast consists of a cup anemometer and other measuring instruments to measure wind speed and wind direction. Using meteorological mast is not a representative idea as it gives point and fixed measurements, and empirical equations such as power law and log law are used to convert wind speed measured at 10 m or 30 m to larger heights of 100 m, 120 m, or more. This chapter is focused on increasing confidence in the result of remote-sensing measurement. Most importantly, there is economic merit in determining the total amount of cash flowing on wind resource assessment using advance different techniques