Exploring Fatty Acid Mimetics as NR4A Ligands.

The ligand-activated transcription factors Nur77, Nurr1, and NOR-1 forming the NR4A family of nuclear receptors are considered as potential targets in various pathologies, including neurodegeneration and cancer. However, chemical tools for pharmacological NR4A modulation as a prerequisite for target validation are rare. Recent findings suggest that NR4As bind fatty acid metabolites and fatty acid mimetic (FAM) drugs, opening new opportunities for NR4A modulator development. We have explored the chemical space of FAM NR4A ligands by using fragment screening, in silico analysis, and systematic structure-activity relationship evaluation. From a chemically diverse library of 92 fragments, we identified 11 new FAM NR4A agonist and inverse agonist scaffolds. Structural optimization of the most active FAM fragment yielded NR4A agonists with submicromolar potency and binding affinity, demonstrating remarkable potential of FAM as NR4A-modulating tools and drugs.

De Novo Design of Nurr1 Agonists via Fragment-Augmented Generative Deep Learning in Low-Data Regime.

Generative neural networks trained on SMILES can design innovative bioactive molecules de novo. These so-called chemical language models (CLMs) have typically been trained on tens of template molecules for fine-tuning. However, it is challenging to apply CLM to orphan targets with few known ligands. We have fine-tuned a CLM with a single potent Nurr1 agonist as template in a fragment-augmented fashion and obtained novel Nurr1 agonists using sampling frequency for design prioritization. Nanomolar potency and binding affinity of the top-ranking design and its structural novelty compared to available Nurr1 ligands highlight its value as an early chemical tool and as a lead for Nurr1 agonist development, as well as the applicability of CLM in very low-data scenarios.

Development of a Potent Nurr1 Agonist Tool for In Vivo Applications.

Nuclear receptor related 1 (Nurr1) is a neuroprotective transcription factor and an emerging target in neurodegenerative diseases. Despite strong evidence for a role in Parkinson's and Alzheimer's disease, pharmacological control and validation of Nurr1 are hindered by a lack of suitable ligands. We have discovered considerable Nurr1 activation by the clinically studied dihydroorotate dehydrogenase (DHODH) inhibitor vidofludimus calcium and systematically optimized this scaffold to a Nurr1 agonist with nanomolar potency, strong activation efficacy, and pronounced preference over the highly related receptors Nur77 and NOR1. The optimized compound induced Nurr1-regulated gene expression in astrocytes and exhibited favorable pharmacokinetics in rats, thus emerging as a superior chemical tool to study Nurr1 activation in vitro and in vivo.