High-throughput Screening Assay Research Articles

Acoustic droplet ejection facilitates cell-based high-throughput screenings using natural products

Natural Products (NPs) are one of the main sources for drug discovery. Many clinical drugs are NPs or NP-inspired compounds, and recently discovered New Chemical Entities (NCEs) of NPs are emerging as promising new drugs. High-Throughput Screening (HTS) of large sample sets or libraries has grown to be vital for the drug discovery field. Industrial-scale HTS of NP libraries can be limited due to the difficulties entailed in working with tiny extract volumes and the variability in viscosity of NP extracts. For these reasons, the implementation of new technologies to miniaturize different reagent volumes grows to be fundamental. Since Acoustic Droplet Ejection (ADE) emerged as a helpful tool in HTS campaigns for the transference of compound libraries. The aim of this work was to test the effectiveness of ADE for the dispensation of NP extract libraries in cell-based HTS assays.

A fine-tuned yeast surface-display/secretion platform enables the rapid discovery of neutralizing antibodies against Clostridioides difficile toxins

BackgroundNeutralizing antibody plays a key role in protecting hosts from invasive pathogens and their virulent components. Current high-throughput assays for antibody screening are based on binding activities. However, those antibodies with high affinity may not have neutralizing activities. Subsequent functionality assays are necessary to identify neutralizing antibodies from binders with high affinity to their target antigens, which is laborious and time-consuming. Therefore, a versatile platform that can rapidly identify antibodies with both high binding affinity and neutralizing activity is desired to curb future pandemics like COVID-19.ResultsIn this proof-of-concept study, we adapted Saccharomyces cerevisiae to either display human antibodies on the yeast surface or secrete soluble antibodies into the cultivation supernatant under a controllable ‘switch’ through different carbon source induced promoters. Initially, an engineered chimeric-bispecific Fab antibody, derived from humanized nanobodies against both Clostridioides difficile toxin A and B (TcdA and TcdB), was successfully expressed either on the yeast cell surface or in the culture medium with intact bioactivity, suggesting the applicability of our system in antibody display and secretion. Next, a combinatorial Fab library was constructed from B cells isolated from a convalescent patient with a high serological neutralizing titer against TcdB. Following three rounds of magnetic bead enrichment and one round of flow cytometry sorting, antibodies against TcdB were enriched efficiently. We then sorted out single binders with high binding affinity and induced them to express soluble antibodies in culture medium. The neutralizing activity of culture supernatant was analyzed using cell-based assay immediately. This way, we rapidly identified two unique neutralizers (out of seven binders) that can neutralize the cytotoxicity of TcdB.ConclusionThe antibody screening platform described here simplifies the neutralizing antibody discovery procedure and will be an attractive alternative for screening functional antibodies against infectious diseases.

Discovery of Nedd4 auto-ubiquitination inhibitors

E3 ubiquitin ligases are critical to the protein degradation pathway by catalyzing the final step in protein ubiquitination by mediating ubiquitin transfer from E2 enzymes to target proteins. Nedd4 is a HECT domain-containing E3 ubiquitin ligase with a wide range of protein targets, the dysregulation of which has been implicated in myriad pathologies, including cancer and Parkinson's disease. Towards the discovery of compounds disrupting the auto-ubiquitination activity of Nedd4, we developed and optimized a TR-FRET assay for high-throughput screening. Through selective screening of a library of potentially covalent compounds, compounds 25 and 81 demonstrated apparent IC50 values of 52 µM and 31 µM, respectively. Tandem mass spectrometry (MS/MS) analysis confirmed that 25 and 81 were covalently bound to Nedd4 cysteine residues (Cys182 and Cys867). In addition, 81 also adducted to Cys627. Auto-ubiquitination assays of Nedd4 mutants featuring alanine substitutions for each of these cysteines suggested that the mode of inhibition of these compounds occurs through blocking the catalytic Cys867. The discovery of these inhibitors could enable the development of therapeutics for various diseases caused by Nedd4 E3 ligase dysregulation.

The ToxCast pipeline: updates to curve-fitting approaches and database structure.

Introduction: The US Environmental Protection Agency Toxicity Forecaster (ToxCast) program makes in vitro medium- and high-throughput screening assay data publicly available for prioritization and hazard characterization of thousands of chemicals. The assays employ a variety of technologies to evaluate the effects of chemical exposure on diverse biological targets, from distinct proteins to more complex cellular processes like mitochondrial toxicity, nuclear receptor signaling, immune responses, and developmental toxicity. The ToxCast data pipeline (tcpl) is an open-source R package that stores, manages, curve-fits, and visualizes ToxCast data and populates the linked MySQL Database, invitrodb. Methods: Herein we describe major updates to tcpl and invitrodb to accommodate a new curve-fitting approach. The original tcpl curve-fitting models (constant, Hill, and gain-loss models) have been expanded to include Polynomial 1 (Linear), Polynomial 2 (Quadratic), Power, Exponential 2, Exponential 3, Exponential 4, and Exponential 5 based on BMDExpress and encoded by the R package dependency, tcplfit2. Inclusion of these models impacted invitrodb (beta version v4.0) and tcpl v3 in several ways: (1) long-format storage of generic modeling parameters to permit additional curve-fitting models; (2) updated logic for winning model selection; (3) continuous hit calling logic; and (4) removal of redundant endpoints as a result of bidirectional fitting. Results and discussion: Overall, the hit call and potency estimates were largely consistent between invitrodb v3.5 and 4.0. Tcpl and invitrodb provide a standard for consistent and reproducible curve-fitting and data management for diverse, targeted in vitro assay data with readily available documentation, thus enabling sharing and use of these data in myriad toxicology applications. The software and database updates described herein promote comparability across multiple tiers of data within the US Environmental Protection Agency CompTox Blueprint.

Drug Discovery for Adult Cardiomyocyte Regeneration: Opportunities and Challenges.

Significance: Cardiovascular disease is a major contributor to human mortality and morbidity. The cardiac tissue undergoes fibrotic healing after injury because of the limited regenerative capacity of adult mammalian cardiomyocyte (CM). Extensive research has been performed to identify therapeutic targets for CM regeneration, as the success of promoting adult human CM regeneration to repair the injured heart is considered the Holy Grail in the field. Recent Advances: To date, more than 30 target genes have been shown to regulate adult mammalian CM proliferation. More than 20 targets have been validated in adult mouse myocardial infarction (MI) model in a therapeutic setting. In this review, the translational efficacy readouts from 17 selected pharmaceutical targets are summarized, among which the Hippo-yes-associated protein (Yap) pathway is the most extensively investigated and fits the criteria for a promising target for pro-CM-regeneration therapy development. Critical Issues and Future Directions: As the pro-CM-regeneration potential of current drug treatment for cardiovascular patients is limited, to help identify and fill the gap between basic research and drug discovery in this specific field, details regarding target identification, validation in mouse MI models, high-throughput screening assay development, and preclinical in vivo efficacy model optimization are discussed. Finally, suggestions and recommendations are also provided to help establish a common guideline for in vivo translational studies for drug discovery focusing on CM regeneration. Antioxid. Redox Signal. 39, 1070-1087.

Optical-based microbubble for on-demand droplet release from static droplet array (SDA) for dispensing one droplet into one tube

Static droplet array (SDA) is a pivotal tool for high-capacity screening assays, yet extraction and collection the target droplets that contain unique analytes or cells from the SDA remains one major technical bottleneck that limits its broader application. Here we present an optical-based on-demand droplet release (OODR) system by incorporating a 1064 nm laser-responsive indium tin oxide (ITO) layer into a chamber array-based droplet microfluidic chip. By focusing the 1064 nm laser onto the ITO layer, microbubbles can be created via local heating to selectively push-out the droplets from the chamber. Then the released droplet is readily exported in a one-droplet-one-tube (ODOT) manner by the inherent capillary force into pipette tip. Releasing of the droplets containing fluorescein sodium demonstrated ∼100% successful rate (9 out of 6400 droplets were successfully released) and low residual (only ∼5% of the droplet volume remains in the chamber). White or fluorescence image-based releasing of single-cell-droplets directly after cell loading or multi-cells-droplets derived from on-chip single-cell cultivation for both E. coli and yeast cells further demonstrated the wide applicability of OODR. The present system is user-friendly and has the potential to be applied in various high-throughput screening assays, including single molecule/cell analysis, drug screening, and phenotype-based cell sorting.

Fluorescent probe for the detection of acetylcholinesterase inhibitors using high performance thin layer chromatography effect-directed assay in complex matrices

In recent years Bioautography has become an efficient bioassay for finding active compounds in complex matrices including extracts of; bacteria, plants or fungi. High Performance Thin Layer Chromatography (HPTLC) is a technique which allows effect-directive analysis (EDA) through the separation and identification of biologically active substances on a Thin Layer Chromatography (TLC) plate and can be run as a high throughput screening assay for enzymes. This paper presents a new bioautography method using a novel fluorescent probe derived from coumarin and its validation with Acetylcholinesterase (AChE) inhibition. This method combines the advantages of bioautography and the high sensitivity of fluorescence for detection. Combining these advantages, the limit of detection (LOD) and limit of quantification (LOQ) limits usually obtained with traditional chromophores has been reduced by three times. Therefore our new method has been applied on 14 mushroom extracts and we highlight a compound (variegatic acid) as a potentially new AChE inhibitor in X. Chrysenteron.

High-throughput bactericidal assays for monoclonal antibody screening against antimicrobial resistant Neisseria gonorrhoeae.

Neisseria gonorrhoeae (gonococcus) is an obligate human pathogen and the etiological agent of the sexually transmitted disease gonorrhea. The rapid rise in gonococcal resistance to all currently available antimicrobials has become a significant public health burden and the need to develop novel therapeutic and prophylactic tools is now a global priority. While high-throughput screening methods allowed rapid discovery of extremely potent monoclonal antibodies (mAbs) against viral pathogens, the field of bacteriology suffers from the lack of assays that allow efficient screening of large panels of samples. To address this point, we developed luminescence-based (L-ABA) and resazurin-based (R-ABA) antibody bactericidal assays that measure N. gonorrhoeae metabolic activity as a proxy of bacterial viability. Both L-ABA and R-ABA are applicable on the large scale for the rapid identification of bactericidal antibodies and were validated by conventional methods. Implementation of these approaches will be instrumental to the development of new medications and vaccines against N. gonorrhoeae and other bacterial pathogens to support the fight against antimicrobial resistance.

A high-throughput screening assay for silencing established HIV-1 macrophage infection identifies nucleoside analogs that perturb H3K9me3 on proviral genomes.

HIV-infected macrophages are long-lived cells that represent a barrier to functional cure. Additionally, low-level viral expression by central nervous system (CNS) macrophages contributes to neurocognitive deficits that develop despite antiretroviral therapy (ART). We recently identified H3K9me3 as an atypical epigenetic mark associated with chronic HIV infection in macrophages. Thus, strategies are needed to suppress HIV-1 expression in macrophages, but the unique myeloid environment and the responsible macrophage/CNS-tropic strains require cell/strain-specific approaches. Here, we generated an HIV-1 reporter virus from a CNS-derived strain with intact auxiliary genes expressing destabilized luciferase. We employed this reporter virus in polyclonal infection of primary human monocyte-derived macrophages (MDM) for a high-throughput screen (HTS) to identify compounds that suppress virus expression from established macrophage infection. Screening ~6,000 known drugs and compounds yielded 214 hits. A secondary screen with 10-dose titration identified 24 meeting criteria for HIV-selective activity. Using three replication-competent CNS-derived macrophage-tropic HIV-1 isolates and viral gene expression readout in MDM, we confirmed the effect of three purine analogs, nelarabine, fludarabine, and entecavir, showing the suppression of HIV-1 expression from established macrophage infection. Nelarabine inhibited the formation of H3K9me3 on HIV genomes in macrophages. Thus, this novel HTS assay can identify suppressors of HIV-1 transcription in established macrophage infection, such as nucleoside analogs and HDAC inhibitors, which may be linked to H3K9me3 modification. This screen may be useful to identify new metabolic and epigenetic agents that ameliorate HIV-driven neuroinflammation in people on ART or prevent viral recrudescence from macrophage reservoirs in strategies to achieve ART-free remission. IMPORTANCE Macrophages infected by HIV-1 are a long-lived reservoir and a barrier in current efforts to achieve HIV cure and also contribute to neurocognitive complications in people despite antiretroviral therapy (ART). Silencing HIV expression in these cells would be of great value, but the regulation of HIV-1 in macrophages differs from T cells. We developed a novel high-throughput screen for compounds that can silence established infection of primary macrophages, and identified agents that downregulate virus expression and alter provirus epigenetic profiles. The significance of this assay is the potential to identify new drugs that act in the unique macrophage environment on relevant viral strains, which may contribute to adjunctive treatment for HIV-associated neurocognitive disorders and/or prevent viral rebound in efforts to achieve ART-free remission or cure.

A New and Fast-Response Fluorescent Probe for Monitoring Hypochlorous Acid Derived from Myeloperoxidase.

Hypochlorous acid (HOCl) has been implicated in numerous pathologies associated with an inflammatory component, but its selective and sensitive detection in biological settings remains a challenge. In this report, imaging of HOCl was realized with a thiomorpholine-based probe as derivative of nitrobenzothiadiazole (NBD-S-TM). The fluorescence is based on photoinduced electron transfer by using nitrobenzothiadiazole core as a donor and thiomorpholine substituent as an acceptor. NBD-S-TM showed high sensitivity and a fast response to HOCl k = (2.6 ± 0.2) × 107 M-1s-1 with a 1:1 stoichiometry. The detection limit for HOCl was determined to be 60 nM. Furthermore, the desirable features of NBD-S-TM for the detection of HOCl in aqueous solutions, such as its reliability at physiological pH, rapid fluorescence response, and biocompatibility, enabled its application in the detection of HOCl in myeloperoxidase enzymatic system. Moreover, NBD-S-TM exhibited excellent selectivity and sensitivity for HOCl over other biologically relevant species, such as hydrogen peroxide and peroxynitrite. The fluorescent S-oxidized product (NBD-S-TSO) is only formed in the presence of HOCl. Probing with NBD-S-TM may be helpful to further the development of high throughput screening assays to monitor the activity of myeloperoxidase.

A Comparative Study on the Lysosomal Cation Channel TMEM175 Using Automated Whole-Cell Patch-Clamp, Lysosomal Patch-Clamp, and Solid Supported Membrane-Based Electrophysiology: Functional Characterization and High-Throughput Screening Assay Development.

The lysosomal cation channel TMEM175 is a Parkinson's disease-related protein and a promising drug target. Unlike whole-cell automated patch-clamp (APC), lysosomal patch-clamp (LPC) facilitates physiological conditions, but is not yet suitable for high-throughput screening (HTS) applications. Here, we apply solid supported membrane-based electrophysiology (SSME), which enables both direct access to lysosomes and high-throughput electrophysiological recordings. In SSME, ion translocation mediated by TMEM175 is stimulated using a concentration gradient at a resting potential of 0 mV. The concentration-dependent K+ response exhibited an I/c curve with two distinct slopes, indicating the existence of two conducting states. We measured H+ fluxes with a permeability ratio of PH/PK = 48,500, which matches literature findings from patch-clamp studies, validating the SSME approach. Additionally, TMEM175 displayed a high pH dependence. Decreasing cytosolic pH inhibited both K+ and H+ conductivity of TMEM175. Conversely, lysosomal pH and pH gradients did not have major effects on TMEM175. Finally, we developed HTS assays for drug screening and evaluated tool compounds (4-AP, Zn as inhibitors; DCPIB, arachidonic acid, SC-79 as enhancers) using SSME and APC. Additionally, we recorded EC50 data for eight blinded TMEM175 enhancers and compared the results across all three assay technologies, including LPC, discussing their advantages and disadvantages.

Integrating Concentration-Dependent Toxicity Data and Toxicokinetics To Inform Hepatotoxicity Response Pathways.

Failure of animal models to predict hepatotoxicity in humans has created a push to develop biological pathway-based alternatives, such as those that use in vitro assays. Public screening programs (e.g., ToxCast/Tox21 programs) have tested thousands of chemicals using in vitro high-throughput screening (HTS) assays. Developing pathway-based models for simple biological pathways, such as endocrine disruption, has proven successful, but development remains a challenge for complex toxicities like hepatotoxicity, due to the many biological events involved. To this goal, we aimed to develop a computational strategy for developing pathway-based models for complex toxicities. Using a database of 2171 chemicals with human hepatotoxicity classifications, we identified 157 out of 1600+ ToxCast/Tox21 HTS assays to be associated with human hepatotoxicity. Then, a computational framework was used to group these assays by biological target or mechanisms into 52 key event (KE) models of hepatotoxicity. KE model output is a KE score summarizing chemical potency against a hepatotoxicity-relevant biological target or mechanism. Grouping hepatotoxic chemicals based on the chemical structure revealed chemical classes with high KE scores plausibly informing their hepatotoxicity mechanisms. Using KE scores and supervised learning to predict in vivo hepatotoxicity, including toxicokinetic information, improved the predictive performance. This new approach can be a universal computational toxicology strategy for various chemical toxicity evaluations.

A Review on the Recent Applications of Deep Learning in Predictive Drug Toxicological Studies.

Drug toxicity prediction is an important step in ensuring patient safety during drug design studies. While traditional preclinical studies have historically relied on animal models to evaluate toxicity, recent advances in deep-learning approaches have shown great promise in advancing drug safety science and reducing animal use in preclinical studies. However, deep-learning-based approaches also face challenges in handling large biological data sets, model interpretability, and regulatory acceptance. In this review, we provide an overview of recent developments in deep-learning-based approaches for predicting drug toxicity, highlighting their potential advantages over traditional methods and the need to address their limitations. Deep-learning models have demonstrated excellent performance in predicting toxicity outcomes from various data sources such as chemical structures, genomic data, and high-throughput screening assays. The potential of deep learning for automated feature engineering is also discussed. This review emphasizes the need to address ethical concerns related to the use of deep learning in drug toxicity studies, including the reduction of animal use and ensuring regulatory acceptance. Furthermore, emerging applications of deep learning in drug toxicity prediction, such as predicting drug-drug interactions and toxicity in rare subpopulations, are highlighted. The integration of deep-learning-based approaches with traditional methods is discussed as a way to develop more reliable and efficient predictive models for drug safety assessment, paving the way for safer and more effective drug discovery and development. Overall, this review highlights the critical role of deep learning in predictive toxicology and drug safety evaluation, emphasizing the need for continued research and development in this rapidly evolving field. By addressing the limitations of traditional methods, leveraging the potential of deep learning for automated feature engineering, and addressing ethical concerns, deep-learning-based approaches have the potential to revolutionize drug toxicity prediction and improve patient safety in drug discovery and development.

High-throughput screening identifies cell cycle-associated signaling cascades that regulate a multienzyme glucosome assembly in human cells.

We have previously demonstrated that human liver-type phosphofructokinase 1 (PFK1) recruits other rate-determining enzymes in glucose metabolism to organize multienzyme metabolic assemblies, termed glucosomes, in human cells. However, it has remained largely elusive how glucosomes are reversibly assembled and disassembled to functionally regulate glucose metabolism and thus contribute to human cell biology. We developed a high-content quantitative high-throughput screening (qHTS) assay to identify regulatory mechanisms that control PFK1-mediated glucosome assemblies from stably transfected HeLa Tet-On cells. Initial qHTS with a library of pharmacologically active compounds directed following efforts to kinase-inhibitor enriched collections. Consequently, three compounds that were known to inhibit cyclin-dependent kinase 2, ribosomal protein S6 kinase and Aurora kinase A, respectively, were identified and further validated under high-resolution fluorescence single-cell microscopy. Subsequent knockdown studies using small-hairpin RNAs further confirmed an active role of Aurora kinase A on the formation of PFK1 assemblies in HeLa cells. Importantly, all the identified protein kinases here have been investigated as key signaling nodes of one specific cascade that controls cell cycle progression in human cells. Collectively, our qHTS approaches unravel a cell cycle-associated signaling network that regulates the formation of PFK1-mediated glucosome assembly in human cells.

Environmental contaminants modulate transport activity of zebrafish (Danio rerio) multidrug and toxin extrusion protein 3 (Mate3/Slc47a2.1)

Zebrafish Mate3 is one of six co-orthologs of human multidrug and toxin extrusion proteins. It is highly expressed in the kidneys, intestine, testes, and brain of males. Initial interaction studies showed its interaction with xenobiotic compounds, suggesting a role in the efflux of toxic compounds. In this study, we aimed to test various environmental contaminants for their interaction with zebrafish Mate3. We developed a stable zebrafish Mate3 cell line and optimized a high-throughput screening assay using DAPI and ASP+ as fluorescent model substrates. To gain insight into the structure and function of the Mate3 protein and relate these to the results of the DAPI and ASP+ transport measurements, we predicted its 3D structure using the AlphaFold2 algorithm. A 3D structure with high per residue confidence scores with 13 transmembrane segments (TMs) was obtained, with topology and mutual positioning characteristic of the Mate protein family in a shape open to the extracellular part. Molecular docking methods were used to identify DAPI and ASP+ binding sites on the surface and in the center of the protein cavity. Because our kinetics experiments combined with molecular docking indicated that there may be additional active sites in zebrafish Mate3, additional cytotoxicity experiments were performed and highly potent Mate3 interactors were identified from a set of 55 different environmental contaminants. Our results suggest that some of the identified interactors may be of environmental concern, as their interaction with Mate3 could lead to an impairment of its normal efflux function, making fish more sensitive to harmful substances commonly released into the aquatic environment. Finally, the quality of zebrafish Mate3 structures predicted by the AlphaFold2 algorithm opens up the possibility of successfully using this tool for in silico research on transport preferences of other Mate proteins.

Facile Method for High-throughput Identification of Stabilizing Mutations

Characterizing the effects of mutations on stability is critical for understanding the function and evolution of proteins and improving their biophysical properties. High throughput folding and abundance assays have been successfully used to characterize missense mutations associated with reduced stability. However, screening for increased thermodynamic stability is more challenging since such mutations are rarer and their impact on assay readout is more subtle. Here, a multiplex assay for high throughput screening of protein folding was developed by combining deep mutational scanning, fluorescence-activated cell sorting, and deep sequencing. By analyzing a library of 2000 variants of Adenylate kinase we demonstrate that the readout of the method correlates with stability and that mutants with up to 13 °C increase in thermal melting temperature could be identified with low false positive rate. The discovery of many stabilizing mutations also enabled the analysis of general substitution patterns associated with increased stability in Adenylate kinase. This high throughput method to identify stabilizing mutations can be combined with functional screens to identify mutations that improve both stability and activity.

Computational Construction of Toxicant Signaling Networks.

Humans and animals are regularly exposed to compounds that may have adverse effects on health. The Toxicity Forecaster (ToxCast) program was developed to use high throughput screening assays to quickly screen chemicals by measuring their effects on many biological end points. Many of these assays test for effects on cellular receptors and transcription factors (TFs), under the assumption that a toxicant may perturb normal signaling pathways in the cell. We hypothesized that we could reconstruct the intermediate proteins in these pathways that may be directly or indirectly affected by the toxicant, potentially revealing important physiological processes not yet tested for many chemicals. We integrate data from ToxCast with a human protein interactome to build toxicant signaling networks that contain physical and signaling protein interactions that may be affected as a result of toxicant exposure. To build these networks, we developed the EdgeLinker algorithm, which efficiently finds short paths in the interactome that connect the receptors to TFs for each toxicant. We performed multiple evaluations and found evidence suggesting that these signaling networks capture biologically relevant effects of toxicants. To aid in dissemination and interpretation, interactive visualizations of these networks are available at http://graphspace.org.

Nasal-PAMPA: A novel non-cell-based high throughput screening assay for prediction of nasal drug permeability

In nasal drug product development, screening studies are vital to select promising compounds or formulations. The Parallel Artificial Membrane Permeability Assay (PAMPA), a high throughput screening tool, has been applied to evaluate drug permeability across several barriers such as the skin or blood–brain barrier. Herein, a new nasal-PAMPA model was optimized to predict nasal permeability, using a biorelevant donor medium containing mucin. The apparent permeability (Papp) of 15 reference compounds was assessed in six different experimental conditions, and the most discriminating and predictive model was applied to a test drug (piroxicam) and mucoadhesive powder formulations loading the same drug. The model with 0.5% (w/v) mucin in the donor compartment and 2% (w/v) phosphatidylcholine in the lipid membrane accurately distinguished high and low permeable compounds. Additionally, it exhibited the highest correlation with permeation across human nasal epithelial cells, RPMI 2650 (R2 = 0.93). When applied to powder formulations, this model was sensitive to the presence of mucoadhesive excipients and the drug solid state.Overall, the nasal-PAMPA model was more rapid than cell-based assays, without requiring specialized training or equipment, showing to be a promising in vitro tool that can be applied in drug and formulation screening for nasal delivery.

Enabling programmable dynamic DNA chemistry using small-molecule DNA binders

The binding of small molecules to the double helical structure of DNA, through either intercalation or minor groove binding, may significantly alter the stability and functionality of DNA, which is a fundamental basis for many therapeutic and sensing applications. Here, we report that small-molecule DNA binders can also be used to program reaction pathways of a dynamic DNA reaction, where DNA strand displacement can be tuned quantitatively according to the affinity, charge, and concentrations of a given DNA binder. The binder-induced nucleic acid strand displacement (BIND) thus enables innovative technologies to accelerate the discovery and characterization of bioactive small molecules. Specifically, we demonstrate the comprehensive characterization of existing and newly discovered DNA binders, where critical parameters for binding affinity and sequence selectivity can be obtained in a single, unbiased molecular platform without the need for any specialized equipment. We also engineer a tandem BIND system as a high-throughput screening assay for discovering DNA binders, through which 8 DNA binders were successfully discovered from a library of 700 compounds.

Identification of 2-Sulfonyl/Sulfonamide Pyrimidines as Covalent Inhibitors of WRN Using a Multiplexed High-Throughput Screening Assay.

Werner syndrome protein (WRN) is a multifunctional enzyme with helicase, ATPase, and exonuclease activities that are necessary for numerous DNA-related transactions in the human cell. Recent studies identified WRN as a synthetic lethal target in cancers characterized by genomic microsatellite instability resulting from defects in DNA mismatch repair pathways. WRN's helicase activity is essential for the viability of these high microsatellite instability (MSI-H) cancers and thus presents a therapeutic opportunity. To this end, we developed a multiplexed high-throughput screening assay that monitors exonuclease, ATPase, and helicase activities of full-length WRN. This screening campaign led to the discovery of 2-sulfonyl/sulfonamide pyrimidine derivatives as novel covalent inhibitors of WRN helicase activity. The compounds are specific for WRN versus other human RecQ family members and show competitive behavior with ATP. Examination of these novel chemical probes established the sulfonamide NH group as a key driver of compound potency. One of the leading compounds, H3B-960, showed consistent activities in a range of assays (IC50 = 22 nM, KD = 40 nM, KI = 32 nM), and the most potent compound identified, H3B-968, has inhibitory activity IC50 ∼ 10 nM. These kinetic properties trend toward other known covalent druglike molecules. Our work provides a new avenue for screening WRN for inhibitors that may be adaptable to different therapeutic modalities such as targeted protein degradation, as well as a proof of concept for the inhibition of WRN helicase activity by covalent molecules.