Prophylactic treatment with the c-Abl inhibitor, neurotinib, diminishes neuronal damage and the convulsive state in pilocarpine-induced mice.

The molecular mechanisms underlying seizure generation remain elusive, yet they are crucial for developing effective treatments for epilepsy. The current study shows that inhibiting c-Abl tyrosine kinase prevents apoptosis, reduces dendritic spine loss, and maintains N-methyl-d-aspartate (NMDA) receptor subunit 2B (NR2B) phosphorylated in in vitro models of excitotoxicity. Pilocarpine-induced status epilepticus (SE) in mice promotes c-Abl phosphorylation, and disrupting c-Abl activity leads to fewer seizures, increases latency toward SE, and improved animal survival. Currently, clinically used c-Abl inhibitors are non-selective and have poor brain penetration. The allosteric c-Abl inhibitor, neurotinib, used here has favorable potency, selectivity, pharmacokinetics, and vastly improved brain penetration. Neurotinib-administered mice have fewer seizures and improved survival following pilocarpine-SE induction. Our findings reveal c-Abl kinase activation as a key factor in ictogenesis and highlight the impact of its inhibition in preventing the insurgence of epileptic-like seizures in rodents and humans.

An Orally Efficacious Thyrotropin Receptor Ligand Inhibits Growth and Metastatic Activity of Thyroid Cancers.

CONTEXT: Thyroid-stimulating hormone (or thyrotropin) receptor (TSHR) could be a selective target for small molecule ligands to treat thyroid cancer (TC). OBJECTIVE: We report a novel, orally efficacious ligand for TSHR that exhibits proliferation inhibitory activity against human TC in vitro and in vivo, and inhibition of metastasis in vivo. DESIGN: A35 (NCATS-SM4420; NCGC00241808) was selected from a sub-library of >200 TSHR ligands. Cell proliferation assays including BrdU incorporation and WST-1, along with molecular docking studies were done. In vivo activity of A35 was assessed in TC cell-derived xenograft (CDX) models with immunocompromised (NSG) mice. FFPE sections of tumor and lung tissues were observed for the extent of cell death and metastasis. RESULTS: A35 was shown to stimulate cAMP production in some cell types by activating TSHR but not in TC cells, MDA-T32 and MDA-T85. A35 inhibited proliferation of MDA-T32 & MDA-T85 in vitro and in vivo, and pulmonary metastasis of MDA-T85F1 in mice. In vitro, A35 inhibition of proliferation was reduced by a selective TSHR antagonist. Inhibition of CDX tumor growth without decreases in mouse weights and liver function showed A35 to be efficacious without apparent toxicity. Lastly, A35 reduced levels of Ki67 in the tumors and metastatic markers in lung tissues. CONCLUSION: We conclude that A35 is a TSHR-selective inhibitor of TC cell proliferation and metastasis, and suggest that A35 may be a promising lead drug candidate for the treatment of differentiated thyroid cancer in humans.

A patient safety knowledge graph supporting vaccine product development.

BACKGROUND: Knowledge graphs are well-suited for modeling complex, unstructured, and multi-source data and facilitating their analysis. During the COVID-19 pandemic, adverse event data were integrated into a knowledge graph to support vaccine safety surveillance and nimbly respond to urgent health authority questions. Here, we provide details of this post-marketing safety system using public data sources. In addition to challenges with varied data representations, adverse event reporting on the COVID-19 vaccines generated an unprecedented volume of data; an order of magnitude larger than adverse events for all previous vaccines. The Patient Safety Knowledge Graph (PSKG) is a robust data store to accommodate the volume of adverse event data and harmonize primary surveillance data sources. METHODS: We designed a semantic model to represent key safety concepts. We built an extract-transform-load (ETL) data pipeline to parse and import primary public data sources; align key elements such as vaccine names; integrated the Medical Dictionary for Regulatory Activities (MedDRA); and applied quality metrics. PSKG is deployed in a Neo4J graph database, and made available via a web interface and Application Programming Interfaces (APIs). RESULTS: We import and align adverse event data and vaccine exposure data from 250 countries on a weekly basis, producing a graph with 4,340,980 nodes and 30,544,475 edges as of July 1, 2022. PSKG is used for ad-hoc analyses and periodic reporting for several widely available COVID-19 vaccines. Analysis code using the knowledge graph is 80% shorter than an equivalent implementation written entirely in Python, and runs over 200 times faster. CONCLUSIONS: Organizing safety data into a concise model of nodes, properties, and edge relationships has greatly simplified analysis code by removing complex parsing and transformation algorithms from individual analyses and instead managing these centrally. The adoption of the knowledge graph transformed how the team answers key scientific and medical questions. Whereas previously an analysis would involve aggregating and transforming primary datasets from scratch to answer a specific question, the team can now iterate easily and respond as quickly as requests evolve (e.g., "Produce vaccine-X safety profile for adverse event-Y by country instead of age-range").

Validation of a Natural Language Machine Learning Model for Safety Literature Surveillance.

INTRODUCTION: As part of routine safety surveillance, thousands of articles of potential interest are manually triaged for review by safety surveillance teams. This manual triage task is an interesting candidate for automation based on the abundance of process data available for training, the performance of natural language processing algorithms for this type of cognitive task, and the small number of safety signals that originate from literature review, resulting in its lower risk profile. However, deep learning algorithms introduce unique risks and the validation of such models for use in Good Pharmacovigilance Practice remains an open question. OBJECTIVE: Qualifying an automated, deep learning approach to literature surveillance for use at AstraZeneca. METHODS: The study is a prospective validation of a literature surveillance triage model, comparing its real-world performance with that of human surveillance teams working in parallel. The biggest risk in modifying this triage process is missing a safety signal (resulting in model false negatives) and hence model recall is the main evaluation metric considered. RESULTS: The model demonstrates consistent global performance from training through testing, with recall rates comparable to that of existing surveillance teams. The model is accepted for use specifically for those products where non-inferiority to the manual process is rigorously demonstrated. CONCLUSION: Characterizing model performance prospectively, under real-world conditions, allows us to thoroughly examine model consistency and failure modes, qualifying it for use in our surveillance processes. We also identify potential future improvements and recognize the opportunity for the community to collaborate on this shared task.

Discovery of small molecule agonists of the Relaxin Family Peptide Receptor 2.

The relaxin/insulin-like family peptide receptor 2 (RXFP2) belongs to the family of class A G-protein coupled receptors (GPCRs) and it is the only known target for the insulin-like factor 3 peptide (INSL3). The importance of this ligand-receptor pair in the development of the gubernacular ligament during the transabdominal phase of testicular descent is well established. More recently, RXFP2 has been implicated in maintaining healthy bone formation. In this report, we describe the discovery of a small molecule series of RXFP2 agonists. These compounds are highly potent, efficacious, and selective RXFP2 allosteric agonists that induce gubernacular invagination in mouse embryos, increase mineralization activity in human osteoblasts in vitro, and improve bone trabecular parameters in adult mice. The described RXFP2 agonists are orally bioavailable and display favorable pharmacokinetic properties, which allow for future evaluation of the therapeutic benefits of modulating RXFP2 activation in disease models.

Discovery of small molecule inhibitors that effectively disrupt IQGAP1-Cdc42 interaction in breast cancer cells.

The small GTPase Cdc42 is an integral component of the cytoskeleton, and its dysregulation leads to pathophysiological conditions, such as cancer. Binding of Cdc42 to the scaffold protein IQGAP1 stabilizes Cdc42 in its active form. The interaction between Cdc42 and IQGAP1 enhances migration and invasion of cancer cells. Disrupting this association could impair neoplastic progression and metastasis; however, no effective means to achieve this has been described. Here, we screened 78,500 compounds using a homogeneous time resolved fluorescence-based assay to identify small molecules that disrupt the binding of Cdc42 to IQGAP1. From the combined results of the validation assay and counter-screens, we selected 44 potent compounds for cell-based experiments. Immunoprecipitation and cell viability analysis rendered four lead compounds, namely NCGC00131308, NCGC00098561, MLS000332963 and NCGC00138812, three of which inhibited proliferation and migration of breast carcinoma cells. Microscale thermophoresis revealed that two compounds bind directly to Cdc42. One compound reduced the amount of active Cdc42 in cells and effectively impaired filopodia formation. Docking analysis provided plausible models of the compounds binding to the hydrophobic pocket adjacent to the GTP binding site of Cdc42. In conclusion, we identified small molecules that inhibit binding between Cdc42 and IQGAP1, which could potentially yield chemotherapeutic agents.

Activation of mitochondrial TRAP1 stimulates mitochondria-lysosome crosstalk and correction of lysosomal dysfunction.

Numerous studies have established the involvement of lysosomal and mitochondrial dysfunction in the pathogenesis of neurodegenerative disorders such as Alzheimer's and Parkinson diseases. Building on our previous studies of the neurodegenerative lysosomal lipidosis Niemann-Pick C1 (NPC1), we have unexpectedly discovered that activation of the mitochondrial chaperone tumor necrosis factor receptor-associated protein 1 (TRAP1) leads to the correction of the lysosomal storage phenotype in patient cells from multiple lysosomal storage disorders including NPC1. Using small compound activators specific for TRAP1, we find that activation of this chaperone leads to a generalized restoration of lysosomal and mitochondrial health. Mechanistically, we show that this process includes inhibition of oxidative phosphorylation and reduction of oxidative stress, which results in activation of AMPK and ultimately stimulates lysosome recycling. Thus, TRAP1 participates in lysosomal-mitochondrial crosstalk to maintain cellular homeostasis and could represent a potential therapeutic target for multiple disorders.

Real-Time Cellular Thermal Shift Assay to Monitor Target Engagement.

Determining a molecule's mechanism of action is paramount during chemical probe development and drug discovery. The cellular thermal shift assay (CETSA) is a valuable tool to confirm target engagement in cells for a small molecule that demonstrates a pharmacological effect. CETSA directly detects biophysical interactions between ligands and protein targets, which can alter a protein's unfolding and aggregation properties in response to thermal challenge. In traditional CETSA experiments, each temperature requires an individual sample, which restricts throughput and requires substantial optimization. To capture the full aggregation profile of a protein from a single sample, we developed a prototype real-time CETSA (RT-CETSA) platform by coupling a real-time PCR instrument with a CCD camera to detect luminescence. A thermally stable Nanoluciferase variant (ThermLuc) was bioengineered to withstand unfolding at temperatures greater than 90 °C and was compatible with monitoring target engagement events when fused to diverse targets. Utilizing well-characterized inhibitors of lactate dehydrogenase alpha, RT-CETSA showed significant correlation with enzymatic, biophysical, and other cell-based assays. A data analysis pipeline was developed to enhance the sensitivity of RT-CETSA to detect on-target binding. RT-CETSA technology advances capabilities of the CETSA method and facilitates the identification of ligand-target engagement in cells, a critical step in assessing the mechanism of action of a small molecule.

Discovery and Optimization of Pyrrolopyrimidine Derivatives as Selective Disruptors of the Perinucleolar Compartment, a Marker of Tumor Progression toward Metastasis.

The perinucleolar compartment (PNC) is a dynamic subnuclear body found at the periphery of the nucleolus. The PNC is enriched with RNA transcripts and RNA-binding proteins, reflecting different states of genome organization. PNC prevalence positively correlates with cancer progression and metastatic capacity, making it a useful marker for metastatic cancer progression. A high-throughput, high-content assay was developed to identify novel small molecules that selectively reduce PNC prevalence in cancer cells. We identified and further optimized a pyrrolopyrimidine series able to reduce PNC prevalence in PC3M cancer cells at submicromolar concentrations without affecting cell viability. Structure-activity relationship exploration of the structural elements necessary for activity resulted in the discovery of several potent compounds. Analysis of in vitro drug-like properties led to the discovery of the bioavailable analogue, metarrestin, which has shown potent antimetastatic activity with improved survival in rodent models and is currently being evaluated in a first-in-human phase 1 clinical trial.

Progress toward a universal biomedical data translator.

Clinical, biomedical, and translational science has reached an inflection point in the breadth and diversity of available data and the potential impact of such data to improve human health and well-being. However, the data are often siloed, disorganized, and not broadly accessible due to discipline-specific differences in terminology and representation. To address these challenges, the Biomedical Data Translator Consortium has developed and tested a pilot knowledge graph-based "Translator" system capable of integrating existing biomedical data sets and "translating" those data into insights intended to augment human reasoning and accelerate translational science. Having demonstrated feasibility of the Translator system, the Translator program has since moved into development, and the Translator Consortium has made significant progress in the research, design, and implementation of an operational system. Herein, we describe the current system's architecture, performance, and quality of results. We apply Translator to several real-world use cases developed in collaboration with subject-matter experts. Finally, we discuss the scientific and technical features of Translator and compare those features to other state-of-the-art, biomedical graph-based question-answering systems.

c-Abl Activation Linked to Autophagy-Lysosomal Dysfunction Contributes to Neurological Impairment in Niemann-Pick Type A Disease.

Niemann-Pick type A (NPA) disease is a fatal lysosomal neurodegenerative disorder caused by the deficiency in acid sphingomyelinase (ASM) activity. NPA patients present severe and progressive neurodegeneration starting at an early age. Currently, there is no effective treatment for this disease and NPA patients die between 2 and 3 years of age. NPA is characterized by an accumulation of sphingomyelin in lysosomes and dysfunction in the autophagy-lysosomal pathway. Recent studies show that c-Abl tyrosine kinase activity downregulates autophagy and the lysosomal pathway. Interestingly, this kinase is also activated in other lysosomal neurodegenerative disorders. Here, we describe that c-Abl activation contributes to the mechanisms of neuronal damage and death in NPA disease. Our data demonstrate that: 1) c-Abl is activated in-vitro as well as in-vivo NPA models; 2) imatinib, a clinical c-Abl inhibitor, reduces autophagy-lysosomal pathway alterations, restores autophagy flux, and lowers sphingomyelin accumulation in NPA patient fibroblasts and NPA neuronal models and 3) chronic treatment with nilotinib and neurotinib, two c-Abl inhibitors with differences in blood-brain barrier penetrance and target binding mode, show further benefits. While nilotinib treatment reduces neuronal death in the cerebellum and improves locomotor functions, neurotinib decreases glial activation, neuronal disorganization, and loss in hippocampus and cortex, as well as the cognitive decline of NPA mice. Our results support the participation of c-Abl signaling in NPA neurodegeneration and autophagy-lysosomal alterations, supporting the potential use of c-Abl inhibitors for the clinical treatment of NPA patients.

High-Throughput Cellular Thermal Shift Assay Using Acoustic Transfer of Protein Lysates.

Cellular thermal shift assay (CETSA) is a valuable method to confirm target engagement within a complex cellular environment, by detecting changes in a protein's thermal stability upon ligand binding. The classical CETSA method measures changes in the thermal stability of endogenous proteins using immunoblotting, which is low-throughput and laborious. Reverse-phase protein arrays (RPPAs) have been demonstrated as a detection modality for CETSA; however, the reported procedure requires manual processing steps that limit throughput and preclude screening applications. We developed a high-throughput CETSA using an acoustic RPPA (HT-CETSA-aRPPA) protocol that is compatible with 96- and 384-well microplates from start-to-finish, using low speed centrifugation to remove thermally destabilized proteins. The utility of HT-CETSA-aRPPA for guiding structure-activity relationship studies was demonstrated for inhibitors of lactate dehydrogenase A. Additionally, a collection of kinase inhibitors was screened to identify compounds that engage MEK1, a clinically relevant kinase target.

Defining clinical outcome pathways.

Here, we propose a broad concept of 'Clinical Outcome Pathways' (COPs), which are defined as a series of key molecular and cellular events that underlie therapeutic effects of drug molecules. We formalize COPs as a chain of the following events: molecular initiating event (MIE) â†’ intermediate event(s) â†’ clinical outcome. We illustrate the concept with COP examples both for primary and alternative (i.e., drug repurposing) therapeutic applications. We also describe the elucidation of COPs for several drugs of interest using the publicly accessible Reasoning Over Biomedical Objects linked in Knowledge-Oriented Pathways (ROBOKOP) biomedical knowledge graph-mining tool. We propose that broader use of COP uncovered with the help of biomedical knowledge graph mining will likely accelerate drug discovery and repurposing efforts.

NCATS Inxight Drugs: a comprehensive and curated portal for translational research.

The United States has a complex regulatory scheme for marketing drugs. Understanding drug regulatory status is a daunting task that requires integrating data from many sources from the United States Food and Drug Administration (FDA), US government publications, and other processes related to drug development. At NCATS, we created Inxight Drugs (https://drugs.ncats.io), a web resource that attempts to address this challenge in a systematic manner. NCATS Inxight Drugs incorporates and unifies a wealth of data, including those supplied by the FDA and from independent public sources. The database offers a substantial amount of manually curated literature data unavailable from other sources. Currently, the database contains 125 036 product ingredients, including 2566 US approved drugs, 6242 marketed drugs, and 9684 investigational drugs. All substances are rigorously defined according to the ISO 11238 standard to comply with existing regulatory standards for unique drug substance identification. A special emphasis was placed on capturing manually curated and referenced data on treatment modalities and semantic relationships between substances. A supplementary resource 'Novel FDA Drug Approvals' features regulatory details of newly approved FDA drugs. The database is regularly updated using NCATS Stitcher data integration tool that automates data aggregation and supports full data access through a RESTful API.

Validating ADME QSAR Models Using Marketed Drugs.

Problems with drug ADME are responsible for many clinical failures. By understanding the ADME properties of marketed drugs and modeling how chemical structure contributes to these inherent properties, we can help new projects reduce their risk profiles. Kinetic aqueous solubility, the parallel artificial membrane permeability assay (PAMPA), and rat liver microsomal stability constitute the Tier I ADME assays at the National Center for Advancing Translational Sciences (NCATS). Using recent data generated from in-house lead optimization Tier I studies, we update quantitative structure-activity relationship (QSAR) models for these three endpoints and validate in silico performance against a set of marketed drugs (balanced accuracies range between 71% and 85%). Improved models and experimental datasets are of direct relevance to drug discovery projects and, together with the prediction services that have been made publicly available at the ADME@NCATS web portal (https://opendata.ncats.nih.gov/adme/), provide important tools for the drug discovery community. The results are discussed in light of our previously reported ADME models and state-of-the-art models from scientific literature.Graphical Abstract[Figure: see text].

Discovery and Optimization of a 4-Aminopiperidine Scaffold for Inhibition of Hepatitis C Virus Assembly.

The majority of FDA-approved HCV therapeutics target the viral replicative machinery. An automated high-throughput phenotypic screen identified several small molecules as potent inhibitors of hepatitis C virus replication. Here, we disclose the discovery and optimization of a 4-aminopiperidine (4AP) scaffold targeting the assembly stages of the HCV life cycle. The original screening hit (1) demonstrates efficacy in the HCVcc assay but does not show potency prior to or during viral replication. Colocalization and infectivity studies indicate that the 4AP chemotype inhibits the assembly and release of infectious HCV. Compound 1 acts synergistically with FDA-approved direct-acting antiviral compounds Telaprevir and Daclatasvir, as well as broad spectrum antivirals Ribavirin and cyclosporin A. Following an SAR campaign, several derivatives of the 4AP series have been identified with increased potency against HCV, reduced in vitro toxicity, as well as improved in vitro and in vivo ADME properties.

Identification of Small Molecule Inhibitors of a Mir155 Transcriptional Reporter in Th17 Cells.

MicroRNA miR-155 is an important regulatory molecule in the immune system and is highly expressed and functional in Th17 cells, a subset of CD4+ T helper cells which are key players in autoimmune diseases. Small molecules that can modulate miR-155 may potentially provide new therapeutic avenues to inhibit Th17 cell-mediated autoimmune diseases. Here, we present a novel high-throughput screening assay using primary T cells from genetically engineered Mir155 reporter mice, and its use to screen libraries of small molecules to identify novel modulators of Th17 cell function. We have discovered a chemical series of (E)-1-(phenylsulfonyl)-2-styryl-1H-benzo[d] imidazoles as novel down-regulators of Mir155 reporter and cytokine expression in Th17 cells. In addition, we found that FDA approved antiparasitic agents belonging to the 'azole' family also down-regulate Mir155 reporter and cytokine expression in Th17 cells, and thus could potentially be repurposed to treat Th17-driven immunopathologies.

A high-throughput screening to identify small molecules that suppress huntingtin promoter activity or activate huntingtin-antisense promoter activity.

Huntington's disease (HD) is a neurodegenerative disorder caused by a CAG repeat expansion in exon 1 of huntingtin (HTT). While there are currently no disease-modifying treatments for HD, recent efforts have focused on the development of nucleotide-based therapeutics to lower HTT expression. As an alternative to siRNA or oligonucleotide methods, we hypothesized that suppression of HTT expression might be accomplished by small molecules that either (1) directly decrease HTT expression by suppressing HTT promoter activity or (2) indirectly decrease HTT expression by increasing the promoter activity of HTT-AS, the gene antisense to HTT that appears to inhibit expression of HTT. We developed and employed a high-throughput screen for modifiers of HTT and HTT-AS promoter activity using luminescent reporter HEK293 cells; of the 52,041 compounds tested, we identified 898 replicable hits. We used a rigorous stepwise approach to assess compound toxicity and the capacity of the compounds to specifically lower huntingtin protein in 5 different cell lines, including HEK293 cells, HD lymphoblastoid cells, mouse primary neurons, HD iPSCs differentiated into cortical-like neurons, and HD hESCs. We found no compounds which were able to lower huntingtin without lowering cell viability in all assays, though the potential efficacy of a few compounds at non-toxic doses could not be excluded. Our results suggest that more specific targets may facilitate a small molecule approach to HTT suppression.