Target Validation Research Articles

The immunotherapy mechanism of Hedyotis Diffusae Herba in treating liver cancer: a study based on network pharmacology, bioinformatics, and experimental validation.

Liver cancer is a malignant tumor that develops on or inside the liver. Hedyotis diffusa Willd (HDW) plays a significant role in anti-tumor activities; however, its mechanism against liver cancer remains unclear. This study aims to evaluate the immunotherapeutic mechanism of HDW in treating liver cancer through network pharmacology, bioinformatics analysis, and experimental validation. Network pharmacology was utilized to identify the active components and potential targets of HDW from the TCMSP database. A potential target protein-protein interaction (PPI) network was constructed using the STRING database, followed by function and pathway enrichment analysis of the targets using GO and KEGG methods. In addition, the key targets for HDW against liver cancer were identified using five different algorithms in Cytoscape. The TCGA and HPA databases were used to assess the mRNA and protein expression of core target genes in normal liver and liver cancer tissues and their relationship with overall survival in liver cancer, as well as their role in immune infiltration. Molecular docking between the core components of HDW and the core targets was performed using PyMOL software. The effects of HDW on the proliferation and apoptosis of liver cancer cells were examined using MTT and flow cytometry. The regulatory effects of the core component quercetin on core targets were validated using RT-qPCR and Western blot. A total of 163 potential targets were identified by searching for intersections among 7 types of active components and all potential and liver cancer targets. PPI network analysis revealed the core targets IL6 and TNF. GO enrichment analysis involved 2089 biological processes, 76 cellular components, and 196 molecular functions. KEGG enrichment analysis suggested that the anti-cancer effects of HDW might be mediated by the AGE-RAGE signaling pathway, IL-17 signaling pathway, TNF signaling pathway, PI3K-Akt signaling pathway, and NF-κB signaling pathway. Database validation of key targets showed that mRNA and protein expression results for the IL6 gene were contradictory, while those for the TNF gene were consistent, both being underexpressed in liver cancer. Importantly, the expression of IL6 and TNF was related to the infiltration of 24 types of immune cells, with the highest correlation with macrophages. Molecular docking showed that IL6 and TNF had high binding stability with quercetin, with binding energies of - 7.4 and - 6.0kJ∙mol-1, respectively. Experimental validation showed that quercetin inhibited liver cancer cell proliferation and promoted apoptosis in a dose-dependent manner, with protein results indicating that quercetin downregulated the mRNA and protein expression of IL6 and TNF, and upregulated key proteins in the AGE-RAGE signaling pathway, AGEs, and RAGE. This study comprehensively elucidates the activity, potential targets, and molecular mechanisms of HDW against liver cancer, providing a promising strategy for the scientific basis and treatment mechanism of traditional Chinese medicine in treating liver cancer.

Inflammasome-Inhibiting Nanoligomers Are Neuroprotective against Space-Induced Pathology in Healthy and Diseased Three-Dimensional Human Motor and Prefrontal Cortex Brain Organoids.

The microgravity and space environment has been linked to deficits in neuromuscular and cognitive capabilities, hypothesized to occur due to accelerated aging and neurodegeneration in space. While the specific mechanisms are still being investigated, spaceflight-associated neuropathology is an important health risk to astronauts and space tourists and is being actively investigated for the development of appropriate countermeasures. However, such space-induced neuropathology offers an opportunity for accelerated screening of therapeutic targets and lead molecules for treating neurodegenerative diseases. Here, we show a proof-of-concept high-throughput target screening (on Earth), target validation, and mitigation of microgravity-induced neuropathology using our Nanoligomer platform, onboard the 43-day SpaceX CRS-29 mission to the International Space Station. First, comparing 3D healthy and diseased prefrontal cortex (PFC, for cognition) and motor neuron (MN, for neuromuscular function) organoids, we assessed space-induced pathology using biomarkers relevant to Alzheimer's disease (AD), frontotemporal dementia (FTD), and amyotrophic lateral sclerosis (ALS). Both healthy and diseased PFC and MN organoids showed significantly enhanced neurodegeneration in space, as measured through relevant disease biomarkers, when compared to their respective Earth controls. Second, we tested the top two lead molecules, NI112 that targeted NF-κB and NI113 that targeted IL-6. We observed that these Nanoligomers significantly mitigate the AD, FTD, and ALS relevant biomarkers like amyloid beta-42 (Aβ42), phosphorylated tau (pTau), Kallikrein (KLK-6), Tar DNA-binding protein 43 (TDP-43), and others. Moreover, the 43-day Nanoligomer treatment of these brain organoids did not appear to cause any observable toxicity or safety issues in the target organoid tissue, suggesting good tolerability for these molecules in the brain at physiologically relevant doses. Together, these results show significant potential for both the development and translation of NI112 and NI113 molecules as potential neuroprotective countermeasures for safer space travel and demonstrate the usefulness of the space environment for rapid, high-throughput screening of targets and lead molecules for clinical translation. We assert that the use of microgravity in drug development and screening may ultimately benefit millions of patients suffering from debilitating neurodegenerative diseases on Earth.

Structural Optimization of Oxaprozin for Selective Inverse Nurr1 Agonism.

Nuclear receptor related 1 (Nurr1, NR4A2) is a ligand-sensing transcription factor with neuroprotective and anti-inflammatory roles widely distributed in the CNS. Pharmacological Nurr1 modulation is considered a promising experimental strategy in Parkinson's and Alzheimer's disease but target validation is incomplete. While significant progress has been made in Nurr1 agonist development, inverse agonists blocking the receptor's constitutive activity are lacking. Here we report comprehensive structure-activity relationship elucidation of oxaprozin which acts as moderately potent and nonselective inverse Nurr1 agonist and RXR agonist. We identified structural determinants selectively driving RXR agonism or inverse Nurr1 agonism of the scaffold enabling the development of selective inverse Nurr1 agonists with enhanced potency and strong efficacy.

Molecular Docking of Gamma Amino Butyric Acid GABA on Rattus Norvegicus B-receptor as Antidiabetic

Earlier research reported that GABA had a correlation with diabetes in processes of glucose homeostasis. This study aims to identify the validity of B-receptor Rattus norvegicus as GABA protein target, modeling the structure and knowing the binding affinity between GABA and B-receptor Rattus norvegicus through molecular docking. The research was carried out using in-silico method. The interaction of GABA with the target protein was determined using SuperPred, followed by modeling the protein target using SwissadMe. Ramachandran Plot and Errat Procheck are used to determine the validity of the protein target. Molecular docking was determined using Pyrx and PyMol. The results showed that GABA binding to the B- receptor Rattus norvegicus has biological activity as glucose oxidase inhibitor and antidiabetic. The conclusion are: B-receptor Rattus norvegicus is a valid protein target for binding to GABA; there are four 3-dimensional models of B-receptor Rattus norvegicus and the best model has 98.43% sequence identity; the binding affinity of GABA (ligand) on B-receptor Rattus norvegicus from the best model is -3.4 kcal/mol energy, 1.773 RMSD lower bound, and 1.81 RMSD upper bound. It is suggested that this research might be used as an empirical basis to further investigate GABA as antidiabetic.

CACTI: an in silico chemical analysis tool through the integration of chemogenomic data and clustering analysis

It is well-accepted that knowledge of a small molecule’s target can accelerate optimization. Although chemogenomic databases are helpful resources for predicting or finding compound interaction partners, they tend to be limited and poorly annotated. Furthermore, unlike genes, compound identifiers are often not standardized, and many synonyms may exist, especially in the biological literature, making batch analysis of compounds difficult. Here, we constructed an open-source annotation and target hypothesis prediction tool that explores some of the largest chemical and biological databases, mining these for both common name, synonyms, and structurally similar molecules. We used this Chemical Analysis and Clustering for Target Identification (CACTI) tool to analyze the Pathogen Box collection, an open-source set of 400 drug-like compounds active against a variety of microbial pathogens. Our analysis resulted in 4,315 new synonyms, 35,963 pieces of new information and target prediction hints for 58 members.Scientific contributionsWith the employment of this tool, a comprehensive report with known evidence, close analogs and drug-target prediction can be obtained for large-scale chemical libraries that will facilitate their evaluation and future target validation and optimization efforts.

Identification of Ribonuclease Inhibitors for the Control of Pathogenic Bacteria.

Bacteria are known to be constantly adapting to become resistant to antibiotics. Currently, efficient antibacterial compounds are still available; however, it is only a matter of time until these compounds also become inefficient. Ribonucleases are the enzymes responsible for the maturation and degradation of RNA molecules, and many of them are essential for microbial survival. Members of the PNPase and RNase II families of exoribonucleases have been implicated in virulence in many pathogens and, as such, are valid targets for the development of new antibacterials. In this paper, we describe the use of virtual high-throughput screening (vHTS) to identify chemical compounds predicted to bind to the active sites within the known structures of RNase II and PNPase from Escherichia coli. The subsequent in vitro screening identified compounds that inhibited the activity of these exoribonucleases, with some also affecting cell viability, thereby providing proof of principle for utilizing the known structures of these enzymes in the pursuit of new antibacterials.

Exploring the therapeutic potential of garlic in alcoholic liver disease: a network pharmacology and experimental validation study

ObjectiveEmploying network pharmacology and molecular docking, the study predicts the active compounds in garlic and elucidates their mechanism in inhibiting the development of alcoholic liver disease (ALD). ALD is a global chronic liver disease with potential for hepatocellular carcinoma progression.MethodsThe main active ingredients and targets of garlic were identified through screening the TCMSP, TCM-ID, and ETCM databases. ALD disease targets were sourced from DisGeNET, GeneCards, and DiGSeE databases, and intervention targets for garlic were determined through intersections. Protein interaction networks were constructed using the STRING platform, and GO and KEGG pathway enrichment analyses were performed with R software. The garlic component-disease-target network was established using Cytoscape software. Validation of active ingredients against core targets was conducted through molecular docking simulations using AutoDock Vina software. Expression validation of core targets was carried out using human sequencing data of ALD obtained from the GEO database.ResultsIntegration of garlic drug targets with ALD disease targets identified 83 target genes. Validation through an alcohol-induced ALD mouse model supported certain network pharmacology findings, suggesting that garlic may impede disease progression by mitigating the inflammatory response and promoting ethanol metabolism.ConclusionThis study provides insights into the potential therapeutic mechanisms of garlic in inhibiting ALD development. The identified active ingredients offer promising avenues for further investigation and development of treatments for ALD, emphasizing the importance of botanical remedies in liver disease management.

Exploring the mechanisms of Guizhifuling pills in the treatment of coronary spastic angina based on network pharmacology combined with molecular docking.

Coronary spastic angina (CSA) is common, and treatment options for refractory vasospastic angina are sometimes limited. Guizhifuling pills (GFP) have demonstrated efficacy in reducing CSA episodes, but their pharmacological mechanism remains unclear. To explore the mechanism of action of GFP in preventing and treating CSA, we employed network pharmacology and molecular docking to predict targets and analyze networks. We searched GFP chemical composition information and related targets from databases. The drug-target and drug-target pathway networks were constructed using Cytoscape. Then the protein-protein interaction was analyzed using the STRING database. Gene Ontology biological functions and Kyoto Encyclopedia of Genes and Genomes pathways were performed by the Metascape database, and molecular docking validation of vital active ingredients and action targets of GFP was performed using AutoDock Vina software. The 51 active components in GFP are expected to influence CSA by controlling 279 target genes and 151 signaling pathways. Among them, 6 core components, such as quercetin, β-sitosterol, and baicalein, may regulate CSA by affecting 10 key target genes such as STAT3, IL-6, TP53, AKT1, and EGFR. In addition, they are involved in various critical signaling pathways such as apelin, calcium, advanced glycation end product-receptor for advanced glycation end product, and necroptosis. Molecular docking analysis confirms favorable binding interactions between the active components of GFP and the selected target proteins. The effects of GFP in treating CSA involve multiple components, targets, and pathways, offering a theoretical basis for its clinical use and enhancing our understanding of how it works.

Micro Target: MicroRNA Target Prediction and Validation with Experimentally Positive and Negative Examples

MicroRNAs (miRNAs) usually controls the gene by binding to complementary sites of 3’ untranslated region of its target genes. Numerous criteria-based and machine learning approaches are available in the literature to predict miRNA–mRNA interactions, but most of them struggle with either high false positive or false negative rates and also don’t show good validation with experimentally validated positive and negative examples. Here we present microTarget, a new computational approach for identifying miRNA target genes which are based on complementarity score, thermodynamic duplex stability and also independent of conservation of target sites in related genomes. In this article, we validated our algorithm using positive and negative data from the literature in various human tissues, and our method outperformed existing computational methods such as miRanda, RNA22, and PITA. Receiver operating characteristic curves (ROC) and Matthew's correlation coefficient (MCC) were calculated using experimentally validated data, and they reveal that microTarget greatly improves miRNA target prediction compared to the three algorithms employed individually. Additionally, an F-score analysis demonstrated that microTarget greatly enhances the relevance of the other techniques. Thus, microTarget is a useful tool for biologists looking for miRNA targets and integrating them into biological contexts.

Discovery of Two Highly Selective Structurally Orthogonal Chemical Probes for Activin Receptor-like Kinases 1 and 2.

Activin receptor-like kinases 1-7 (ALK1-7) regulate a complex network of SMAD-independent as well as SMAD-dependent signaling pathways. One of the widely used inhibitors for functional investigations of these processes, in particular for bone morphogenetic protein (BMP) signaling, is LDN-193189. However, LDN-193189 has insufficient kinome-wide selectivity complicating its use in cellular target validation assays. Herein, we report the identification and comprehensive characterization of two chemically distinct highly selective inhibitors of ALK1 and ALK2, M4K2234 and MU1700, along with their negative controls. We show that both MU1700 and M4K2234 efficiently block the BMP pathway via selective in cellulo inhibition of ALK1/2 kinases and exhibit favorable in vivo profiles in mice. MU1700 is highly brain penetrant and shows remarkably high accumulation in the brain. These high-quality orthogonal chemical probes offer the selectivity required to become widely used tools for in vitro and in vivo investigation of BMP signaling.

Post-GWAS Validation of Target Genes Associated with HbF and HbA2 Levels.

Genome-Wide Association Studies (GWASs) have identified a huge number of variants associated with different traits. However, their validation through in vitro and in vivo studies often lags well behind their identification. For variants associated with traits or diseases of biomedical interest, this gap delays the development of possible therapies. This issue also impacts beta-hemoglobinopathies, such as beta-thalassemia and sickle cell disease (SCD). The definitive cures for these diseases are currently bone marrow transplantation and gene therapy. However, limitations regarding their effective use restrict their worldwide application. Great efforts have been made to identify whether modulators of fetal hemoglobin (HbF) and, to a lesser extent, hemoglobin A2 (HbA2) are possible therapeutic targets. Herein, we performed the post-GWAS in vivo validation of two genes, cyclin D3 (CCND3) and nuclear factor I X (NFIX), previously associated with HbF and HbA2 levels. The absence of Ccnd3 expression in vivo significantly increased g (HbF) and d (HbA2) globin gene expression. Our data suggest that CCND3 is a possible therapeutic target in sickle cell disease. We also confirmed the association of Nfix with γ-globin gene expression and present data suggesting a possible role for Nfix in regulating Kruppel-like transcription factor 1 (Klf1), a master regulator of hemoglobin switching. This study contributes to filling the gap between GWAS variant identification and target validation for beta-hemoglobinopathies.

Irisflorentin improves functional recovery after spinal cord injury by protecting the blood–spinal cord barrier and promoting axonal growth

Spinal cord injury (SCI) induces the disruption of the blood–spinal cord barrier (BSCB) and the failure of axonal growth. SCI activates a complex series of responses, including cell apoptosis and endoplasmic reticulum (ER) stress. Pericytes play a critical role in maintaining BSCB integrity and facilitating tissue growth and repair. However, the roles of pericytes in SCI and the potential mechanisms underlying the improvements in functional recovery in SCI remain unclear. Recent evidence indicates that irisflorentin exerts neuroprotective effects against Parkinson's disease; however, whether it has potential protective roles in SCI or not is still unknown. In this study, we found that the administration of irisflorentin significantly inhibited pericyte apoptosis, protected BSCB integrity, promoted axonal growth, and ultimately improved locomotion recovery in a rat model of SCI. In vitro, we found that the positive effects of irisflorentin on axonal growth were likely to be mediated by regulating the crosstalk between pericytes and neurons. Furthermore, irisflorentin effectively ameliorated ER stress caused by incubation with thapsigargin (TG) in pericytes. Meanwhile, the protective effect of irisflorentin on BSCB disruption is strongly related to the reduction of pericyte apoptosis via inhibition of ER stress. Collectively, our findings demonstrate that irisflorentin is beneficial for functional recovery after SCI and that pericytes are a valid target of interest for future SCI therapies.

A Highly Potent, Orally Bioavailable Pyrazole-Derived Cannabinoid CB2 Receptor- Selective Full Agonist for In Vivo Studies.

The cannabinoid CB2 receptor (CB2R) is a potential therapeutic target for distinct forms of tissue injury and inflammatory diseases. To thoroughly investigate the role of CB2R in pathophysiological conditions and for target validation in vivo, optimal pharmacological tool compounds are essential. Despite the sizable progress in the generation of potent and selective CB2R ligands, pharmacokinetic parameters are often neglected for in vivo studies. Here, we report the generation and characterization of a tetra-substituted pyrazole CB2R full agonist named RNB-61 with high potency (K i 0.13-1.81 nM, depending on species) and a peripherally restricted action due to P-glycoprotein-mediated efflux from the brain. 3H and 14C labeled RNB-61 showed apparent K d values of <4 nM toward human CB2R in both cell and tissue experiments. The 6,800-fold selectivity over CB1 receptors and negligible off-targets in vitro, combined with high oral bioavailability and suitable systemic pharmacokinetic (PK) properties, prompted the assessment of RNB-61 in a mouse ischemia-reperfusion model of acute kidney injury (AKI) and in a rat model of chronic kidney injury/inflammation and fibrosis (CKI) induced by unilateral ureteral obstruction. RNB-61 exerted dose-dependent nephroprotective and/or antifibrotic effects in the AKI/CKI models. Thus, RNB-61 is an optimal CB2R tool compound for preclinical in vivo studies with superior biophysical and PK properties over generally used CB2R ligands.

Screening and validation of therapeutic targets for chronic sinusitis with nasal polyps based on proteomics

Objective: To identify potential therapeutic targets of chronic sinusitis with nasal polyps (CRSwNP) through proteomics screening of and verify its effectiveness experimentally. Methods: The nasal tissue samples were collected from patients undergoing surgical treatment in the Department of Otorhinolaryngology, Head and Neck Surgery in Yuhuangding Hospital of Yantai from June 2010 to December 2021, including 69 patients with CRSwNP and 39 patients in the control group. Tissue samples were analyzed by liquid chromatography-tandem mass spectrometry (LC-MS/MS) in data-independent acquisition (DIA) mode to find differentially expressed proteins. Bioinformatics tools were employed to analyze the functions of differentially expressed proteins. The expression of hematopoietic cell kinase (HCK) in nasal tissues of patients with CRSwNP was further confirmed by qPCR and western blot. The mouse model of CRSwNP was established and treated with HCK inhibitor. The levels of inflammatory factors IgE, IL-4 and IL-5 in serum of CRSwNP mice, both treated and untreated with HCK inhibitors, were detected by enzyme-linked immunosorbent assay (ELISA) across different experimental groups. The experimental data were analyzed by Graphpad Prism 9 software. Results: DIA analysis identified 1 850 differential proteins, including 760 up-regulated proteins and 1 090 down-regulated proteins. Weighted correlation network analysis (WGCNA) correlation analysis of phenotypic data such as cell count and CT score with the results of genomics indemnified 575 proteins of MEBrown module which intersected with 35 kinases further screened from 1 850 differential proteins, yielding eight protein kinases: HCK, SYK, PDK2, FGR, PRKCB, ROR1, CAMK1 and GRK6. qPCR showed that the expression of HCK in CRSwNP was significantly higher than that in the control group (P<0.05). Further experiments in mice confirmed that the secretion of IgE, IL-4 and IL-5 in the serum of CRSwNP group was significantly higher than the control group (all P<0.05), indicating successful model establishment. The intervention of HCK significantly decreased the secretion of IgE, IL-4 and IL-5 in serum of mice (all P<0.05). Conclusion: The HCK inhibitor can reduce the inflammatory index of mice with CRSwNP, and HCK is a potential therapeutic target of CRSwNP.

TRPA1 Inhibition Effects by 3-Phenylcoumarin Derivatives.

Transient receptor potential ankyrin 1 (TRPA1) protein plays an important role in the inflammatory response, and it has been associated with different pain conditions and pain-related diseases, making TRPA1 a valid target for painkillers. In this study, we identified potential TRPA1 inhibitors and located their binding sites utilizing computer-aided drug design (CADD) techniques. The designed 3-phenylcoumarin-based TRPA1 inhibitors were successfully synthesized using a microwave assisted synthetic strategy. 3-(3-Bromophenyl)-7-acetoxycoumarin (5), 7-hydroxy-3-(3-hydroxyphenyl)coumarin (12) and 3-(3-hydroxyphenyl)coumarin (23) all showed inhibitory activity toward TRPA1 in vitro. Compound 5 also decreased the size and formation of breast cancer cells. Hence, targeting TRPA1 may represent a promising alternative for the treatment of pain and inflammation.

Role of Artificial Intelligence in Drug Discovery and Target Identification in Cancer.

Drug discovery and development (DDD) is a highly complex process that necessitates precise monitoring and extensive data analysis at each stage. Furthermore, the DDD process is both timeconsuming and costly. To tackle these concerns, artificial intelligence (AI) technology can be used, which facilitates rapid and precise analysis of extensive datasets within a limited timeframe. The pathophysiology of cancer disease is complicated and requires extensive research for novel drug discovery and development. The first stage in the process of drug discovery and development involves identifying targets. Cell structure and molecular functioning are complex due to the vast number of molecules that function constantly, performing various roles. Furthermore, scientists are continually discovering novel cellular mechanisms and molecules, expanding the range of potential targets. Accurately identifying the correct target is a crucial step in the preparation of a treatment strategy. Various forms of AI, such as machine learning, neural-based learning, deep learning, and network-based learning, are currently being utilised in applications, online services, and databases. These technologies facilitate the identification and validation of targets, ultimately contributing to the success of projects. This review focuses on the different types and subcategories of AI databases utilised in the field of drug discovery and target identification for cancer.

Impact of relative and absolute values on orienting attention in time.

Reward has been known to render the reward-associated stimulus more salient to block effective attentional orienting in space. However, whether and how reward influences goal-directed attention in time remains unclear. Here, we used a modified attentional cueing paradigm to explore the effect of reward on temporal attention, in which the valid targets were given a low monetary reward and invalid targets were given a high monetary reward. The results showed that the temporal cue validity effect was significantly smaller when the competitive reward structure was employed (Experiment 1), and we ruled out the possibility that the results were due to the practice effect (Experiment 2a) or a reward-promoting effect (Experiment 2b). When further strengthening the intensity of the reward from 1:10 to 1:100 (Experiment 3), we found a similar pattern of results to those in Experiment 1. These results suggest that reward information which was based on relative instead of absolute values can weaken, but not reverse, the orienting attention in time.

Induction of steatosis in primary human hepatocytes recapitulates key pathophysiological aspects of metabolic dysfunction-associated steatotic liver disease

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most common cause of chronic liver disease. Owing to limited available treatment options, novel pre-clinical models for target selection and drug validation are warranted. We have established and extensively characterized a primary human steatotic hepatocyte invitro model system that could guide the development of treatment strategies for MASLD. Cryopreserved primary human hepatocytes from five donors varying in sex and ethnicity were cultured with free fatty acids in a 3D collagen sandwich for 7 days and the development of MASLD was followed by assessing classical hepatocellular functions. As proof of concept, the effects of the drug firsocostat (GS-0976) on invitro MASLD phenotypes were evaluated. Incubation with free fatty acids induced steatosis, insulin resistance, mitochondrial dysfunction, inflammation, and alterations in prominent human gene signatures similar to patients with MASLD, indicating the recapitulation of human MASLD in this system. The application of firsocostat rescued clinically observed fatty liver disease pathologies, highlighting the ability of the invitro system to test the efficacy and potentially characterize the mode of action of drug candidates. Altogether, our human MASLD invitro model system could guide the development and validation of novel targets and drugs for the treatment of MASLD. Due to low drug efficacy and high toxicity, clinical treatment options for metabolic dysfunction-associated steatotic liver disease (MASLD) are currently limited. To facilitate earlier stop-go decisions in drug development, we have established a primary human steatotic hepatocyte invitro model. As the model recapitulates clinically relevant MASLD characteristics at high phenotypic resolution, it can serve as a pre-screening platform and guide target identification and validation in MASLD therapy.

Modeling inherited retinal diseases using human induced pluripotent stem cell derived photoreceptor cells and retinal pigment epithelial cells.

Since the discovery of induced pluripotent stem cell (iPSC) technology, there have been many attempts to create cellular models of inherited retinal diseases (IRDs) for investigation of pathogenic processes to facilitate target discovery and validation activities. Consistency remains key in determining the utility of these findings. Despite the importance of consistency, quality control metrics are still not widely used. In this review, a toolkit for harnessing iPSC technology to generate photoreceptor, retinal pigment epithelial cell, and organoid disease models is provided. Considerations while developing iPSC-derived IRD models such as iPSC origin, reprogramming methods, quality control metrics, control strategies, and differentiation protocols are discussed. Various iPSC IRD models are dissected and the scientific hurdles of iPSC-based disease modeling are discussed to provide an overview of current methods and future directions in this field.

Development of Nurr1 agonists from amodiaquine by scaffold hopping and fragment growing

The neuroprotective transcription factor nuclear receptor-related 1 (Nurr1) has shown great promise as a therapeutic target in Parkinson’s and Alzheimer’s disease as well as multiple sclerosis but high-quality chemical tools for pharmacological target validation of Nurr1 are rare. We have employed the weak Nurr1 modulator amodiaquine (AQ) and AQ-derived fragments as templates to design a new Nurr1 agonist chemotype by scaffold hopping and fragment growing strategies. Systematic structural optimization of this scaffold yielded Nurr1 agonists with nanomolar potency and binding affinity. Comprehensive in vitro profiling revealed efficient cellular target engagement and compliance with the highest probe criteria. In human midbrain organoids bearing a Parkinson-driving LRRK2 mutation, a novel Nurr1 agonist rescued tyrosine hydroxylase expression highlighting the potential of the new Nurr1 modulator chemotype as lead and as a chemical tool for biological studies.