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

Elucidating mechanisms of proteasome modulation by small molecules to treat neurodegenerative diseases and cancer

Maintaining protein homeostasis, or proteostasis, is crucial for cellular function, and protein degradation through the proteasome plays a pivotal role in this process. Dysregulation of the proteasome can lead to proteostasis collapse and has been linked to the development of neurodegenerative diseases and cancers. Neurodegenerative diseases often exhibit proteasome impairment, whereas proteasome upregulation is frequently observed in cancer. Although the use of proteasome inhibitors as a pharmaceutical approach has shown success in certain cancers, it has yet to demonstrate efficacy in neurodegenerative diseases due to the absence of drug-like small molecules capable of effectively reversing proteasome impairment and/or activating the proteasome. To address this challenge, we conducted a study focused on understanding and emulating the HbYX-dependent mechanism of proteasome activation utilized by endogenous complexes known as Proteasome Activators. Through this investigation, we characterized and elucidated the mechanistic details of a small molecule called ZYA, which stimulates peptide and protein degradation by the proteasome. ZYA served as a research tool to investigate the HbYX-dependent mechanism, leading to the identification of critical conformational changes in the proteasome and the discovery of novel binding pockets for small molecules. While proteasome inhibitors are currently utilized in clinical settings, there is a growing concern regarding the development of resistance to these inhibitors, necessitating the development of novel proteasome inhibitors. We identified an unparalleled mechanism of regulation by reverse T3, a thyroid hormone variant, with the aim of designing similar small molecules that can specifically and robustly inhibit the proteasome. The findings presented in these studies provide a framework for the development of proteasome activators and inhibitors, offering potential therapeutic strategies for neurodegenerative diseases and cancer. Overall, this research contributes to the search for effective therapeutic interventions by shedding light on the design of proteasome-targeting compounds that can either activate or inhibit the proteasome, depending on the specific pathological context, ultimately aiding in the treatment of neurodegenerative diseases and cancer