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

FUNCTIONAL AND PHARMACOLOGICAL CHARACTERIZATION OF GLUN3-CONTAINING NMDA RECEPTORS

N-methyl-D-aspartate (NMDA) receptors are a member of ionotropic glutamate receptors that mediate excitatory neurotransmission across the mammalian central nervous system. NMDA receptors are organized into heterotetrameric assemblies containing two obligatory GluN1 subunits and two GluN2A-D, or GluN3A-B subunits. GluN1 and GluN3A-B bind glycine or D-serine, whereas GluN2A-D bind glutamate. The structural, functional, and pharmacological investigation of GluN1/3 NMDA receptors has been greatly hindered by their unconventional properties such as impermeability to Ca2+, insensitivity to the voltage-dependent block by Mg2+, and robust desensitization upon binding their endogenous agonist glycine. Another major barrier in GluN3 research has been the lack of selective and potent ligands. This dissertation presents new understanding to facilitate functional investigation of GluN3A-containing NMDA receptors, and provides a mechanistic and pharmacological roadmap for the development of selective and potent tool-compounds and therapeutics targeting GluN1/3 NMDA receptors

Derivatives of (R)-3-(5-Furanyl)carboxamido-2-aminopropanoic Acid as Potent NMDA Receptor Glycine Site Agonists with GluN2 Subunit-Specific Activity

NMDA receptors mediate glutamatergic neurotransmission and are therapeutic targets due to their involvement in a variety of psychiatric and neurological disorders. Here, we describe the design and synthesis of a series of (R)-3-(5-fyranyl)carboxamido-2-aminopropanoic acid analogs 8a-s as agonists at the glycine (Gly) binding site in the GluN1 subunit, but not GluN3 subunits, of NMDA receptors. These novel analogs display high variation in potencies and agonist efficacies among the NMDA receptor subtypes (GluN1/2A-D) in a manner dependent on the GluN2 subunit. Notably, compound 8p is identified as a potent partial agonist at GluN1/2C (EC(50) = 0.074 μM) with agonist efficacy of 28% relative to activation by Gly and virtually no agonist activity at GluN1/2A, GluN1/2B and GluN1/2D. Thus, these novel agonists can modulate the activity of specific NMDA receptor subtypes by replacing the full endogenous agonists Gly or d-serine (d-Ser), thereby providing new opportunities in the development of novel therapeutic agents