High-throughput Drug Discovery Research Articles

Abstract 6790: Breaking barriers: A high-throughput 3D drug discovery platform for ovarian cancer

Abstract Background: Ovarian Cancer (OVCA) is a formidable challenge in oncology and remains the most lethal gynecologic malignancy with many cases (~80%) diagnosed at a late stage with an equally high rate of recurrence. Yet, no established OVCA models exist that faithfully recapitulate the biological complexity of metastatic OVCA. This multidisciplinary team developed a new in vitro high-throughput model that maintains the characteristics of the patient’s tumor including resident immune cells. Key breakthroughs include long term (>21 day) culture of patient-derived microtumors, a functional and perfusable microgel medium (Liquid Like Solids - LLS™), microplates with controlled “pumpless” perfusion of culture media (Darcy Plates™), and integrated in situ imaging. Methods: We designed, fabricated, and validated a new 3D culture device in the standard SBS microplate format (Darcy Plate) that integrates in situ microscopy and perfusion through a bio-conjugated microgel bed (LLS). Patient tumors were collected during debulking surgery, micronized into 1 µl microtumors, suspended in LLS, and plated into the 48-well Darcy Plate. Viability and proliferation were assessed over 21 days in situ using a standard LIVE/DEAD™ kit and EDU staining, respectively. Epithelial OVCA cells and immune cells were identified with immunofluorescence microscopy. Results: Optimal media conditions (HPLM media with 10% FBS, 1% Pen/Strep, 2.5 mg L−1 Amphotericin B, 10 mM HEPES, 0.5 µM A83-01 -TGF-β inhibitor-, and ITS) and perfusion flow rates (100 µl/day per well) were identified that resulted in outstanding cell viability after 21 days (~100% - no detectable cell death using LIVE/DEAD™). PAX8 nuclear expression, a marker for epithelial metastatic OVCA, was retained. EDU staining confirmed cell proliferation and CD45 staining revealed retention of viable immune cells on and within the microtumor at 21 days. Drug testing to evaluate tumor response to chemotherapeutic agents, carboplatin, and emerging targeted therapies was performed by dosing the feed-wells at different concentrations and evaluating cell death through LIVE/DEAD imaging after 5 days of treatment. Conclusions: OVCA is a challenging disease with understudied biological complexity and extensive metastatic involvement. This study demonstrates that drug screening with 3D microtumors has important clinical implications and provides a unique opportunity to evaluate drug responses and personalized treatment strategies. These patient-derived microtumors retain crosstalk between diverse cell populations and the tumor microenvironment, which increases the likelihood of identifying effective therapies and drug candidates. This system retains patient-specific tumor heterogeneity and microenvironmental complexity of OVCA, offering a promising platform for drug screening, high-throughput assays, biomarker discovery, and ultimately improving treatment outcomes. Citation Format: Erin George, Diego I. Pedro, Alfonso Pepe, Angie M. Rivera, Ryan A. Smolchek, Jack E. Famiglietti, W. Gregory Sawyer. Breaking barriers: A high-throughput 3D drug discovery platform for ovarian cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 6790.

Abstract 2060: Automation of 3D cancer spheroid assay for compound screening

Abstract Finding efficient drug combinations to treat cancer patients is critical for therapy success. Accordingly, there is a critical need to develop methods for efficient testing drug efficacy to discover new therapeutic targets. 3D cancer models are highly valuable tools for cancer research and drug development. However, the complexity of performing 3D assays remains a hurdle for adopting these methods for compound screening. To alleviate the bottlenecks that come with labor-intensive manual protocols we developed cell culture automation methods using CellXpress.ai instrument. The instrument enables automation of 2D or 3D culture for prolonged complex workflows. The CellXpress.ai provides automated plating, passaging, media exchanges, monitoring organoids, alone with compound treatment and the end point assays with high content image analysis. In the present study we describe full automation of imaging, analysis, and cell culture process which enables scaling up complex 3D cell-based assays and compound screening. As an example of 3D protocol, we automated culture and imaging of colorectal cancer 3D spheroids formed from HCT116 cell line in U-shape low attachment plates. HCT116 cells were expanded in 2D, then spheroids were formed after automated dispensing of cell suspension into U-shape 96 or 384 plates. After 48h spheroids were treated with 12 anti-cancer compounds, at multiple concentrations for 3-5 days, then stained and imaged. Cell plating, compound additions, media exchange, and staining were performed automatically by CellXpressAI instrument. During the culture spheroids were monitored using transmitted light, with immediate analysis of phenotypic changes, including inhibition of growth or spheroid disintegration. For endpoint assay spheroids were stained with combination of Hoechst nuclear stain and viability dyes Calcein AM and EtHD, then imaged, and analyzed for multiple read-outs including spheroid size, marker intensities, and live-dead cell scoring. We observed concentration-dependent inhibition of spheroid growth and cell death in response to anti-cancer compounds and evaluated effective compound concentrations for cytotoxic or cytostatic effects. Cell culture process automation for 3D assays, powered by imaging and image analysis has a potential to bring 3D biology into another level, allowing to increase throughput and reproducibility, and enabling variety of high throughput drug discovery and precision medicine applications. Citation Format: Oksana Sirenko, Angeline Lim, Astrid Michlmayr, Zhisong Tong, Emilie Keidel, Felix Spira. Automation of 3D cancer spheroid assay for compound screening [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2060.

A Zebrafish-Based Platform for High-Throughput Epilepsy Modeling and Drug Screening in F0.

The zebrafish model has emerged as a reference tool for phenotypic drug screening. An increasing number of molecules have been brought from bench to bedside thanks to zebrafish-based assays over the last decade. The high homology between the zebrafish and the human genomes facilitates the generation of zebrafish lines carrying loss-of-function mutations in disease-relevant genes; nonetheless, even using this alternative model, the establishment of isogenic mutant lines requires a long generation time and an elevated number of animals. In this study, we developed a zebrafish-based high-throughput platform for the generation of F0 knock-out (KO) models and the screening of neuroactive compounds. We show that the simultaneous inactivation of a reporter gene (tyrosinase) and a second gene of interest allows the phenotypic selection of F0 somatic mutants (crispants) carrying the highest rates of mutations in both loci. As a proof of principle, we targeted genes associated with neurodevelopmental disorders and we efficiently generated de facto F0 mutants in seven genes involved in childhood epilepsy. We employed a high-throughput multiparametric behavioral analysis to characterize the response of these KO models to an epileptogenic stimulus, making it possible to employ kinematic parameters to identify seizure-like events. The combination of these co-injection, screening and phenotyping methods allowed us to generate crispants recapitulating epilepsy features and to test the efficacy of compounds already during the first days post fertilization. Since the strategy can be applied to a wide range of indications, this study paves the ground for high-throughput drug discovery and promotes the use of zebrafish in personalized medicine and neurotoxicity assessment.

Limited high-throughput screening compatibility of the phenuivirus cap-binding domain

Bunyaviruses constitute a large and diverse group of viruses encompassing many emerging pathogens, such as Rift Valley fever virus (family Phenuiviridae), with public and veterinary health relevance but with very limited medical countermeasures are available. For the development of antiviral strategies, the identification and validation of virus-specific targets would be of high value. The cap-snatching mechanism is an essential process in the life cycle of bunyaviruses to produce capped mRNAs, which are then recognized and translated into viral proteins by the host cell translation machinery. Cap-snatching involves cap-binding as well as endonuclease functions and both activities have been demonstrated to be druggable in related influenza viruses. Here, we explore the suitability of the phenuivirus cap-binding function as a target in medium- and high-throughput drug discovery approaches. We developed a range of in vitro assays aiming to detect the interaction between the cap-binding domain (CBD) and the analogue of its natural cap-ligand m7GTP. However, constricted by its shallow binding pocket and low affinity for m7GTP, we conclude that the CBD has limited small molecule targeting potential using classical in vitro drug discovery approaches.

Abstract 13500: An Improved Reporter Identifies Ruxolitinib as a Potent and Cardioprotective CaMKII Inhibitor

Background: Ca 2+ /Calmodulin-dependent protein kinase II (CaMKII) hyperactivity is an established driver of cardiac arrhythmias. Despite proven benefits of CaMKII inhibition in numerous preclinical arrhythmia models, translation of CaMKII antagonists into humans has remained unsuccessful, and today, there are no clinically approved CaMKII inhibitors. Our ability to identify potent CaMKII inhibitors has been hamstrung by a lack of a CaMKII biosensor with sufficient sensitivity for high throughput drug discovery. Research question: We hypothesized that development of a CaMKII biosensor with high throughput capabilities would enable identification of CaMKII inhibitors capable of preventing arrhythmias. Methods: To address this problem, we engineered and validated a new genetically encoded CaMKII biosensor: CaMKAR (CaMKII Activity Reporter). CaMKAR enjoys a dynamic range of 227 ± 11.1 %, seconds-scale kinetics, robust specificity, and dual in cellulo and in vitro functionality. This makes CaMKAR the fastest and most sensitive CaMKII biosensor to date and the first that is amenable for in cellulo drug screening. Results: Using CaMKAR, we carried out a drug repurposing screen (4,475 compounds in clinical use) in human cells. This yielded five previously unrecognized CaMKII inhibitors: ruxolitinib, baricitinib, silmitasertib, crenolanib, and abemaciclib (false discovery-adjusted p<3 x 10 -5 ). Stand out among these, ruxolitinib, an FDA-approved Janus kinase inhibitor, blocked CaMKII kinase activity with an inhibitory constant of 23.5 ± 2.2 nM. In patient-derived cardiomyocytes, ruxolitinib ameliorated arrhythmogenic Ca 2+ release events (p<0.0001), and in mice, ruxolitinib prevented catecholaminergic polymorphic ventricular tachycardia (p<0.01) and rescued pre-existing atrial fibrillation (p<0.0001). Conclusion: Our work presents three impactful Conclusions: 1) Our biosensor, CaMKAR, provides the highest CaMKII activity reporting performance to date. 2) Long sought-after CaMKII inhibitors already exist within the human pharmacopeia. 3) Our results demonstrate that ruxolitinib—a drug already in human use—is a cardioprotective CaMKII inhibitor and a suitable candidate for cardiovascular repurposing.

Identification of potent inhibitors for Leishmania donovani homoserine kinase: an integrated in silico and kinetic study

Leishmaniasis is caused by ∼20 species of Leishmania that affects millions in endemic areas. Available therapies are not sufficient to effectively control the disease, cause severe side effects and eventually lead to drug resistance, making the discovery of novel therapeutic molecules an immediate need. Molecular target-based drug discovery, where the target is a defined molecular gene, protein or a mechanism, is a rationale driven approach for novel therapeutics. Humans obtain the essential amino acid such as threonine from dietary sources, while Leishmania synthesize it de-novo. Enzymes of the threonine biosynthesis pathway, including the rate limiting Homoserine kinase (HSK) which converts L-homoserine into ortho-phospho homoserine are thus attractive targets for rationale driven therapy. The absence of HSK in humans and its presence in Leishmania donovani enhances the opportunity to exploit HSK as a molecular target for anti-leishmanials therapeutic development. In this study, we utilize structure-based high throughput drug discovery (SBDD), followed by biochemical validation and identified two potential inhibitors (RH00038 and S02587) from Maybridge chemical library that targets L. donovani HSK. These two inhibitors effectively induced the mortality of Leishmania donovani in both amastigote and promastigote stages, with one of them being specific to parasite and twice as effective as the standard therapeutic molecule.

Development of a novel human triculture model of non-alcoholic fatty liver disease and identification of berberine as ameliorating steatosis, oxidative stress and fibrosis.

Objectives: Non-alcoholic fatty liver disease (NAFLD) and its progression to non-alcoholic steatohepatitis (NASH) and hepatocarcinoma is a serious and growing problem. However, the development of new therapies is severely hindered by a lack of high-throughput assays for drug testing. Methods: We have developed a simple transwell assay comprised of HepG2 hepatocytes, hepatic LX-2 stellate cells, and differentiated THP-1 cells. The cells were incubated with an activating mixture containing the NASH-associated risk factors, glucose, insulin, free fatty acids (FFAs), and lipopolysaccharide (LPS) for 72h. We compared different combinations of culture conditions to obtain a model system that recapitulates the main features of NAFLD/NASH, i.e., increased steatosis, reactive oxygen species (ROS), secretion of pro-inflammatory cytokines/chemokines, and presence of fibrosis. To confirm the usefulness of the optimized model system, we screened for compounds that inhibit steatosis in the hepatocytes and evaluated the most effective compound in the triculture model system. Results: The activating mixture stimulated HepG2 cells in this triculture to accumulate more fat and produce higher levels of reactive oxygen species (ROS) than HepG2 cells in monocultures. As well, higher levels of inflammatory cytokines and chemokines (IL-8, IL-6, MIP-1α, etc.) were produced in this triculture compared to monocultures. In addition, in all LX-2 monocultures and cocultures, exposure to the activating mixture increased markers of fibrosis. A major strength of our triculture system is that it makes possible the simultaneous monitoring of 4 main features of NASH, i.e., steatosis, oxidative stress, inflammation and fibrosis. Screening potential modulators that may reduce steatosis in HepG2 cells revealed the protective effects of the isoalkaloid, berberine. Tested using this novel triculture assay, treatment with 5µM berberine decreased steatosis and ROS in HepG2 hepatocytes, reduced inflammatory cytokine production and inhibited collagen production from LX-2 cells. Conclusion: This simple triculture model recapitulates the main features of NAFLD/NASH and should be useful for high-throughput preclinical drug discovery. In this model, berberine showed promising results in decreasing steatosis and ROS and protection against fibrosis.

Repurposing sunscreen as an antibiotic: zinc-activated avobenzone inhibits methicillin-resistant Staphylococcus aureus.

Methicillin-resistant Staphylococcus aureus (MRSA) is a major healthcare concern with associated healthcare costs reaching over ${\$}$1 billion in a single year in the USA. Antibiotic resistance in S. aureus is now observed against last line of defense antibiotics, such as vancomycin, linezolid, and daptomycin. Unfortunately, high throughput drug discovery approaches to identify new antibiotics effective against MRSA have not resulted in much tangible success over the last decades. Previously, we demonstrated the feasibility of an alternative drug discovery approach, the identification of metallo-antibiotics, compounds that gain antibacterial activity only after binding to a transition metal ion and as such are unlikely to be detected in standard drug screens. We now report that avobenzone, the primary active ingredient of most sunscreens, can be activated by zinc to become a potent antibacterial compound against MRSA. Zinc-activated avobenzone (AVB-Zn) potently inhibited a series of clinical MRSA isolates [minimal inhibitory concentration (MIC): 0.62-2.5 µM], without pre-existing resistance and activity without zinc (MIC: >10 µM). AVB-Zn was also active against clinical MRSA isolates that were resistant against the commonly used zinc-salt antibiotic bacitracin. We found AVB-Zn exerted no cytotoxicity on human cell lines and primary cells. Last, we demonstrate AVB-Zn can be deployed therapeutically as lotion preparations, which showed efficacy in a mouse wound model of MRSA infection. AVB-Zn thus demonstrates Zn-activated metallo-antibiotics are a promising avenue for future drug discovery.

The million-molecule challenge: a moonshot project to rapidly advance longevity intervention discovery.

Targeting aging is the future of twenty-first century preventative medicine. Small molecule interventions that promote healthy longevity are known, but few are well-developed and discovery of novel, robust interventions has stagnated. To accelerate longevity intervention discovery and development, high-throughput systems are needed that can perform unbiased drug screening and directly measure lifespan and healthspan metrics in whole animals. C. elegans is a powerful model system for this type of drug discovery. Combined with automated data capture and analysis technologies, truly high-throughput longevity drug discovery is possible. In this perspective, we propose the "million-molecule challenge", an effort to quantitatively assess 1,000,000 interventions for longevity within five years. The WormBot-AI, our best-in-class robotics and AI data analysis platform, provides a tool to achieve the million-molecule challenge for pennies per animal tested.

Nutrient stress is a target for new antibiotics.

Novel approaches are required to address the looming threat of pan-resistant Gram-negative pathogens and forestall the rise of untreatable infections. Unconventional targets that are uniquely important during infection and tractable to high-throughput drug discovery methods hold high potential for innovation in antibiotic discovery programs. In this context, inhibitors of bacterial nutrient stress are particularly exciting candidates for future antibiotic development. Amino acid, nucleotide, and vitamin biosynthesis pathways are critical for bacterial growth in nutrient-limiting conditions in the laboratory and the host. Although historically dismissed as dispensable for pathogens, a wealth of transposon mutagenesis and single-mutant studies have emerged which demonstrate that several such pathways are critical for infection. Indeed, high-throughput screens of diverse synthetic compounds and natural products have uncovered inhibitors of nutrient biosynthesis. Herein, we review bacterial nutrient biosynthesis and its role during host infection. Further, we explore screening platforms developed to search for inhibitors of these targets and highlight successes among these. Finally, we feature important and sometimes surprising connections between bacterial nutrient biosynthesis, antibiotic activity, and antibiotic resistance.

Editorial: The protagonism of bioanalytical methods in high-throughput drug discovery

Editorial: The protagonism of bioanalytical methods in high-throughput drug discovery

Microsystem Advances through Integration with Artificial Intelligence

Microfluidics is a rapidly growing discipline that involves studying and manipulating fluids at reduced length scale and volume, typically on the scale of micro- or nanoliters. Under the reduced length scale and larger surface-to-volume ratio, advantages of low reagent consumption, faster reaction kinetics, and more compact systems are evident in microfluidics. However, miniaturization of microfluidic chips and systems introduces challenges of stricter tolerances in designing and controlling them for interdisciplinary applications. Recent advances in artificial intelligence (AI) have brought innovation to microfluidics from design, simulation, automation, and optimization to bioanalysis and data analytics. In microfluidics, the Navier–Stokes equations, which are partial differential equations describing viscous fluid motion that in complete form are known to not have a general analytical solution, can be simplified and have fair performance through numerical approximation due to low inertia and laminar flow. Approximation using neural networks trained by rules of physical knowledge introduces a new possibility to predict the physicochemical nature. The combination of microfluidics and automation can produce large amounts of data, where features and patterns that are difficult to discern by a human can be extracted by machine learning. Therefore, integration with AI introduces the potential to revolutionize the microfluidic workflow by enabling the precision control and automation of data analysis. Deployment of smart microfluidics may be tremendously beneficial in various applications in the future, including high-throughput drug discovery, rapid point-of-care-testing (POCT), and personalized medicine. In this review, we summarize key microfluidic advances integrated with AI and discuss the outlook and possibilities of combining AI and microfluidics.

Abstract 199: Novel platform for automation of high throughput drug discovery using patient derived colorectal cancer organoids

Abstract Most potential oncology drugs fail at the later stages of the drug development pipeline and in clinical trials, despite having promising data for their efficacy in vitro. This high failure rate is partly due to insufficient predictive models being used to screen drug candidates in the early stages of drug discovery. As such, there is a need to develop and utilize more representative models that are amendable for efficient testing of drug efficacy to discover new therapeutic targets. 3D cell models, specifically patient-derived organoids (PDOs), offer a promising solution to this problem. Cells grown in 3D can better mimic cell-cell interactions and the tissue microenvironment, including cancer stem cell niches. Studies show that patients and their derived organoids respond similarly to drugs, suggesting the therapeutic value of using PDOs to improve therapeutic outcomes. However, challenges commonly associated with using these organoids, such as assay reproducibility, ability to scale up, and cost have limited their widespread adoption as a primary screening method in drug discovery. To address some of the hurdles associated with the use of PDOs in large scale screens, a semi-automated bioprocess has been developed for the controlled production of standardized PDOs at scale. PDOs cultured in the bioprocessor were uniform in size, show high viability and were produced in repeatable batches in an assay-ready format. In this study, patient-derived colorectal cancer (CRC) organoids were seeded in high density (96 or 384 well) microtiter plates manually. We also tested the feasibility of scaling up the use of these CRCs by using an automated liquid handler or a bioprinter to seed and culture the PDOs. CRC PDOs were treated with selected anti-cancer compounds at various concentrations. Compound effects were monitored over time using transmitted light imaging. For the analysis of organoid growth and development, a deep learning-based image segmentation model was developed to automate the segmentation of the organoids. Using this approach, we tracked the effects of the compounds on colorectal organoid size, morphology, texture, and additional morphological and phenotypic readouts. A viability assay was carried out using live/dead cell dyes and the PDOs were imaged in 3D on a high-content confocal imager. Out of the tested panel of known anti-cancer drugs, we found that PDOs treated with romidepsin and trametinib showed the most significant reduction in size, with a greater number of dead cells compared to the other compounds and controls. Overall, our results show the potential for the utility of PDOs in both precision medicine and high throughput drug discovery applications, when using automation with high-content imaging. Citation Format: Angeline Lim, Zhisong Tong, Prathyushakrishna Macha, Oksana Sirenkp. Novel platform for automation of high throughput drug discovery using patient derived colorectal cancer organoids [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 199.

Abstract 4728: Biochemical and genomic approaches for high throughput drug discovery in chromatin remodeling research

Abstract Chromatin remodeling is mediated by ATP-dependent enzymes that play key roles regulating gene expression and genome replication/repair. Aberrant nucleosome organization from dysregulated chromatin remodeling can severely alter chromatin accessibility and disrupt these important processes, thereby driving various cancers. Remarkably, nearly 20% of all human cancers contain mutations in subunits from the SWI/SNF family of chromatin remodeling complexes, making them of great interest to basic research and therapeutic intervention. In vitro studies on the remodeling enzymes (and their multi-subunit complexes) are challenging, partially due to the strong preference for nucleosome-based substrates (the physiological target of these enzymes). We have created the EpiDyne® nucleosome portfolio to examine chromatin remodeler activity in biochemical assays, and here present the development of novel readouts (-PicoGreenTM and -TR-FRET). These nonradioactive plate-based assays are automation adaptable, ready for high-throughput inhibitor screening, and can be customized for various remodeling enzymes that exhibit preferences in nucleosome composition (e.g. histone type or DNA linker length).For parallel in vivo studies we note that genome-wide remodeler localization and open chromatin mapping are fundamental for understanding the function/activity of these enzymes in cancer development and inhibitor response. However, traditional genomic approaches have significant issues: e.g. ChIP-seq is unable to effectively map ATPases without heavily modified high-noise protocols; while ATAC-seq to map open regions cannot deal with cross-linking that could stabilize transient states on interest. To this end, we have optimized the CUTANA™ CUT&RUN approach to efficiently capture the localization of all major classes of chromatin remodelers with high signal to background. We have also adopted NicE-seq for chromatin accessibility profiling in cross-linked material. As complementary tools to the EpiDyne platform, CUT&RUN and NicE-seq facilitate epigenomic research on chromatin remodelers in cancer therapeutic intervention. Keywords: Chromatin Remodeling, EpiDyne, Nucleosome repositioning, high-throughput screening (HTS), CUTANA™ CUT&RUN, NicE-seq Citation Format: Lu Sun, Hannah Willis, Matthew R. Marunde, Vishnu U. Kumary, Matthew J. Meiners, Saarang Gopinath, Jonathan M. Burg, Bryan J. Venters, Allison Hickman, Zu-Wen Sun, Martis W. Cowles, Pierre Esteve, Hang Gyeong Chin, Chaithanya Ponnaluri, Sriharsa Pradhan, Michael-Christopher Keogh. Biochemical and genomic approaches for high throughput drug discovery in chromatin remodeling research. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4728.

High-throughput infrared spectroscopy for quantification of peptides in drug discovery

Peptides have gained an increasing importance in drug discovery as potential therapeutics. Discovery efforts toward finding new, efficacious peptide-based therapeutics have increased the throughput of peptide development, allowing the rapid generation of unique and pure peptide samples. However, high-throughput analysis of peptides may be still challenging and can encumber a high-throughput drug discovery campaign. We report herein a fit-for-purpose method to quantify peptide concentrations using high-throughput infrared spectroscopy (HT-IR). Through the development of this method, multiple critical method parameters were optimized including solvent composition, droplet deposition size, plate drying procedures, sample concentration, and internal standard. The relative absorbance of the amide region (1600–1750 cm-1) to the internal standard, K3Fe(CN)6 (2140 cm-1), was determined to be most effective at providing lowest interference for measuring peptide concentration. The best sample deposition was achieved by dissolving samples in a 50:50 v/v allyl alcohol/water mixture. The developed method was used on 96-well plates and analyzed at a rate of 22 min per plate. Calibration curves to measure sample concentration versus response relationship displayed sufficient linearity (R2 > 0.95). The repeatability and scope of detection was demonstrated with eighteen peptide samples that were measured with most values below 20% relative standard deviation. The linear dynamic range of the method was determined to be between 1 and 5 mg/mL. This developed HT-IR methodology could be a useful tool in peptide drug candidate lead identification and optimization processes.

3D Hydrogel Cultures for High-Throughput Drug Discovery.

Our increased understanding of how a cell's microenvironment influences its behavior has fueled an interest in three-dimensional (3D) cell cultures for drug discovery. Particularly, scaffold-based 3D cultures are expected to recapitulate in vivo tissue stiffness and extracellular matrix composition more accurately than standard two-dimensional (2D) monolayer cultures. Here we present a 3D hydrogel cell culture setup suitable for automated screening with standard high-throughput screening (HTS) liquid handling equipment commonly found in a drug discovery laboratory. Further, we describe the steps required to validate the assay system for compound screening.

Effects of valproate on seizure-like activity in Drosophila melanogaster with a knockdown of Ube3a in different neuronal populations as a model of Angelman Syndrome

Angelman Syndrome is a rare, genetically induced neurodevelopmental disorder. This disorder stems from a mutation or deletion of the maternal UBE3A gene. Characteristics of this disease include developmental delay, recurring seizures, and severe intellectual disabilities. We studied seizure activity in male Drosophila melanogaster with a knockdown of Ube3a in different neuronal populations (GABAergic, glutamatergic, mushroom body, and all neurons) and investigated the effects of the antiseizure medication (ASM) on seizure-like activity. Epileptiform activity was monitored in individual fruit flies using imaging chambers and mechanically induced seizures using a vortex assay. A positive control was also used: eas (easily shocked seizure phenotype). Seizure activity was analyzed for sums of seizure durations, number of seizures, and total time to return to normal activity.Ube3a knockdowns in GABAergic neurons elicited more seizure-like episodes than knockdowns in glutamatergic neurons and were on par with the positive control group and those with knockdowns in the mushroom bodies. We have established a method whereby valproate could be administered through food rather than through injections to effectively treat epileptiform activity. We demonstrated that if Ube3a is not knocked down pan-neuronally, Angelman Syndrome seizure-like activity can be studied using Drosophila melanogaster and therefore allows for high-throughput drug discovery.

Rapid and Highly Selective Fluorescent Labeling of Peptides via a Thia-Diels-Alder Cycloaddition: Application to Apelin.

Herein, we describe a catalyst-free thia-Diels-Alder cycloaddition for the chemoselective labeling of fully deprotected phosphonodithioester-peptides in solution with fluorophores functionalized with an exocyclic diene. The reaction was optimized on the model tripeptide 1 containing a lysine residue, which enabled its rapid and straightforward labeling with three different fluorophores (fluorescein, lissamine rhodamine B, and squaraine) in very mild conditions (H2O/iPrOH, 37 °C, 1 h). The reaction was then successfully applied to the chemoselective labeling of fully deprotected apelin-13 with squaraine dye. The resulting fluorescent ligand 18 exhibited a high affinity (0.17 ± 0.03 nM) for apelinR. It enabled the development of time-resolved FRET-based competition assays for high-throughput screening and drug discovery. Thanks to its fluorogenic properties, ligand 18 was also successfully involved in the live-cell optical imaging of apelinR in no-wash conditions.

Advances in high-throughput mass spectrometry in drug discovery.

High-throughput (HT) screening drug discovery, during which thousands or millions of compounds are screened, remains the key methodology for identifying active chemical matter in early drug discovery pipelines. Recent technological developments in mass spectrometry (MS) and automation have revolutionized the application of MS for use in HT screens. These methods allow the targeting of unlabelled biomolecules in HT assays, thereby expanding the breadth of targets for which HT assays can be developed compared to traditional approaches. Moreover, these label-free MS assays are often cheaper, faster, and more physiologically relevant than competing assay technologies. In this review, we will describe current MS techniques used in drug discovery and explain their advantages and disadvantages. We will highlight the power of mass spectrometry in label-free invitro assays, and its application for setting up multiplexed cellular phenotypic assays, providing an exciting new tool for screening compounds in cell lines, and even primary cells. Finally, we will give an outlook on how technological advances will increase the future use and the capabilities of mass spectrometry in drug discovery.

Ultrahigh-Throughput Intact Protein Analysis with Acoustic Ejection Mass Spectrometry.

The need for high-throughput intact protein analysis has been rising as drug discovery increasingly requires the analysis of large sets of covalent modifiers and protein therapeutics. Liquid chromatography-mass spectrometry (LC-MS) is the primary analytical tool used to date to characterize proteins within the biopharmaceutical industry. However, the speed of LC-MS prevents the analysis of large-scale sample sets (>1000 within a day). Acoustic ejection mass spectrometry (AEMS) has recently been established as an electrospray ionization (ESI)-MS based platform with both fast analytical throughput and high data quality. Since its introduction, this technology has been applied in numerous fields with a primary focus on small-molecule analysis in high-throughput drug discovery and development. Here we explore the application of AEMS to high-throughput intact protein analysis for proteins ranging in molecular weight from 17 to 150 kDa on a prototype high-resolution quadrupole time-of-flight (HR QTOF) based AEMS system. Data quality obtained on this platform is comparable to LC-MS, while the analysis speed is significantly improved to one-second-per-sample. This ultrahigh-throughput intact protein analysis platform has the potential to be used broadly in drug discovery.