Design and Optimization of Novel Competitive, Non-peptidic, SARS-CoV-2 Mpro Inhibitors.

The SARS-CoV-2 main protease (Mpro) has been proven to be a highly effective target for therapeutic intervention, yet only one drug currently holds FDA approval status for this target. We were inspired by a series of publications emanating from the Jorgensen and Anderson groups describing the design of potent, non-peptidic, competitive SARS-CoV-2 Mpro inhibitors, and we saw an opportunity to make several design modifications to improve the overall pharmacokinetic profile of these compounds without losing potency. To this end, we created a focused virtual library using reaction-based enumeration tools in the Schrödinger suite. These compounds were docked into the Mpro active site and subsequently prioritized for synthesis based upon relative binding affinity values calculated by FEP+. Fourteen compounds were selected, synthesized, and evaluated both biochemically and in cell culture. Several of the synthesized compounds proved to be potent, competitive Mpro inhibitors with improved metabolic stability profiles.

A Glutamate N-Methyl-d-Aspartate (NMDA) Receptor Subunit 2B-Selective Inhibitor of NMDA Receptor Function with Enhanced Potency at Acidic pH and Oral Bioavailability for Clinical Use.

We describe a clinical candidate molecule from a new series of glutamate N-methyl-d-aspartate receptor subunit 2B-selective inhibitors that shows enhanced inhibition at extracellular acidic pH values relative to physiologic pH. This property should render these compounds more effective inhibitors of N-methyl-d-aspartate receptors at synapses responding to a high frequency of action potentials, since glutamate-containing vesicles are acidic within their lumen. In addition, acidification of penumbral regions around ischemic tissue should also enhance selective drug action for improved neuroprotection. The aryl piperazine we describe here shows strong neuroprotective actions with minimal side effects in preclinical studies. The clinical candidate molecule NP10679 has high oral bioavailability with good brain penetration and is suitable for both intravenous and oral dosing for therapeutic use in humans. SIGNIFICANCE STATEMENT: This study identifies a new series of glutamate N-methyl-d-aspartate (NMDA) receptor subunit 2B-selective negative allosteric modulators with properties appropriate for clinical advancement. The compounds are more potent at acidic pH, associated with ischemic tissue, and this property should increase the therapeutic safety of this class by improving efficacy in affected tissue while sparing NMDA receptor block in healthy brain.

Synthesis and Antiviral Activity of a Series of 2'-C-Methyl-4'-thionucleoside Monophosphate Prodrugs.

The NS5B RNA-dependent RNA polymerase of the hepatitis C virus (HCV) is a validated target for nucleoside antiviral drug therapy. We endeavored to synthesize and test a series of 4'-thionucleosides with a monophosphate prodrug moiety for their antiviral activity against HCV and other related viruses in the Flaviviridae family. Nucleoside analogs were prepared via the stereoselective Vorbrüggen glycosylation of various nucleobases with per-acetylated 2-C-methyl-4-thio-d-ribose built in a 10-step synthetic sequence from the corresponding ribonolactone. Conjugation of the thionucleoside to a ProTide phosphoramidate allowed for evaluation of the prodrugs in the cellular HCV replicon assay with anti-HCV activities ranging from single-digit micromolar (µM) to >200 µM. The diminished anti-HCV potency of our best compound compared to its 4'-oxo congener is the subject of ongoing research in our lab and is proposed to stem from changes in sugar geometry imparted by the larger sulfur atom.

Correction to "Accelerated Discovery of Novel Ponatinib Analogs with Improved Properties for the Treatment of Parkinson's Disease".

[This corrects the article DOI: 10.1021/acsmedchemlett.9b00612.].

Accelerated Discovery of Novel Ponatinib Analogs with Improved Properties for the Treatment of Parkinson's Disease.

Parkinson's disease (PD) is a debilitating and common neurodegenerative disease. New insights implicating c-Abl activation as a driving force in PD have opened a new drug development avenue for PD treatment beyond the symptomatic relief by L-DOPA. BCR-Abl inhibitors, which include nilotinib and ponatinib, have been found to inhibit this process, and nilotinib has shown improvement in outcomes in a 12-patient, nonrandomized trial. However, nilotinib is a potent inhibitor of hERG, a cardiac K+ channel whose inhibition increases risk of sudden death. We used our machine learning approach to predict novel molecules that would inhibit c-Abl while also having minimal liability against hERG. Of our six novel compounds tested, we identified two that had c-Abl potencies comparable to nilotinib, but with significantly improved profiles regarding the hERG channel. Our best compound exhibited a hERG IC50 of 12.1 µM (compared to nilotinib with an IC50 of 0.45 µM and ponatinib with IC50 of 0.767 µM). This work is a step forward for a machine learning enabled, multiparameter optimization of a chemical space and represents a significant advance in the development of novel Parkinson's therapies.

Accelerated Discovery of Potent Fusion Inhibitors for Respiratory Syncytial Virus.

A series of five benzimidazole-based compounds were identified using a machine learning algorithm as potential inhibitors of the respiratory syncytial virus (RSV) fusion protein. These compounds were synthesized, and compound 2 in particular exhibited excellent in vitro potency with an EC50 value of 5 nM. This new scaffold was then further refined leading to the identification of compound 44, which exhibited a 10-fold improvement in activity with an EC50 value of 0.5 nM.

Design and Validation of FRESH, a Drug Discovery Paradigm Resting on Robust Chemical Synthesis.

A method capable of identifying novel synthetic targets for small molecule lead optimization has been developed. The FRESH (FRagment-based Exploitation of modular Synthesis by vHTS) approach relies on a multistep synthetic route to a target series of compounds devised by a close collaboration between synthetic and computational chemists. It combines compound library generation, quantitative structure-acitvity relationship construction, fragment processing, virtual high throughput screening and display of results within the Pipeline Pilot framework. Outcomes enumerate tailored selection of novel synthetic targets with improved potency and optimized physical properties for an emerging compound series. To validate the application of FRESH, three retrospective case studies have been performed to pinpoint reported potent analogues. One prospective case study was performed to demonstrate that FRESH is able to capture additional potent analogues.