RALDH1 Inhibition Shows Immunotherapeutic Efficacy in Hepatocellular Carcinoma.

Globally, hepatocellular carcinoma (HCC) is one of the most commonly diagnosed cancers and a leading cause of cancer-related death. We previously identified an immune evasion pathway whereby tumor cells produce retinoic acid (RA) to promote differentiation of intratumoral monocytes into protumor macrophages. Retinaldehyde dehydrogenase 1 (RALDH1), RALDH2, and RALDH3 are the three isozymes that catalyze RA biosynthesis. In this study, we have identified RALDH1 as the key driver of RA production in HCC and demonstrated the efficacy of RALDH1-selective inhibitors (Raldh1-INH) in suppressing RA production by HCC cells. Raldh1-INH restrained tumor growth in multiple mouse models of HCC by reducing the number and tumor-supporting functions of intratumoral macrophages as well as increasing T-cell infiltration and activation within tumors. Raldh1-INH also displayed favorable pharmacokinetic, pharmacodynamic, and toxicity profiles in mice thereby establishing them as promising new drug candidates for HCC immunotherapy.

Lies and Liabilities: Computational Assessment of High-Throughput Screening Hits to Identify Artifact Compounds.

Hits from high-throughput screening (HTS) of chemical libraries are often false positives due to their interference with assay detection technology. In response, we generated the largest publicly available library of chemical liabilities and developed "Liability Predictor," a free web tool to predict HTS artifacts. More specifically, we generated, curated, and integrated HTS data sets for thiol reactivity, redox activity, and luciferase (firefly and nano) activity and developed and validated quantitative structure-interference relationship (QSIR) models to predict these nuisance behaviors. The resulting models showed 58-78% external balanced accuracy for 256 external compounds per assay. QSIR models developed and validated herein identify nuisance compounds among experimental hits more reliably than do popular PAINS filters. Both the models and the curated data sets were implemented in "Liability Predictor," publicly available at https://liability.mml.unc.edu/. "Liability Predictor" may be used as part of chemical library design or for triaging HTS hits.

Discovering selective antiferroptotic inhibitors of the 15LOX/PEBP1 complex noninterfering with biosynthesis of lipid mediators.

Programmed ferroptotic death eliminates cells in all major organs and tissues with imbalanced redox metabolism due to overwhelming iron-catalyzed lipid peroxidation under insufficient control by thiols (Glutathione (GSH)). Ferroptosis has been associated with the pathogenesis of major chronic degenerative diseases and acute injuries of the brain, cardiovascular system, liver, kidneys, and other organs, and its manipulation offers a promising new strategy for anticancer therapy. This explains the high interest in designing new small-molecule-specific inhibitors against ferroptosis. Given the role of 15-lipoxygenase (15LOX) association with phosphatidylethanolamine (PE)-binding protein 1 (PEBP1) in initiating ferroptosis-specific peroxidation of polyunsaturated PE, we propose a strategy of discovering antiferroptotic agents as inhibitors of the 15LOX/PEBP1 catalytic complex rather than 15LOX alone. Here we designed, synthesized, and tested a customized library of 26 compounds using biochemical, molecular, and cell biology models along with redox lipidomic and computational analyses. We selected two lead compounds, FerroLOXIN-1 and 2, which effectively suppressed ferroptosis in vitro and in vivo without affecting the biosynthesis of pro-/anti-inflammatory lipid mediators in vivo. The effectiveness of these lead compounds is not due to radical scavenging or iron-chelation but results from their specific mechanisms of interaction with the 15LOX-2/PEBP1 complex, which either alters the binding pose of the substrate [eicosatetraenoyl-PE (ETE-PE)] in a nonproductive way or blocks the predominant oxygen channel thus preventing the catalysis of ETE-PE peroxidation. Our successful strategy may be adapted to the design of additional chemical libraries to reveal new ferroptosis-targeting therapeutic modalities.

Quantitative Bioactivity Signatures of Dietary Supplements and Natural Products.

Dietary supplements and natural products are often marketed as safe and effective alternatives to conventional drugs, but their safety and efficacy are not well regulated. To address the lack of scientific data in these areas, we assembled a collection of Dietary Supplements and Natural Products (DSNP), as well as Traditional Chinese Medicinal (TCM) plant extracts. These collections were then profiled in a series of in vitro high-throughput screening assays, including a liver cytochrome p450 enzyme panel, CAR/PXR signaling pathways, and P-glycoprotein (P-gp) transporter assay activities. This pipeline facilitated the interrogation of natural product-drug interaction (NaPDI) through prominent metabolizing pathways. In addition, we compared the activity profiles of the DSNP/TCM substances with those of an approved drug collection (the NCATS Pharmaceutical Collection or NPC). Many of the approved drugs have well-annotated mechanisms of action (MOAs), while the MOAs for most of the DSNP and TCM samples remain unknown. Based on the premise that compounds with similar activity profiles tend to share similar targets or MOA, we clustered the library activity profiles to identify overlap with the NPC to predict the MOAs of the DSNP/TCM substances. Our results suggest that many of these substances may have significant bioactivity and potential toxicity, and they provide a starting point for further research on their clinical relevance.

Venglustat Inhibits Protein N-Terminal Methyltransferase 1 in a Substrate-Competitive Manner.

Venglustat is a known allosteric inhibitor for ceramide glycosyltransferase, investigated in diseases caused by lysosomal dysfunction. Here, we identified venglustat as a potent inhibitor (IC50 = 0.42 µM) of protein N-terminal methyltransferase 1 (NTMT1) by screening 58,130 compounds. Furthermore, venglustat exhibited selectivity for NTMT1 over 36 other methyltransferases. The crystal structure of NTMT1-venglustat and inhibition mechanism revealed that venglustat competitively binds at the peptide substrate site. Meanwhile, venglustat potently inhibited protein N-terminal methylation levels in cells (IC50 = 0.5 µM). Preliminary structure-activity relationships indicated that the quinuclidine and fluorophenyl parts of venglustat are important for NTMT1 inhibition. In summary, we confirmed that venglustat is a bona fide NTMT1 inhibitor, which would advance the study on the biological roles of NTMT1. Additionally, this is the first disclosure of NTMT1 as a new molecular target of venglustat, which would cast light on its mechanism of action to guide the clinical investigations.

A platform of assays for the discovery of anti-Zika small-molecules with activity in a 3D-bioprinted outer-blood-retina model.

The global health emergency posed by the outbreak of Zika virus (ZIKV), an arthropod-borne flavivirus causing severe neonatal neurological conditions, has subsided, but there continues to be transmission of ZIKV in endemic regions. As such, there is still a medical need for discovering and developing therapeutical interventions against ZIKV. To identify small-molecule compounds that inhibit ZIKV disease and transmission, we screened multiple small-molecule collections, mostly derived from natural products, for their ability to inhibit wild-type ZIKV. As a primary high-throughput screen, we used a viral cytopathic effect (CPE) inhibition assay conducted in Vero cells that was optimized and miniaturized to a 1536-well format. Suitably active compounds identified from the primary screen were tested in a panel of orthogonal assays using recombinant Zika viruses, including a ZIKV Renilla luciferase reporter assay and a ZIKV mCherry reporter system. Compounds that were active in the wild-type ZIKV inhibition and ZIKV reporter assays were further evaluated for their inhibitory effects against other flaviviruses. Lastly, we demonstrated that wild-type ZIKV is able to infect a 3D-bioprinted outer-blood-retina barrier tissue model and disrupt its barrier function, as measured by electrical resistance. One of the identified compounds (3-Acetyl-13-deoxyphomenone, NCGC00380955) was able to prevent the pathological effects of the viral infection on this clinically relevant ZIKV infection model.

Cross-Platform Bayesian Optimization System for Autonomous Biological Assay Development.

Current high-throughput screening assay optimization is often a manual and time-consuming process, even when utilizing design-of-experiment approaches. A cross-platform, Cloud-based Bayesian optimization-based algorithm was developed as part of the National Center for Advancing Translational Sciences (NCATS) ASPIRE (A Specialized Platform for Innovative Research Exploration) Initiative to accelerate preclinical drug discovery. A cell-free assay for papain enzymatic activity was used as proof of concept for biological assay development and system operationalization. Compared with a brute-force approach that sequentially tested all 294 assay conditions to find the global optimum, the Bayesian optimization algorithm could find suitable conditions for optimal assay performance by testing 21 assay conditions on average, with up to 20 conditions being tested simultaneously, as confirmed by repeated simulation. The algorithm could achieve a sevenfold reduction in costs for lab supplies and high-throughput experimentation runtime, all while being controlled from a remote site through a secure connection. Based on this proof of concept, this technology is expected to be applied to more complex biological assays and automated chemistry reaction screening at NCATS, and should be transferable to other institutions.

Kinetic and structural investigations of novel inhibitors of human epithelial 15-lipoxygenase-2.

Human epithelial 15-lipoxygenase-2 (h15-LOX-2, ALOX15B) is expressed in many tissues and has been implicated in atherosclerosis, cystic fibrosis and ferroptosis. However, there are few reported potent/selective inhibitors that are active ex vivo. In the current work, we report newly discovered molecules that are more potent and structurally distinct from our previous inhibitors, MLS000545091 and MLS000536924 (Jameson et al, PLoS One, 2014, 9, e104094), in that they contain a central imidazole ring, which is substituted at the 1-position with a phenyl moiety and with a benzylthio moiety at the 2-position. The initial three molecules were mixed-type, non-reductive inhibitors, with IC50 values of 0.34 ±â€¯0.05 µM for MLS000327069, 0.53 ±â€¯0.04 µM for MLS000327186 and 0.87 ±â€¯0.06 µM for MLS000327206 and greater than 50-fold selectivity versus h5-LOX, h12-LOX, h15-LOX-1, COX-1 and COX-2. A small set of focused analogs was synthesized to demonstrate the validity of the hits. In addition, a binding model was developed for the three imidazole inhibitors based on computational docking and a co-structure of h15-LOX-2 with MLS000536924. Hydrogen/deuterium exchange (HDX) results indicate a similar binding mode between MLS000536924 and MLS000327069, however, the latter restricts protein motion of helix-α2 more, consistent with its greater potency. Given these results, we designed, docked, and synthesized novel inhibitors of the imidazole scaffold and confirmed our binding mode hypothesis. Importantly, four of the five inhibitors mentioned above are active in an h15-LOX-2/HEK293 cell assay and thus they could be important tool compounds in gaining a better understanding of h15-LOX-2's role in human biology. As such, a suite of similar pharmacophores that target h15-LOX-2 both in vitro and ex vivo are presented in the hope of developing them as therapeutic agents.

Small Molecule Inhibitors of Activation-Induced Deaminase Decrease Class Switch Recombination in B Cells.

Activation-induced deaminase (AID) not only mutates DNA within the immunoglobulin loci to generate antibody diversity, but it also promotes development of B cell lymphomas. To tame this mutagen, we performed a quantitative high-throughput screen of over 90 000 compounds to see if AID activity could be mitigated. The enzymatic activity was assessed in biochemical assays to detect cytosine deamination and in cellular assays to measure class switch recombination. Three compounds showed promise via inhibition of switching in a transformed B cell line and in murine splenic B cells. These compounds have similar chemical structures, which suggests a shared mechanism of action. Importantly, the inhibitors blocked AID, but not a related cytosine DNA deaminase, APOBEC3B. We further determined that AID was continually expressed for several days after B cell activation to induce switching. This first report of small molecules that inhibit AID can be used to gain regulatory control over base editors.

A target-agnostic screen identifies approved drugs to stabilize the endoplasmic reticulum-resident proteome.

Endoplasmic reticulum (ER) dysregulation is associated with pathologies including neurodegenerative, muscular, and diabetic conditions. Depletion of ER calcium can lead to the loss of resident proteins in a process termed exodosis. To identify compounds that attenuate the redistribution of ER proteins under pathological conditions, we performed a quantitative high-throughput screen using the Gaussia luciferase (GLuc)-secreted ER calcium modulated protein (SERCaMP) assay, which monitors secretion of ER-resident proteins triggered by calcium depletion. We identify several clinically used drugs, including bromocriptine, and further characterize them using assays to measure effects on ER calcium, ER stress, and ER exodosis. Bromocriptine elicits protective effects in cell-based models of exodosis as well as in vivo models of stroke and diabetes. Bromocriptine analogs with reduced dopamine receptor activity retain similar efficacy in stabilizing the ER proteome, indicating a non-canonical mechanism of action. This study describes a strategic approach to identify small-molecule drugs capable of improving ER proteostasis in human disease conditions.

Discovery and Optimization of 2H-1λ2-Pyridin-2-one Inhibitors of Mutant Isocitrate Dehydrogenase 1 for the Treatment of Cancer.

Neomorphic mutations in isocitrate dehydrogenase 1 (IDH1) are oncogenic for a number of malignancies, primarily low-grade gliomas and acute myeloid leukemia. We report a medicinal chemistry campaign around a 7,7-dimethyl-7,8-dihydro-2H-1λ2-quinoline-2,5(6H)-dione screening hit against the R132H and R132C mutant forms of isocitrate dehydrogenase (IDH1). Systematic SAR efforts produced a series of potent pyrid-2-one mIDH1 inhibitors, including the atropisomer (+)-119 (NCATS-SM5637, NSC 791985). In an engineered mIDH1-U87-xenograft mouse model, after a single oral dose of 30 mg/kg, 16 h post dose, between 16 and 48 h, (+)-119 showed higher tumoral concentrations that corresponded to lower 2-HG concentrations, when compared with the approved drug AG-120 (ivosidenib).

The Tox21 10K Compound Library: Collaborative Chemistry Advancing Toxicology.

Since 2009, the Tox21 project has screened ∼8500 chemicals in more than 70 high-throughput assays, generating upward of 100 million data points, with all data publicly available through partner websites at the United States Environmental Protection Agency (EPA), National Center for Advancing Translational Sciences (NCATS), and National Toxicology Program (NTP). Underpinning this public effort is the largest compound library ever constructed specifically for improving understanding of the chemical basis of toxicity across research and regulatory domains. Each Tox21 federal partner brought specialized resources and capabilities to the partnership, including three approximately equal-sized compound libraries. All Tox21 data generated to date have resulted from a confluence of ideas, technologies, and expertise used to design, screen, and analyze the Tox21 10K library. The different programmatic objectives of the partners led to three distinct, overlapping compound libraries that, when combined, not only covered a diversity of chemical structures, use-categories, and properties but also incorporated many types of compound replicates. The history of development of the Tox21 "10K" chemical library and data workflows implemented to ensure quality chemical annotations and allow for various reproducibility assessments are described. Cheminformatics profiling demonstrates how the three partner libraries complement one another to expand the reach of each individual library, as reflected in coverage of regulatory lists, predicted toxicity end points, and physicochemical properties. ToxPrint chemotypes (CTs) and enrichment approaches further demonstrate how the combined partner libraries amplify structure-activity patterns that would otherwise not be detected. Finally, CT enrichments are used to probe global patterns of activity in combined ToxCast and Tox21 activity data sets relative to test-set size and chemical versus biological end point diversity, illustrating the power of CT approaches to discern patterns in chemical-activity data sets. These results support a central premise of the Tox21 program: A collaborative merging of programmatically distinct compound libraries would yield greater rewards than could be achieved separately.

Therapeutic candidates for the Zika virus identified by a high-throughput screen for Zika protease inhibitors.

When Zika virus emerged as a public health emergency there were no drugs or vaccines approved for its prevention or treatment. We used a high-throughput screen for Zika virus protease inhibitors to identify several inhibitors of Zika virus infection. We expressed the NS2B-NS3 Zika virus protease and conducted a biochemical screen for small-molecule inhibitors. A quantitative structure-activity relationship model was employed to virtually screen ∼138,000 compounds, which increased the identification of active compounds, while decreasing screening time and resources. Candidate inhibitors were validated in several viral infection assays. Small molecules with favorable clinical profiles, especially the five-lipoxygenase-activating protein inhibitor, MK-591, inhibited the Zika virus protease and infection in neural stem cells. Members of the tetracycline family of antibiotics were more potent inhibitors of Zika virus infection than the protease, suggesting they may have multiple mechanisms of action. The most potent tetracycline, methacycline, reduced the amount of Zika virus present in the brain and the severity of Zika virus-induced motor deficits in an immunocompetent mouse model. As Food and Drug Administration-approved drugs, the tetracyclines could be quickly translated to the clinic. The compounds identified through our screening paradigm have the potential to be used as prophylactics for patients traveling to endemic regions or for the treatment of the neurological complications of Zika virus infection.

SCAM Detective: Accurate Predictor of Small, Colloidally Aggregating Molecules.

Small, colloidally aggregating molecules (SCAMs) are the most common source of false positives in high-throughput screening (HTS) campaigns. Although SCAMs can be experimentally detected and suppressed by the addition of detergent in the assay buffer, detergent sensitivity is not routinely monitored in HTS. Computational methods are thus needed to flag potential SCAMs during HTS triage. In this study, we have developed and rigorously validated quantitative structure-interference relationship (QSIR) models of detergent-sensitive aggregation in several HTS campaigns under various assay conditions and screening concentrations. In particular, we have modeled detergent-sensitive aggregation in an AmpC ß-lactamase assay, the preferred HTS counter-screen for aggregation, as well as in another assay that measures cruzain inhibition. Our models increase the accuracy of aggregation prediction by ∼53% in the ß-lactamase assay and by ∼46% in the cruzain assay compared to previously published methods. We also discuss the importance of both assay conditions and screening concentrations in the development of QSIR models for various interference mechanisms besides aggregation. The models developed in this study are publicly available for fast prediction within the SCAM detective web application (https://scamdetective.mml.unc.edu/).

Optimization of High-Throughput Methyltransferase Assays for the Discovery of Small Molecule Inhibitors.

Methyltransferases (MTases) play diverse roles in cellular processes. Aberrant methylation levels have been implicated in many diseases, indicating the need for the identification and development of small molecule inhibitors for each MTase. Specific inhibitors can serve as probes to investigate the function and validate therapeutic potential for the respective MTase. High-throughput screening (HTS) is a powerful method to identify initial hits for further optimization. Here, we report the development of a fluorescence-based MTase assay and compare this format with the recently developed MTase-Glo luminescence assay for application in HTS. Using protein N-terminal methyltransferase 1 (NTMT1) as a model system, we miniaturized to 1536-well quantitative HTS format. Through a pilot screen of 1428 pharmacologically active compounds and subsequent validation, we discovered that MTase-Glo produced lower false positive rates than the fluorescence-based MTase assay. Nevertheless, both assays displayed robust performance along with low reagent requirements and can potentially be employed as general HTS formats for the discovery of inhibitors for any MTase.

Discovery and Structure-Activity Relationship Study of (Z)-5-Methylenethiazolidin-4-one Derivatives as Potent and Selective Pan-phosphatidylinositol 5-Phosphate 4-Kinase Inhibitors.

Due to their role in many important signaling pathways, phosphatidylinositol 5-phosphate 4-kinases (PI5P4Ks) are attractive targets for the development of experimental therapeutics for cancer, metabolic, and immunological disorders. Recent efforts to develop small molecule inhibitors for these lipid kinases resulted in compounds with low- to sub-micromolar potencies. Here, we report the identification of CVM-05-002 using a high-throughput screen of PI5P4Kα against our in-house kinase inhibitor library. CVM-05-002 is a potent and selective inhibitor of PI5P4Ks, and a 1.7 Å X-ray structure reveals its binding interactions in the ATP-binding pocket. Further investigation of the structure-activity relationship led to the development of compound 13, replacing the rhodanine-like moiety present in CVM-05-002 with an indole, a potent pan-PI5P4K inhibitor with excellent kinome-wide selectivity. Finally, we employed isothermal cellular thermal shift assays (CETSAs) to demonstrate the effective cellular target engagement of PI5P4Kα and -ß by the inhibitors in HEK 293T cells.

Structure-Activity Relationship Study of Covalent Pan-phosphatidylinositol 5-Phosphate 4-Kinase Inhibitors.

Phosphatidylinositol 5-phosphate 4-kinases (PI5P4Ks) are important molecular players in a variety of diseases, such as cancer. Currently available PI5P4K inhibitors are reversible small molecules, which may lack selectivity and sufficient cellular on-target activity. In this study, we present a new class of covalent pan-PI5P4K inhibitors with potent biochemical and cellular activity. Our designs are based on THZ-P1-2, a covalent PI5P4K inhibitor previously developed in our lab. Here, we report further structure-guided optimization and structure-activity relationship (SAR) study of this scaffold, resulting in compound 30, which retained biochemical and cellular potency, while demonstrating a significantly improved selectivity profile. Furthermore, we confirm that the inhibitors show efficient binding affinity in the context of HEK 293T cells using isothermal CETSA methods. Taken together, compound 30 represents a highly selective pan-PI5P4K covalent lead molecule.

Applications of Differential Scanning Fluorometry and Related Technologies in Characterization of Protein-Ligand Interactions.

Differential scanning fluorometry (DSF) is an efficient and high-throughput method to analyze protein stability, as well as detect ligand interactions through perturbations of the protein's melting temperature. The method monitors protein unfolding by observing the fluorescence changes of a sample, whether through an environmentally sensitive fluorophore or by intrinsic protein fluorescence, while a temperature gradient is applied. Here, we describe in detail how to develop and optimize DSF assays to identify protein-ligand interactions while exploring different buffer and additive conditions. Analysis of the data and further applications of the method are also discussed.

Novel Consensus Architecture To Improve Performance of Large-Scale Multitask Deep Learning QSAR Models.

Advances in the development of high-throughput screening and automated chemistry have rapidly accelerated the production of chemical and biological data, much of them freely accessible through literature aggregator services such as ChEMBL and PubChem. Here, we explore how to use this comprehensive mapping of chemical biology space to support the development of large-scale quantitative structure-activity relationship (QSAR) models. We propose a new deep learning consensus architecture (DLCA) that combines consensus and multitask deep learning approaches together to generate large-scale QSAR models. This method improves knowledge transfer across different target/assays while also integrating contributions from models based on different descriptors. The proposed approach was validated and compared with proteochemometrics, multitask deep learning, and Random Forest methods paired with various descriptors types. DLCA models demonstrated improved prediction accuracy for both regression and classification tasks. The best models together with their modeling sets are provided through publicly available web services at https://predictor.ncats.io .

Testing for drug-human serum albumin binding using fluorescent probes and other methods.

INTRODUCTION: Drug plasma protein binding remains highly relevant to research and drug development, making the assessment and profiling of compound affinity to plasma proteins essential to drug discovery efforts. Although there are a number of fully-characterized methods, they lack the throughput to handle large numbers of compounds. As the evaluation of adsorption, distribution, metabolism, and excretion is addressed earlier in the drug development timeline, the need for higher-throughput methods has grown. Areas Covered: This review will highlight recent developments on methods for profiling drug plasma binding, with an emphasis on fluorescent probes and emerging high-throughput methodologies. Expert Opinion: There have been a number of high-throughput assays developed in recent years to meet the scaled up demands for compound profiling. Ultimately, the selection of assay technology relies on a number of factors, such as capabilities of the laboratory and the breadth and amount of data required. Fluorescent probe displacement assays are highly flexible and amenable to high-throughput screening, easily scaling up to handle large compound libraries. Recent developments in fluorescence technologies, such as homogenous time-resolved fluorescence and probes utilizing the aggregation-induced emission effect, have improved the sensitivity of these assays. Other technologies, such as microscale thermophoresis and quantitative structure-activity relationship modeling, are gaining popularity as alternative techniques for drug plasma protein binding characterization.