Development of a Potent and Selective G2A (GPR132) Agonist.

G protein-coupled receptor G2A was postulated to be a promising target for the development of new therapeutics in neuropathic pain, acute myeloid leukemia, and inflammation. However, there is still a lack of potent, selective, and drug-like G2A agonists to be used as a chemical tool or as the starting matter for the development of drugs. In this work, we present the discovery and structure-activity relationship elucidation of a new potent and selective G2A agonist scaffold. Systematic optimization resulted in (3-(pyridin-3-ylmethoxy)benzoyl)-d-phenylalanine (T-10418) exhibiting higher potency than the reference and natural ligand 9-HODE and high selectivity among G protein-coupled receptors. With its favorable activity, a clean selectivity profile, excellent solubility, and high metabolic stability, T-10418 qualifies as a pharmacological tool to investigate the effects of G2A activation.

Chemogenomics for NR1 nuclear hormone receptors.

Nuclear receptors (NRs) regulate transcription in response to ligand binding and NR modulation allows pharmacological control of gene expression. Although some NRs are relevant as drug targets, the NR1 family, which comprises 19 NRs binding to hormones, vitamins, and lipid metabolites, has only been partially explored from a translational perspective. To enable systematic target identification and validation for this protein family in phenotypic settings, we present an NR1 chemogenomic (CG) compound set optimized for complementary activity/selectivity profiles and chemical diversity. Based on broad profiling of candidates for specificity, toxicity, and off-target liabilities, sixty-nine comprehensively annotated NR1 agonists, antagonists and inverse agonists covering all members of the NR1 family and meeting potency and selectivity standards are included in the final NR1 CG set. Proof-of-concept application of this set reveals effects of NR1 members in autophagy, neuroinflammation and cancer cell death, and confirms the suitability of the set for target identification and validation.

CRISPR-Cas9 screens reveal common essential miRNAs in human cancer cell lines.

BACKGROUND: Genome-wide functional screening using the CRISPR-Cas9 system is a powerful tool to uncover tumor-specific and common genetic dependencies across cancer cell lines. Current CRISPR-Cas9 knockout libraries, however, primarily target protein-coding genes. This limits functional genomics-based investigations of miRNA function. METHODS: We designed a novel CRISPR-Cas9 knockout library (lentiG-miR) of 8107 distinct sgRNAs targeting a total of 1769 human miRNAs and benchmarked its single guide RNA (sgRNA) composition, predicted on- and off-target activity, and screening performance against previous libraries. Using a total of 45 human cancer cell lines, representing 16 different tumor entities, we performed negative selection screens to identify miRNA fitness genes. Fitness miRNAs in each cell line were scored using a combination of supervised and unsupervised essentiality classifiers. Common essential miRNAs across distinct cancer cell lines were determined using the 90th percentile method. For subsequent validation, we performed knockout experiments for selected common essential miRNAs in distinct cancer cell lines and gene expression profiling. RESULTS: We found significantly lower off-target activity for protein-coding genes and a higher miRNA gene coverage for lentiG-miR as compared to previously described miRNA-targeting libraries, while preserving high on-target activity. A minor fraction of miRNAs displayed robust depletion of targeting sgRNAs, and we observed a high level of consistency between redundant sgRNAs targeting the same miRNA gene. Across 45 human cancer cell lines, only 217 (12%) of all targeted human miRNAs scored as a fitness gene in at least one model, and fitness effects for most miRNAs were confined to small subsets of cell lines. In contrast, we identified 49 common essential miRNAs with a homogenous fitness profile across the vast majority of all cell lines. Transcriptional profiling verified highly consistent gene expression changes in response to knockout of individual common essential miRNAs across a diverse set of cancer cell lines. CONCLUSIONS: Our study presents a miRNA-targeting CRISPR-Cas9 knockout library with high gene coverage and optimized on- and off-target activities. Taking advantage of the lentiG-miR library, we define a catalogue of miRNA fitness genes in human cancer cell lines, providing the foundation for further investigation of miRNAs in human cancer.

Azologs of the fatty acid mimetic drug cinalukast enable light-induced PPARα activation.

Photo-switchable nuclear receptor modulators ("photohormones") enable spatial and temporal control over transcription factor activity and are valuable precision tools for biological studies. We have developed a new photohormone chemotype by incorporating a light-switchable motif in the scaffold of a cinalukast-derived PPARα ligand and tuned light-controlled activity by systematic structural variation. An optimized photohormone exhibited PPARα agonism in its light-induced (Z)-configuration and strong selectivity over related lipid-activated transcription factors representing a valuable addition to the collection of light-controlled tools to study nuclear receptor activity.

Prospective de novo drug design with deep interactome learning.

De novo drug design aims to generate molecules from scratch that possess specific chemical and pharmacological properties. We present a computational approach utilizing interactome-based deep learning for ligand- and structure-based generation of drug-like molecules. This method capitalizes on the unique strengths of both graph neural networks and chemical language models, offering an alternative to the need for application-specific reinforcement, transfer, or few-shot learning. It enables the "zero-shot" construction of compound libraries tailored to possess specific bioactivity, synthesizability, and structural novelty. In order to proactively evaluate the deep interactome learning framework for protein structure-based drug design, potential new ligands targeting the binding site of the human peroxisome proliferator-activated receptor (PPAR) subtype gamma are generated. The top-ranking designs are chemically synthesized and computationally, biophysically, and biochemically characterized. Potent PPAR partial agonists are identified, demonstrating favorable activity and the desired selectivity profiles for both nuclear receptors and off-target interactions. Crystal structure determination of the ligand-receptor complex confirms the anticipated binding mode. This successful outcome positively advocates interactome-based de novo design for application in bioorganic and medicinal chemistry, enabling the creation of innovative bioactive molecules.

Functionally-instructed modifiers of response to ATR inhibition in experimental glioma.

BACKGROUND: The DNA damage response (DDR) is a physiological network preventing malignant transformation, e.g. by halting cell cycle progression upon DNA damage detection and promoting DNA repair. Glioblastoma are incurable primary tumors of the nervous system and DDR dysregulation contributes to acquired treatment resistance. Therefore, DDR targeting is a promising therapeutic anti-glioma strategy. Here, we investigated Ataxia telangiectasia and Rad3 related (ATR) inhibition (ATRi) and functionally-instructed combination therapies involving ATRi in experimental glioma. METHODS: We used acute cytotoxicity to identify treatment efficacy as well as RNAseq and DigiWest protein profiling to characterize ATRi-induced modulations within the molecular network in glioma cells. Genome-wide CRISPR/Cas9 functional genomic screens and subsequent validation with functionally-instructed compounds and selected shRNA-based silencing were employed to discover and investigate molecular targets modifying response to ATRi in glioma cell lines in vitro, in primary cultures ex vivo and in zebrafish and murine models in vivo. RESULTS: ATRi monotherapy displays anti-glioma efficacy in vitro and ex vivo and modulates the molecular network. We discovered molecular targets by genome-wide CRISPR/Cas9 loss-of-function and activation screens that enhance therapeutic ATRi effects. We validated selected druggable targets by a customized drug library and functional assays in vitro, ex vivo and in vivo. CONCLUSION: In conclusion, our study leads to the identification of novel combination therapies involving ATRi that could inform future preclinical studies and early phase clinical trials.

Rational design and virtual screening identify mimetics of the RXR agonist valerenic acid.

The ligand-sensing transcription factor retinoid X receptor (RXR) is the universal heterodimer partner of nuclear receptors and involved in multiple physiological processes. Its pharmacological modulation holds therapeutic potential in cancer and neurodegeneration but many available RXR ligands lack specificity. The sesquiterpenoid valerenic acid has been identified as RXR agonist with unprecedented subtype and homodimer preference. Here, we identified simplified mimetics of the complex natural product by rational design and virtual screening that exhibited similar activity profiles on RXR and informed about structural elements contributing to the favorable activity.

Structure-Guided Design of a Highly Potent Partial RXR Agonist with Superior Physicochemical Properties.

Retinoid X receptors (RXRs, NR2B1-3) hold therapeutic potential in oncology, neurodegeneration, and metabolic diseases, but traditional RXR agonists mimicking the natural ligand 9-cis retinoic acid exhibit poor physicochemical properties, pharmacokinetics, and safety profiles. Improved RXR ligands are needed to exploit RXR modulation as a promising therapeutic concept in various indications beyond its current role in second-line cancer treatment. Here, we report the co-crystal structure of RXR in complex with a novel pyrimidine-based ligand and the structure-informed optimization of this scaffold to highly potent and highly soluble RXR agonists. Focused structure-activity relationship elucidation and rigidization resulted in a substantially optimized partial RXR agonist with low nanomolar potency, no cytotoxic activity, and very favorable physicochemical properties highlighting this promising scaffold for the development of next-generation RXR targeting drugs.

Structural Fusion of Natural and Synthetic Ligand Features Boosts RXR Agonist Potency.

The retinoid X receptors (RXRs) are ligand-activated transcription factors involved in, for example, differentiation and apoptosis regulation. Currently used reference RXR agonists suffer from insufficient specificity and poor physicochemical properties, and improved tools are needed to capture the unexplored therapeutic potential of RXR. Endogenous vitamin A-derived RXR ligands and the natural product RXR agonist valerenic acid comprise acrylic acid residues with varying substitution patterns to engage the critical ionic contact with the binding site arginine. To mimic and exploit this natural ligand motif, we probed its structural fusion with synthetic RXR modulator scaffolds, which had profound effects on agonist activity and remarkably boosted potency of an oxaprozin-derived RXR agonist chemotype. Bioisosteric replacement of the acrylic acid to overcome its pan-assay interference compounds (PAINS) character enabled the development of a highly optimized RXR agonist chemical probe.

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.

Structural Modification of the Natural Product Valerenic Acid Tunes RXR Homodimer Agonism.

Retinoid X receptors (RXR) are ligand-sensing transcription factors with a unique role in nuclear receptor signaling as universal heterodimer partners. RXR modulation holds potential in cancer, neurodegeneration and metabolic diseases but adverse effects of RXR activation and lack of selective modulators prevent further exploration as therapeutic target. The natural product valerenic acid has been discovered as RXR agonist with unprecedented preference for RXR subtype and homodimer activation. To capture structural determinants of this activity profile and identify potential for optimization, we have studied effects of structural modification of the natural product on RXR modulation and identified an analogue with enhanced RXR homodimer agonism.

Structure-Guided Design of Nurr1 Agonists Derived from the Natural Ligand Dihydroxyindole.

The neuroprotective transcription factor Nurr1 was recently found to bind the dopamine metabolite 5,6-dihydroxyindole (DHI) providing access to Nurr1 ligand design from a natural template. We screened a custom set of 14 k extended DHI analogues in silico for optimized descendants to select 24 candidates for microscale synthesis and in vitro testing. Three out of six primary hits were validated as novel Nurr1 agonists with up to sub-micromolar binding affinity, highlighting the druggability of the Nurr1 surface region lining helix 12. In vitro profiling confirmed cellular target engagement of DHI descendants and demonstrated remarkable additive effects of combined Nurr1 agonist treatment, indicating diverse binding sites mediating Nurr1 activation, which may open new avenues in Nurr1 modulation.

Glucocorticoids regulate lipid mediator networks by reciprocal modulation of 15-lipoxygenase isoforms affecting inflammation resolution.

Glucocorticoids (GC) are potent anti-inflammatory agents, broadly used to treat acute and chronic inflammatory diseases, e.g., critically ill COVID-19 patients or patients with chronic inflammatory bowel diseases. GC not only limit inflammation but also promote its resolution although the underlying mechanisms are obscure. Here, we reveal reciprocal regulation of 15-lipoxygenase (LOX) isoform expression in human monocyte/macrophage lineages by GC with respective consequences for the biosynthesis of specialized proresolving mediators (SPM) and their 15-LOX-derived monohydroxylated precursors (mono-15-OH). Dexamethasone robustly up-regulated pre-mRNA, mRNA, and protein levels of ALOX15B/15-LOX-2 in blood monocyte-derived macrophage (MDM) phenotypes, causing elevated SPM and mono-15-OH production in inflammatory cell types. In sharp contrast, dexamethasone blocked ALOX15/15-LOX-1 expression and impaired SPM formation in proresolving M2-MDM. These dexamethasone actions were mimicked by prednisolone and hydrocortisone but not by progesterone, and they were counteracted by the GC receptor (GR) antagonist RU486. Chromatin immunoprecipitation (ChIP) assays revealed robust GR recruitment to a putative enhancer region within intron 3 of the ALOX15B gene but not to the transcription start site. Knockdown of 15-LOX-2 in M1-MDM abolished GC-induced SPM formation and mono-15-OH production. Finally, ALOX15B/15-LOX-2 upregulation was evident in human monocytes from patients with GC-treated COVID-19 or patients with IBD. Our findings may explain the proresolving GC actions and offer opportunities for optimizing GC pharmacotherapy and proresolving mediator production.

An Introduction to Chemogenomics.

Chemogenomics is an innovative approach in chemical biology that synergizes combinatorial chemistry and genomic and proteomic biology to systematically study the response of a biological system to a set of compounds, which can aid the identification and validation of biological targets as well as biologically active small-molecule agents responsible for a phenotypic outcome. Central to this strategy is a collection of chemically diverse compounds, a so-called chemogenomics library. Selection and annotation of vastly available chemogenomic compound candidates for an inclusion in such set present a challenge, but optimal compound selection is critical for success of chemogenomics. The library can be used in a wide variety of research applications from biological mechanism deconvolution to drug discovery. However, phenotypic screening methods are typically required to be high-throughput and equipped with a systematic analysis of complex biological-chemical interactions. This chapter provides a general outline to the chemogenomics approach, including concept and critical steps in all stages of this innovative chemical biology strategy.

Compilation of Custom Compound/Bioactivity Datasets from Public Repositories.

Public repositories containing compound-bioactivity data for millions of small molecules offer a valuable resource for chemogenomic compound candidate search. Nonetheless, owning to nonuniform data mining, these databases are often incomplete, thus advocating the combined use of data from several repositories to increase target coverage and data accuracy. Here, we present a workflow to generate custom datasets from public databases for mining chemogenomic compound candidates. The compiled set provides flags for differences in structural and bioactivity data and enables rapid extraction of potent and selective bioactive compounds.

A Fluorescence-Based Reporter Gene Assay to Characterize Nuclear Receptor Modulators.

Reporter gene assays are critical tools of nuclear receptor research for characterizing the effects of ligands on nuclear receptor activity. Common luciferase-based techniques require expensive substrates and are typically performed in endpoint format. Here, we describe a versatile reporter gene assay to observe nuclear receptor activity with fluorescent proteins as reporters. This setting is highly cost-efficient and enables observation of nuclear receptor activity over time with multiple measurements from one plate.

Targeting the Alternative Vitamin E Metabolite Binding Site Enables Noncanonical PPARγ Modulation.

The lipid-sensing transcription factor PPARγ is the target of antidiabetic thiazolidinediones (TZD). At two sites within its ligand binding domain, it also binds oxidized vitamin E metabolites and the vitamin E mimetic garcinoic acid. While the canonical interaction within the TZD binding site mediates classical PPARγ activation, the effects of the second binding on PPARγ activity remain elusive. Here, we identified an agonist mimicking dual binding of vitamin E metabolites and developed a selective ligand of the second site, unveiling potential noncanonical regulation of PPARγ activities. We found that this alternative binding event can simultaneously occur with orthosteric ligands and it exerted different effects on PPARγ-cofactor interactions compared to both orthosteric PPARγ agonists and antagonists, indicating the diverse roles of the two binding sites. Alternative site binding lacked the pro-adipogenic effect of TZD and mediated no classical PPAR signaling in differential gene expression analysis but markedly diminished FOXO signaling, suggesting potential therapeutic applications.

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.

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 Light-Activated LXR Agonists.

Activation of the oxysterol-sensing transcription factor liver X receptor (LXR) has been studied as a therapeutic strategy in metabolic diseases and cancer but is compromised by the side effects of LXR agonists. Local LXR activation in cancer treatment may offer an opportunity to overcome this issue suggesting potential uses of photopharmacology. We report the computer-aided development of photoswitchable LXR agonists based on the T0901317 scaffold, which is a known LXR agonist. Azologization and structure-guided structure-activity relationship evaluation enabled the design of an LXR agonist, which activated LXR with low micromolar potency in its light-induced (Z)-state and was inactive as (E)-isomer. This tool sensitized human lung cancer cells to chemotherapeutic treatment in a light-dependent manner supporting potential of locally activated LXR agonists as adjuvant cancer treatment.