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

Insight Into Nicotinamide Adenine Dinucleotide Homeostasis as a Targetable Metabolic Pathway in Colorectal Cancer

Tumour cells modify their cellular metabolism with the aim to sustain uncontrolled proliferation. Cancer cells necessitate adequate amounts of NAD and NADPH to support several enzymes that are usually overexpressed and/or overactivated. Nicotinamide adenine dinucleotide (NAD) is an essential cofactor and substrate of several NAD-consuming enzymes, such as PARPs and sirtuins, while NADPH is important in the regulation of the redox status in cells. The present review explores the rationale for targeting the key enzymes that maintain the cellular NAD/NADPH pool in colorectal cancer and the enzymes that consume or use NADP(H)

Imidazo[1,2-a]pyridine Derivatives as Aldehyde Dehydrogenase Inhibitors: Novel Chemotypes to Target Glioblastoma Stem Cells

Glioblastoma multiforme (GBM) is the deadliest form of brain tumour. It is known for its ability to escape the therapeutic options available to date, thanks to the presence of a subset of cells endowed with stem-like properties and able to resist to cytotoxic treatments. As the cytosolic enzyme aldehyde dehydrogenase 1A3 turns out to be overexpresses in this kind of cells, playing a key role for their vitality, treatments targeting this enzyme may represent a successful strategy to fight GBM. In this work we describe a novel class of imidazo[1,2-a]pyridine derivatives as aldehyde dehydrogenase 1A3 inhibitors, reporting the evidence of their significance as novel drug candidates for the treatment of GBM. Besides showing an interesting functional profile, in terms of activity against the target enzyme and selectivity toward highly homologous isoenzymes, representative examples of the series showed also a nanomolar to picomolar efficacy against patient-derived GBM stem-like cells, thus proving the concept that targeting aldehyde dehydrogenase might represent a novel and promising way to combat GBM by striking its ability to divide immortally