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

Does Over-the-Counter Purchase of Antihistamines by Residents of Dhaka City, Bangladesh Align with the Prescribing Choices of the Physicians Practicing in That City?

Most current guidelines recommend prescribing second-generation antihistamines (SGAs) over first-generation antihistamines because SGAs are less likely to cause sedation and impairment of heavy work performance. However, common residents who use these antihistamines as over-the-counter (OTC) medicines are less likely to know that. So, this study was designed to compare the over-the-counter use of antihistamines by common residents with the prescribing preferences of physicians residing at Dhaka City, Bangladesh. Between June and August of 2017, a total of 100 Physicians from some of the top medical institutions of the city and 350 randomly selected common residents were directly interviewed with two separate semistructured questionnaires specifically designed for each population. Data was statistically analyzed using Fischer’s exact test, Spearman’s rank correlation test and Kendall’s tau rank correlation test. The data shows that physicians prefer second-generation antihistamines with fexofenadine (48.09% of the total responses), desloratadine (16.03%), and rupatadine (13.74%) taking the top spots. Cetirizine (29.46% of total responses), desloratadine (14.73%), and chlorpheniramine (14.52%) were the most used OTC antihistamines by the common residents. Statistical analysis with Fischer’s exact test revealed that the difference in preference of first-generation antihistamines between physicians and common residents were extremely significant (p<0.0001). Furthermore, cetirizine (which is known to have some degree of sedating activity) and chlorpheniramine are more preferred among common residents than among physicians (extremely significant difference, p<0.0001 in both cases). The study concludes that physicians of Dhaka City are complying with practice guidelines, but sedating antihistamines still retain some popularity among the common residents. Hence, a more engaging community pharmacy is needed to minimize adverse effects that can arise from OTC use of sedating antihistamines