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

Nations within a nation: variations in epidemiological transition across the states of India, 1990–2016 in the Global Burden of Disease Study

18% of the world's population lives in India, and many states of India have populations similar to those of large countries. Action to effectively improve population health in India requires availability of reliable and comprehensive state-level estimates of disease burden and risk factors over time. Such comprehensive estimates have not been available so far for all major diseases and risk factors. Thus, we aimed to estimate the disease burden and risk factors in every state of India as part of the Global Burden of Disease (GBD) Study 2016

Iroquois genes influence proximo-distal morphogenesis during rat lung development

Lung development is a highly regulated process directed by mesenchymal-epithelial interactions, which coordinate the temporal and spatial expression of multiple regulatory factors required for proper lung formation. The Iroquois homeobox (Irx) genes have been implicated in the patterning and specification of several Drosophila and vertebrate organs, including the heart. Herein, we investigated whether the Irx genes play a role in lung morphogenesis. We found that Irx1-3 and Irx5 expression was confined to the branching lung epithelium, whereas Irx4 was not expressed in the developing lung. Antisense knockdown of all pulmonary Irx genes together dramatically decreased distal branching morphogenesis and increased distention of the proximal tubules in vitro, which was accompanied by a reduction in surfactant protein C-positive epithelial cells and an increase in β-tubulin IV and Clara cell secretory protein positive epithelial structures. Transmission electron microscopy confirmed the proximal phenotype of the epithelial structures. Furthermore, antisense Irx knockdown resulted in loss of lung mesenchyme and abnormal smooth muscle cell formation. Expression of fibroblast growth factors (FGF) 1, 7, and 10, FGF receptor 2, bone morphogenetic protein 4, and Sonic hedgehog (Shh) were not altered in lung explants treated with antisense Irx oligonucleotides. All four Irx genes were expressed in Shh- and Gli 2-deficient murine lungs. Collectively, these results suggest that Irx genes are involved in the regulation of proximo-distal morphogenesis of the developing lung but are likely not linked to the FGF, BMP, or Shh signaling pathways. Copyrigh