17 research outputs found

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

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    : 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

    Disseminate Recurrent Folliculitis and Hidradenitis Suppurativa Are Associated Conditions: Results From a Retrospective Study of 131 Patients With Down Syndrome and a Cohort of 12,351 Pediatric Controls

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    Hidradenitis suppurativa (HS) is a chronic, inflammatory, recurrent skin disease of the pilosebaceous unit characterized by protean manifestations. Several studies have found an increased incidence and earlier presentation of this disease in patients carrying trisomy 21. Patients with Down syndrome (DS) have a higher risk of developing a wide range of cutaneous manifestations, including HS and chronic folliculitis. Recently, disseminate recurrent folliculitis (DRF) has been reported as an atypical monosymptomatic feature of HS at its onset
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