Apparent activity in high-throughput screening: origins of compound-dependent assay interference

Limited Chemical Structural Diversity Found to Modulate Thyroid Hormone Receptor in the Tox21 Chemical Library

BACKGROUND

Thyroid hormone receptors (TRs) are critical endocrine receptors that regulate a multitude of processes in adult and developing organisms, and thyroid hormone disruption is of high concern for neurodevelopmental and reproductive toxicities in particular. To date, only a small number of chemical classes have been identified as possible TR modulators, and the receptors appear highly selective with respect to the ligand structural diversity. Thus, the question of whether TRs are an important screening target for protection of human and wildlife health remains.

OBJECTIVE

Our goal was to evaluate the hypothesis that there is limited structural diversity among environmentally relevant chemicals capable of modulating TR activity via the collaborative interagency Tox21 project.

METHODS

We screened the Tox21 chemical library (8,305 unique structures) in a quantitative high-throughput, cell-based reporter gene assay for TR agonist or antagonist activity. Active compounds were further characterized using additional orthogonal assays, including mammalian one-hybrid assays, coactivator recruitment assays, and a high-throughput, fluorescent imaging, nuclear receptor translocation assay.

RESULTS

Known agonist reference chemicals were readily identified in the TR transactivation assay, but only a single novel, direct agonist was found, the pharmaceutical betamipron. Indirect activation of TR through activation of its heterodimer partner, the retinoid-X-receptor (RXR), was also readily detected by confirmation in an RXR agonist assay. Identifying antagonists with high confidence was a challenge with the presence of significant confounding cytotoxicity and other, non-TR-specific mechanisms common to the transactivation assays. Only three pharmaceuticals-mefenamic acid, diclazuril, and risarestat-were confirmed as antagonists.

DISCUSSION

The results support limited structural diversity for direct ligand effects on TR and imply that other potential target sites in the thyroid hormone axis should be a greater priority for bioactivity screening for thyroid axis disruptors. https://doi.org/10.1289/EHP5314.

In silico Guided Drug Repurposing: Discovery of New Competitive and Non-competitive Inhibitors of Falcipain-2

Malaria is among the leading causes of death worldwide. The emergence of Plasmodium falciparum resistant strains with reduced sensitivity to the first line combination therapy and suboptimal responses to insecticides used for Anopheles vector management have led to renewed interest in novel therapeutic options. Here, we report the development and validation of an ensemble of ligand-based computational models capable of identifying falcipain-2 inhibitors, and their subsequent application in the virtual screening of DrugBank and Sweetlead libraries. Among four hits submitted to enzymatic assays, two (odanacatib, an abandoned investigational treatment for osteoporosis and bone metastasis, and the antibiotic methacycline) confirmed inhibitory effects on falcipain-2, with Ki of 98.2 nM and 84.4 μM. Interestingly, Methacycline proved to be a non-competitive inhibitor (α = 1.42) of falcipain-2. The effects of both hits on falcipain-2 hemoglobinase activity and on the development of P. falciparum were also studied.

Tailored therapeutics based on 1,2,3-1H-triazoles: a mini review

Contemporary drug discovery approaches rely on library synthesis coupled with combinatorial methods and high-throughput screening to identify leads. However, due to the multitude of components involved, a majority of optimization techniques face persistent challenges related to the efficiency of synthetic processes and the purity of compound libraries. These methods have recently found an upgradation as fragment-based approaches for target-guided synthesis of lead molecules with active involvement of their biological target. The click chemistry approach serves as a promising tool for tailoring the therapeutically relevant biomolecules of interest, improving their bioavailability and bioactivity and redirecting them as efficacious drugs. 1,2,3-1H-Triazole nucleus, being a planar and biologically acceptable scaffold, plays a crucial role in the design of biomolecular mimetics and tailor-made molecules with therapeutic relevance. This versatile scaffold also forms an integral part of the current fragment-based approaches for drug design, kinetic target guided synthesis and bioorthogonal methodologies.

Potent and selective inhibitors for M32 metallocarboxypeptidases identified from high-throughput screening of anti-kinetoplastid chemical boxes

Enzymes of the M32 family are Zn-dependent metallocarboxypeptidases (MCPs) widely distributed among prokaryotic organisms and just a few eukaryotes including Trypanosoma brucei and Trypanosoma cruzi, the causative agents of sleeping sickness and Chagas disease, respectively. These enzymes are absent in humans and several functions have been proposed for trypanosomatid M32 MCPs. However, no synthetic inhibitors have been reported so far for these enzymes. Here, we present the identification of a set of inhibitors for TcMCP-1 and TbMCP-1 (two trypanosomatid M32 enzymes sharing 71% protein sequence identity) from the GlaxoSmithKline HAT and CHAGAS chemical boxes; two collections grouping 404 compounds with high antiparasitic potency, drug-likeness, structural diversity and scientific novelty. For this purpose, we adapted continuous fluorescent enzymatic assays to a medium-throughput format and carried out the screening of both collections, followed by the construction of dose-response curves for the most promising hits. As a result, 30 micromolar-range inhibitors were discovered for one or both enzymes. The best hit, TCMDC-143620, showed sub-micromolar affinity for TcMCP-1, inhibited TbMCP-1 in the low micromolar range and was inactive against angiotensin I-converting enzyme (ACE), a potential mammalian off-target structurally related to M32 MCPs. This is the first inhibitor reported for this family of MCPs and considering its potency and specificity, TCMDC-143620 seems to be a promissory starting point to develop more specific and potent chemical tools targeting M32 MCPs from trypanosomatid parasites.

Ligand potency - an essential estimator for drug design: between intuition, misinterpretation and serendipity

This is a review of developments in the field of potency, which is an essential estimator for drug design. We discuss the basic concepts of research and discovery, focusing on how misinterpretation in this area, - but also intuition and serendipity, which are common in drug design - helped us to pave a bumpy road towards better drugs. How far we still are from this goal can be seen in the Eroom law, which states that the efficiency of pharma research and development is decreasing. At the same time, pharma bestsellers are getting older.

Target-based Screening of the Chagas Box: Setting Up Enzymatic Assays to Discover Specific Inhibitors Across Bioactive Compounds

Chagas disease is a neglected tropical illness caused by the protozoan parasite Trypanosoma cruzi. The disease is endemic in Latin America with about 6 million people infected and many more being at risk. Only two drugs are available for treatment, Nifurtimox and Benznidazole, but they have a number of side effects and are not effective in all cases. This makes urgently necessary the development of new drugs, more efficient, less toxic and affordable to the poor people, who are most of the infected population. In this review we will summarize the current strategies used for drug discovery considering drug repositioning, phenotyping screenings and target-based approaches. In addition, we will describe in detail the considerations for setting up robust enzymatic assays aimed at identifying and validating small molecule inhibitors in high throughput screenings.

Quantitative high-throughput screening assays for the discovery and development of SIRPα-CD47 interaction inhibitors

CD47 is an immune checkpoint molecule that downregulates key aspects of both the innate and adaptive anti-tumor immune response via its counter receptor SIRPα, and it is expressed at high levels in a wide variety of tumor types. This has led to the development of biologics that inhibit SIRPα engagement including humanized CD47 antibodies and a soluble SIRPα decoy receptor that are currently undergoing clinical trials. Unfortunately, toxicological issues, including anemia related to on-target mechanisms, are barriers to their clinical advancement. Another potential issue with large biologics that bind CD47 is perturbation of CD47 signaling through its high-affinity interaction with the matricellular protein thrombospondin-1 (TSP1). One approach to avoid these shortcomings is to identify and develop small molecule molecular probes and pretherapeutic agents that would (1) selectively target SIRPα or TSP1 interactions with CD47, (2) provide a route to optimize pharmacokinetics, reduce on-target toxicity and maximize tissue penetration, and (3) allow more flexible routes of administration. As the first step toward this goal, we report the development of an automated quantitative high-throughput screening (qHTS) assay platform capable of screening large diverse drug-like chemical libraries to discover novel small molecules that inhibit CD47-SIRPα interaction. Using time-resolved Förster resonance energy transfer (TR-FRET) and bead-based luminescent oxygen channeling assay formats (AlphaScreen), we developed biochemical assays, optimized their performance, and individually tested them in small-molecule library screening. Based on performance and low false positive rate, the LANCE TR-FRET assay was employed in a ~90,000 compound library qHTS, while the AlphaScreen oxygen channeling assay served as a cross-validation orthogonal assay for follow-up characterization. With this multi-assay strategy, we successfully eliminated compounds that interfered with the assays and identified five compounds that inhibit the CD47-SIRPα interaction; these compounds will be further characterized and later disclosed. Importantly, our results validate the large library qHTS for antagonists of CD47-SIRPα interaction and suggest broad applicability of this approach to screen chemical libraries for other protein-protein interaction modulators.

Phenolic Compounds as Promising Drug Candidates in Tuberculosis Therapy

Tuberculosis (TB), caused by Mycobacterium tuberculosis (MTB) remains one of the deadliest, infectious diseases worldwide. The detrimental effects caused by the existing anti-TB drugs to TB patients and the emergence of resistance strains of M. tuberculosis has driven efforts from natural products researchers around the globe in discovering novel anti-TB drugs that are more efficacious and with less side effects. There were eleven main review publications that focused on natural products with anti-TB potentials. However, none of them specifically emphasized antimycobacterial phenolic compounds. Thus, the current review’s main objective is to highlight and summarize phenolic compounds found active against mycobacteria from 2000 to 2017. Based on the past studies in the electronic databases, the present review also focuses on several test organisms used in TB researches and their different distinct properties, a few types of in vitro TB bioassay and comparison between their strengths and drawbacks, different methods of extraction, fractionation and isolation, ways of characterizing and identifying isolated compounds and the mechanism of actions of anti-TB phenolic compounds as reported in the literature.

Accelerating the Throughput of Affinity Mass Spectrometry-Based Ligand Screening toward a G Protein-Coupled Receptor

Affinity mass spectrometry (MS) enables rapid screening of compound mixtures for ligands bound to a specific protein target, yet its current throughput is limited to individually assay pools of 400-2000 compounds. Typical affinity MS screens implemented in pharmaceutical industry laboratories identify putative ligands based on qualitative analysis of compound binding to the target whereas no quantitative information is acquired to discriminate high- and low-affinity ligands in the screening phase. Furthermore, these screens require purification of a stabilized form of the protein target, which poses a great challenge for membrane receptor targets. Here, we describe a new, potentially general affinity MS strategy that allows screening of 20,000 compounds in one pool for highly efficient ligand discovery toward a G protein-coupled receptor (GPCR) target. Quantitative measurement of compound binding to the receptor enables high-affinity ligand selection using both the purified receptor and receptor-embedded cell membranes. This high-throughput, label-free and quantitative affinity MS screen resulted in discovery of three new antagonists of the A2A adenosine receptor.

Effects of Maerua subcordata (Gilg) DeWolf on electrophile-responsive element (EpRE)-mediated gene expression in vitro

Plant extracts and phytochemicals may prevent chronic diseases via activation of adaptive cellular stress response pathways including induction of antioxidant and phase II detoxifying enzymes. The regulatory regions of these inducible genes encode the electrophile-response element (EpRE). This study tested the EpRE induction ability of Maerua subcordata (fruit, leaf, root, seed) methanol extracts and selected candidate constituents thereof, identified by liquid chromatography coupled with multistage mass spectroscopy, employing an EpRE luciferase reporter gene assay using hepa-1c1c7 mouse hepatoma cells. A parallel Cytotox CALUX assay using human osteosarcoma U2OS cells was used to monitor any non-specific changes in luciferase activity or cytotoxicity. Results showed that fruit, root, and seed extracts were non-cytotoxic up to a concentration of 30 gram dry weight per litre but the leaf extract exhibited some cytotoxicity and that the leaf (despite some cytotoxicity), fruit, and seed extracts showed strong induction of EpRE mediated gene expression while induction by the root extract was minimal. Selected candidates included glucosinolates, isothiocyanates, and some biogenic amines. Subsequent studies showed that methyl-, ethyl-, isopropyl-, isobutyl- isothiocyanates, and sec-butyl thiocyanate as well as glucobrassicin induced concentration (1–100 μM) dependent EpRE-mediated gene expression while the biogenic amines stachydrine and trigonelline acted as inhibitors of EpRE-mediated gene expression at 100 μM. The identification of glucolepidiin, glucobrassicin, glucocapparin, stachydrine, and trigonelline in all extracts was confirmed using standards and based on multiple reaction monitoring; yet, glucobrassicin level in the root extract was negligible. In conclusion, this study provided a first report on EpRE mediated gene expression effects of M. subcordata; and despite detection of different glucosinolates in all extracts, those containing glucobrassicin particularly displayed high EpRE induction. Because EpRE inducers are cytoprotective and potential chemopreventive agents while inhibitors are suggested adjuvants of chemotherapy, results of this study imply that process manipulation of this plant may result in herbal preparations that may be used as chemopreventive agents or adjuvants of chemotherapies.

Development of a High-Throughput Cytometric Screen to Identify Anti- Wolbachia Compounds: The Power of Public-Private Partnership

The Anti-Wolbachia (A·WOL) consortium at the Liverpool School of Tropical Medicine (LSTM) has partnered with the Global High-Throughput Screening (HTS) Centre at AstraZeneca to create the first anthelmintic HTS for neglected tropical diseases (NTDs). The A·WOL consortium aims to identify novel macrofilaricidal drugs targeting the essential bacterial symbiont (Wolbachia) of the filarial nematodes causing onchocerciasis and lymphatic filariasis. Working in collaboration, we have validated a robust high-throughput assay capable of identifying compounds that selectively kill Wolbachia over the host insect cell. We describe the development and validation process of this complex, phenotypic high-throughput assay and provide an overview of the primary outputs from screening the AstraZeneca library of 1.3 million compounds.

Screening the ToxCast Phase 1, Phase 2, and e1k Chemical Libraries for Inhibitors of Iodothyronine Deiodinases

Deiodinase enzymes play an essential role in converting thyroid hormones between active and inactive forms by deiodinating the pro-hormone thyroxine (T4) to the active hormone triiodothyronine (T3) and modifying T4 and T3 to inactive forms. Chemical inhibition of deiodinase activity has been identified as an important endpoint to include in screening chemicals for thyroid hormone disruption. To address the lack of data regarding chemicals that inhibit the deiodinase enzymes, we developed robust in vitro assays that utilized human deiodinase types 1, 2, and 3 and screened over 1800 unique chemicals from the U.S. EPA's ToxCast phase 1_v2, phase 2, and e1k libraries. Initial testing at a single concentration identified 411 putative deiodinase inhibitors that produced inhibition of 20% or greater in at least 1 of the 3 deiodinase assays, including chemicals that have not previously been shown to inhibit deiodinases. Of these, 228 chemicals produced enzyme inhibition of 50% or greater; these chemicals were further tested in concentration-response to determine relative potency. Comparisons across these deiodinase assays identified 81 chemicals that produced selective inhibition, with 50% inhibition or greater of only 1 of the deiodinases. This set of 3 deiodinase inhibition assays provides a significant contribution toward expanding the limited number of in vitro assays used to identify chemicals with the potential to interfere with thyroid hormone homeostasis. In addition, these results set the groundwork for development and evaluation of structure-activity relationships for deiodinase inhibition, and inform targeted selection of chemicals for further testing to identify adverse outcomes of deiodinase inhibition.

Evaluation of endocrine activities of ellagic acid and urolithins using reporter gene assays

Urolithins are metabolites produced in the gut following consumption of ellagitannins and ellagic-acid-rich food, such as pomegranates, berries, and nuts. Compelling biological activities of urolithins together with variabilities between individuals in the metabolic capacity of the resident gut microbiota to produce urolithins, have suggested potential benefits of direct consumption of urolithins. Based on the structures of ellagic acid and urolithins, they might be expected to show endocrine effects. We report on their impact on the estrogen, androgen, glucocorticoid and thyroid-hormone receptors, as determined in vitro using reporter gene assays in the Hela9903 (estrogen receptor), MDA-kb2 (androgen and glucocorticoid receptors) and GH3.TRE-Luc (thyroid hormone receptor) cell lines. Urolithins A and B, but not ellagic acid and urolithin D, showed estrogenic activities on estrogen receptor subtype α under our assay conditions, with EC₅₀ values of 5.59 μM and 32.60 μM, respectively. Moreover, ellagic acid and urolithins A and D showed anti-thyroid hormonal activities (IC₅₀ values of 37.45 μM, 30.32 μM and 8.80 μM, respectively). Glucocorticoid and androgen agonist and antagonist activities were assessed using a luciferase reporter gene assay in the MDA-kb2 cell line. None of these tested compounds showed glucocorticoid agonist or antagonist activities, and ellagic acid showed weak androgen agonist activity, although only at the highest concentration tested. Detected estrogen and antithyroid activities warrant further risk assessment in relation to the exposure of urolithins in humans.

Detecting Secretory Proteins by Acoustic Droplet Ejection in Multiplexed High-Throughput Applications

Nearly one-third of the encoded proteome is comprised of secretory proteins that enable communication between cells and organ systems, playing a ubiquitous role in human health and disease. High-throughput detection of secreted proteins would enhance efforts to identify therapies for secretion-related diseases. Using the Z mutant of alpha-1 antitrypsin as a human secretory model, we have developed 1536-well high-throughput screening assays that utilize acoustic droplet ejection to transfer nanoliter volumes of sample for protein quantification. Among them, the acoustic reverse phase protein array (acoustic RPPA) is a multiplexable, low-cost immunodetection technology for native, endogenously secreted proteins from physiologically relevant model systems like stem cells that is compatible with plate-based instrumentation. Parallel assay profiling with the LOPAC¹²⁸⁰ chemical library validated performance and orthogonality between a secreted bioluminescent reporter and acoustic RPPA method by consistently identifying secretory modulators with comparable concentration response relationships. Here, we introduce a robust, multiplexed drug discovery platform coupling extracellular protein quantification by acoustic RPPA with intracellular and cytotoxicity analyses from single wells, demonstrating proof-of-principle applications for human induced pluripotent stem cell-derived hepatocytes.

Predicting the cytotoxicity of chemicals using ensemble learning methods and molecular fingerprints

The prediction of compound cytotoxicity is an important part of the drug discovery process. However, it usually appears as poor predictive performance because the datasets are high-throughput and have a class-imbalance problem. In this study, several strategies of performing a structure-activity relationship study for a cytotoxic endpoint in the AID364 dataset were explored to solve the class-imbalance problem. Random forest adaboost was used as the base learners for 10 types of molecular fingerprints and an ensemble method and six data-balancing methods were applied to balance the classes. As a result, the ensemble model using MACCS fingerprint was found to be the best, giving area under the curve of 85.2% ± 0.35%, sensitivity of 81.8% ± 0.65%, and specificity of 76.0% ± 0.12% in fivefold cross-validation and area under the curve of 78.8%, sensitivity of 55.5% and specificity of 78.5% in external validation. Good performance also appeared on other datasets with different sizes/degrees of imbalance. To explore the structural commonality of cytotoxic compounds, several substructures were identified as an important reference for substructure alerts. The convincing results indicate that the proposed models are helpful in predicting the cytotoxicity of chemicals.

Identification of Novel Molecules Targeting Cancer Stem Cells

Multiple studies focused on tumor heterogeneity and cellular hierarchies have demonstrated the role of cancer stem cells (CSC) in tumor initiation and recurrence. Colorectal cancer is one of the leading causes of cancer-related death and is hierarchically organized, with the majority of tumor cells descending from a small population of colon cancer stem cells (CCSCs). Such a rare self-renewing population is marked by the acquisition of distinct chromatin regulation and transcriptional programs. Fundamental molecular deviations between CCSCs and bulk tumor cells as well as normal tissues represent a unique therapeutic access to develop novel, selective anticancer therapies.In this chapter, we describe a methodological pipeline to identify novel molecules to selectively target human CCSC. We present a point-by-point description of a typical phenotypic molecular screening experiment, aiming to identify selective modulators of human CCSCs vs. normal intestinal progenitor cells.

Use of high-throughput enzyme-based assay with xenobiotic metabolic capability to evaluate the inhibition of acetylcholinesterase activity by organophosphorous pesticides

The inhibition of acetylcholinesterase (AChE) has pharmaceutical applications as well as potential neurotoxic effects. The in vivo metabolites of some chemicals including organophosphorus pesticides can become more potent AChE inhibitors compared to their parental compounds. To account for the effects of biotransformation, we have developed and characterized a high-throughput screening method for identifying AChE inhibitors that become active or more potent following xenobiotic metabolism. In this study, an enzyme-based assay was developed in 1536-well plates using recombinant human AChE combined with human or rat liver microsomes. The AChE activity was measured by two methods with different readouts: colorimetric and fluorescent. The assay exhibited exceptional performance characteristics including large assay signal window, low well-to-well variability and high reproducibility. The performance of the assays with microsomes was characterized by testing a group of known AChE inhibitors including parent compounds and their metabolites. Large potency differences between the parent compounds and the metabolites were observed in the assay with microsome addition. Both assay readouts were required for maximal sensitivity. These results demonstrate that this platform is a promising method to profile large numbers of chemicals that require metabolic activation for inhibiting AChE activity.

Resonant waveguide grating based assays for colloidal aggregate detection and promiscuity characterization in natural products

Small molecules, including natural compounds, in aqueous buffer that self-associate into colloidal aggregates is the main cause of false results in the early stage of drug discovery. Here we reported resonant waveguide grating (RWG) based assays to identify natural compound aggregation and characterize its influence on membrane receptors in living cells. We first applied a cell-free aggregation assay to determine compound critical aggregation concentration (CAC) values. Then we characterized the aggregators' influence on membrane receptors using three types of dynamic mass redistribution (DMR) assays. Results showed that colloidal aggregates may cause false activity in DMR desensitization assays; some of the false activities can be implied by the large response in DMR agonism assays and can further be identified by DMR antagonism assays. Furthermore, the aggregation mechanism was confirmed by addition of 0.025% tween-80, with cell signals attenuated and potency decreased. Finally, these observations were used for aggregate examination and promiscuity investigation of a traditional herbal medicine, Rhodiola rosea, which ultimately led to the revealing of the true target and reduced the risk of a bioactivity tracking process at the very first stage. This study highlights that the RWG based assays can be used as practical tools to distinguish between real and false hits to provide reliable results in the early stage of drug discovery.

Resonant waveguide grating based assays to eliminate colloidal aggregate induced false activity involving natural products.

Trimethine cyanine dyes as deep-red fluorescent indicators with high selectivity to the internal loop of the bacterial A-site RNA

We report that TO-PRO-3 functions as a deep-red fluorescent indicator for the internal loop structure of the bacterial (Escherichia coli) A-site, which enables the assessment of A-site binding capability of various test compounds including blue and even-green-emitting compounds.

Assessing molecular interactions with biophysical methods using the validation cross

There are numerous methods for studying molecular interactions. However, each method gives rise to false negative- or false positive binding results, stemming from artifacts of the scientific equipment or from shortcomings of the experimental format. To validate an initial positive binding result, additional methods need to be applied to cover the shortcomings of the primary experiment. The aim of such a validation procedure is to exclude as many artifacts as possible to confirm that there is a true molecular interaction that meets the standards for publishing or is worth investing considerable resources for follow-up activities in a drug discovery project. To simplify this validation process, a graphical scheme — the validation cross — can be used. This simple graphic is a powerful tool for identifying blind spots of a binding hypothesis, for selecting the most informative combination of methods to reveal artifacts and, in general, for understanding more thoroughly the nature of a validation process. The concept of the validation cross was originally introduced for the validation of protein–ligand interactions by NMR in drug discovery. Here, an attempt is made to expand the concept to further biophysical methods and to generalize it for binary molecular interactions.

Workflow for defining reference chemicals for assessing performance of in vitro assays

Instilling confidence in use of in vitro assays for predictive toxicology requires evaluation of assay performance. Performance is typically assessed using reference chemicals--compounds with defined activity against the test system target. However, developing reference chemical lists has historically been very resource-intensive. We developed a semi-automated process for selecting and annotating reference chemicals across many targets in a standardized format and demonstrate the workflow here. A series of required fields defines the potential reference chemical: the in vitro molecular target, pathway, or phenotype affected; and the chemical's mode (e.g. agonist, antagonist, inhibitor). Activity information was computationally extracted into a database from multiple public sources including non-curated scientific literature and curated chemical-biological databases, resulting in the identification of chemical activity in 2995 biological targets. Sample data from literature sources covering 54 molecular targets ranging from data-poor to data-rich was manually checked for accuracy. Precision rates were 82.7% from curated data sources and 39.5% from automated literature extraction. We applied the final reference chemical lists to evaluating performance of EPA's ToxCast program in vitro bioassays. The level of support, i.e. the number of independent reports in the database linking a chemical to a target, was found to strongly correlate with likelihood of positive results in the ToxCast assays, although individual assay performance had considerable variation. This overall approach allows rapid development of candidate reference chemical lists for a wide variety of targets that can facilitate performance evaluation of in vitro assays as a critical step in imparting confidence in alternative approaches.

Screening of the Pathogen Box reveals new starting points for anti-trypanosomal drug discovery

This study aimed to uncover new starting points for anti-trypansomal drug discovery through the screening of the Pathogen Box against Trypanosoma brucei brucei. Our study identified compounds 35, 39, 46, 53 and 56 whose activity and selectivity highlighted them as promising candidates with potential for further study and optimisation.

Advances with support vector machines for novel drug discovery

INTRODUCTION

Novel drug discovery remains an enormous challenge, with various computer-aided drug design (CADD) approaches having been widely employed for this purpose. CADD, specifically the commonly used support vector machines (SVMs), can employ machine learning techniques. SVMs and their variations offer numerous drug discovery applications, which range from the classification of substances (as active or inactive) to the construction of regression models and the ranking/virtual screening of databased compounds. Areas covered: Herein, the authors consider some of the applications of SVMs in medicinal chemistry, illustrating their main advantages and disadvantages, as well as trends in their utilization, via the available published literature. The aim of this review is to provide an up-to-date review of the recent applications of SVMs in drug discovery as described by the literature, thereby highlighting their strengths, weaknesses, and future challenges. Expert opinion: Techniques based on SVMs are considered as powerful approaches in early drug discovery. The ability of SVMs to classify active or inactive compounds has enabled the prioritization of substances for virtual screening. Indeed, one of the main advantages of SVMs is related to their potential in the analysis of nonlinear problems. However, despite successes in employing SVMs, the challenges of improving accuracy remain.

QSAR-Based Virtual Screening: Advances and Applications in Drug Discovery

Virtual screening (VS) has emerged in drug discovery as a powerful computational approach to screen large libraries of small molecules for new hits with desired properties that can then be tested experimentally. Similar to other computational approaches, VS intention is not to replace in vitro or in vivo assays, but to speed up the discovery process, to reduce the number of candidates to be tested experimentally, and to rationalize their choice. Moreover, VS has become very popular in pharmaceutical companies and academic organizations due to its time-, cost-, resources-, and labor-saving. Among the VS approaches, quantitative structure–activity relationship (QSAR) analysis is the most powerful method due to its high and fast throughput and good hit rate. As the first preliminary step of a QSAR model development, relevant chemogenomics data are collected from databases and the literature. Then, chemical descriptors are calculated on different levels of representation of molecular structure, ranging from 1D to nD, and then correlated with the biological property using machine learning techniques. Once developed and validated, QSAR models are applied to predict the biological property of novel compounds. Although the experimental testing of computational hits is not an inherent part of QSAR methodology, it is highly desired and should be performed as an ultimate validation of developed models. In this mini-review, we summarize and critically analyze the recent trends of QSAR-based VS in drug discovery and demonstrate successful applications in identifying perspective compounds with desired properties. Moreover, we provide some recommendations about the best practices for QSAR-based VS along with the future perspectives of this approach.

A Comparative Study of Fluorescence Assays in Screening for BRD4

Fluorescence assay technologies are commonly used in high-throughput screening because of their sensitivity and ease of use. Different technologies have their characteristics and the rationale for choosing one over the other can differ between projects because of factors such as availability of reagents, assay performance, and cost. Another important factor to consider is the assay susceptibility to artifacts, which is almost as important as the ability of the assay to pick up active compounds. Spending time and money on false positives or missing the opportunity to build chemistry around false negatives is something that every drug project tries to avoid. We used a BET family Bromodomain, BRD4(1), to explore the outcome of a screening campaign using three fluorescent assay technologies as primary assays. A diverse 7,038 compound set was screened in fluorescence lifetime, fluorescence polarization, and homogeneous time-resolved fluorescence to look at primary hit rates, compound overlap, and hit confirmation rates. The results show a difference between the fluorescence assay technologies with three separate hit lists and some overlap. The confirmed hits from each assay were further evaluated for translation into cells (NanoBRET™). Most of the actives confirmed in cells originated from compounds that overlapped between the assays. In addition, a well-annotated set of compounds with undesirable mechanism of inhibition was screened against BRD4(1) to compare the ability to discriminate true hits from artifact compounds. The results indicate a difference between the assays in their ability to generate false positives and negatives.

Evaluation of androgen assay results using a curated Hershberger database

A set of 39 reference chemicals with reproducible androgen pathway effects in vivo, identified in the companion manuscript [1], were used to interrogate the performance of the ToxCast/Tox 21 androgen receptor (AR) model based on 11 high throughput assays. Cytotoxicity data and specificity confirmation assays were used to distinguish assay loss-of-function from true antagonistic signaling suppression. Overall agreement was 66% (19/29), with ten additional inconclusive chemicals. Most discrepancies were explained using in vitro to in vivo extrapolation to estimate equivalent administered doses. The AR model had 100% positive predictive value for the in vivo response, i.e. there were no false positives, and chemicals with conclusive AR model results (agonist or antagonist) were consistently positive in vivo. Considering the lack of reproducibility of the in vivo Hershberger assay, the in vitro AR model may better predict specific AR interaction and can rapidly and cost-effectively screen thousands of chemicals without using animals.

NCI Program for Natural Product Discovery: A Publicly-Accessible Library of Natural Product Fractions for High-Throughput Screening

The US National Cancer Institute's (NCI) Natural Product Repository is one of the world's largest, most diverse collections of natural products containing over 230,000 unique extracts derived from plant, marine, and microbial organisms that have been collected from biodiverse regions throughout the world. Importantly, this national resource is available to the research community for the screening of extracts and the isolation of bioactive natural products. However, despite the success of natural products in drug discovery, compatibility issues that make extracts challenging for liquid handling systems, extended timelines that complicate natural product-based drug discovery efforts and the presence of pan-assay interfering compounds have reduced enthusiasm for the high-throughput screening (HTS) of crude natural product extract libraries in targeted assay systems. To address these limitations, the NCI Program for Natural Product Discovery (NPNPD), a newly launched, national program to advance natural product discovery technologies and facilitate the discovery of structurally defined, validated lead molecules ready for translation will create a prefractionated library from over 125,000 natural product extracts with the aim of producing a publicly-accessible, HTS-amenable library of >1,000,000 fractions. This library, representing perhaps the largest accumulation of natural-product based fractions in the world, will be made available free of charge in 384-well plates for screening against all disease states in an effort to reinvigorate natural product-based drug discovery.

High-Content Screening Campaign to Identify Compounds That Inhibit or Disrupt Androgen Receptor-Transcriptional Intermediary Factor 2 Protein-Protein Interactions for the Treatment of Prostate Cancer

Twenty percent of prostate cancer (PCa) patients develop a noncurable drug-resistant form of the disease termed castration-resistant prostate cancer (CRPC). Overexpression of Androgen Receptor (AR) coactivators such as transcriptional intermediary factor 2 (TIF2) is associated with poor CRPC patient outcomes. We describe the implementation of the AR-TIF2 protein-protein interaction biosensor (PPIB) assay in a high-content screening (HCS) campaign of 143,535 compounds. The assay performed robustly and reproducibly and enabled us to identify compounds that inhibited dihydrotestosterone (DHT)-induced AR-TIF2 protein-protein interaction (PPI) formation or disrupted preexisting AR-TIF2 PPIs. We used multiparameter HCS data z-scores to identify and deprioritize cytotoxic or autofluorescent outliers and confirmed the resulting qualified actives in triplicate. None of the confirmed AR-TIF2 PPIB inhibitors/disruptors exhibited activity in a p53-hDM2 PPIB counter screen, indicating that they were unlikely to be either nonselective PPI inhibitors or to interfere with the biosensor assay format. However, eight confirmed AR-TIF2 PPIB actives also inhibited the glucocorticoid receptor (GR) nuclear translocation counter screen by >50%. These compounds were deprioritized because they either lacked AR specificity/selectivity, or they inhibited a shared component of the AR and GR signaling pathways. Twenty-nine confirmed AR-TIF2 PPIB actives also inhibited the AR nuclear localization counter screen, suggesting that they might indirectly inhibit the AR-TIF2 PPIB assay rather than directly blocking/disrupting PPIs. A total of 62.2% of the confirmed actives inhibited the DHT-induced AR-TIF2 PPI formation in a concentration-dependent manner with IC₅₀s < 40 μM, and 59.4% also disrupted preexisting AR-TIF2 PPI complexes. Overall, the hit rate for the AR-TIF2 PPIB HCS campaign was 0.12%, and most hits inhibited AR-TIF2 PPI formation and disrupted preexisting AR-TIF2 complexes with similar AR-red fluorescent protein distribution phenotypes. Further secondary and tertiary hit characterization assays are underway to select AR-TIF2 PPI inhibitor/disruptor hits suitable for medicinal chemistry lead optimization and development into novel PCa/CRPC therapeutics.

Continuous assays for meprin alpha and beta using prolyl tripeptidyl aminopeptidase (PtP) from Porphyromonas gingivalis

Common assays for endoprotease activity of meprin α and β are based on cleavage of internally quenched substrates. Although direct and convenient, for meprins these assays bear disadvantages such as, e.g., significant substrate inhibition or potential fluorescence quenching by compounds applied in inhibitor analysis. Here, we present a novel continuous assay by introducing an auxiliary enzyme, prolyl tripeptidyl aminopeptidase (PtP) and the chromogenic substrate KKGYVADAP-p-nitroanilide. We provide a quick strategy for expression and one-step-purification of the auxiliary enzyme. The enzyme kinetic data for meprin α and β suggest hyperbolic v/S-characteristics, the kinetic parameters of substrate conversion by meprin β were K_m = 184 ± 32 μM and k_cat = 20 ± 4 s^-1. We also present conditions for the use of the fluorogenic substrate KKGYVADAP-AMC to assess meprin β activity. The assays were applied for determination of inhibitory parameters of the natural inhibitor actinonin and two recently published hydroxamates. Hence, we present two novel methods, which can be applied to assess inhibitory mechanism and potency with the attractive current drug targets meprin α and β. Furthermore, the assay might also provide implications for analysis of other endoproteases as well as their inhibitors.

Automated MALDI Target Preparation Concept: Providing Ultra-High-Throughput Mass Spectrometry–Based Screening for Drug Discovery

Label-free, mass spectrometric (MS) deciphering of enzymatic reactions by direct analysis of substrate-to-product conversion provides the next step toward more physiological relevant assays within drug discovery campaigns. Reduced risk of suffering from compound interference combined with diminished necessity for tailored signal mediators emphasizes the valuable role of label-free readouts. However, MS-based detection has not hitherto met high-throughput screening (HTS) requirements because of the lack of HTS-compatible sample introduction. In the present study, we report on a fully automated liquid-handling concept built in-house to concatenate biochemical assays with matrix-assisted laser desorption/ionization time-of-flight closing this technological gap. The integrated reformatting from 384- to 1536-well format enables cycle times of 0.6 s/sample for automated spotting and 0.4 s/sample for MS analysis, matching the requirements of HTS compatibility. In-depth examination of spotting quality, quantification accuracy, and instrument robustness together with the implementation of a protein tyrosine phosphatase 1B (PTP1B) inhibitor screening (4896 compounds) demonstrate the potential of the heavily inquired HTS integration of the label-free MS readout. Overall, the presented data demonstrate that the introduced automation concept makes label-free MS-based readouts accessible for HTS within drug discovery campaigns but also in other research areas requiring ultrafast MS-based detection.

Assay Guidance Manual: Quantitative Biology and Pharmacology in Preclinical Drug Discovery

The Assay Guidance Manual (AGM) is an eBook of best practices for the design, development, and implementation of robust assays for early drug discovery. Initiated by pharmaceutical company scientists, the manual provides guidance for designing a “testing funnel” of assays to identify genuine hits using high‐throughput screening (HTS) and advancing them through preclinical development. Combined with a workshop/tutorial component, the overall goal of the AGM is to provide a valuable resource for training translational scientists.

Modeling Small-Molecule Reactivity Identifies Promiscuous Bioactive Compounds

Scientists rely on high-throughput screening tools to identify promising small-molecule compounds for the development of biochemical probes and drugs. This study focuses on the identification of promiscuous bioactive compounds, which are compounds that appear active in many high-throughput screening experiments against diverse targets but are often false-positives which may not be easily developed into successful probes. These compounds can exhibit bioactivity due to nonspecific, intractable mechanisms of action and/or by interference with specific assay technology readouts. Such "frequent hitters" are now commonly identified using substructure filters, including pan assay interference compounds (PAINS). Herein, we show that mechanistic modeling of small-molecule reactivity using deep learning can improve upon PAINS filters when modeling promiscuous bioactivity in PubChem assays. Without training on high-throughput screening data, a deep learning model of small-molecule reactivity achieves a sensitivity and specificity of 18.5% and 95.5%, respectively, in identifying promiscuous bioactive compounds. This performance is similar to PAINS filters, which achieve a sensitivity of 20.3% at the same specificity. Importantly, such reactivity modeling is complementary to PAINS filters. When PAINS filters and reactivity models are combined, the resulting model outperforms either method alone, achieving a sensitivity of 24% at the same specificity. However, as a probabilistic model, the sensitivity and specificity of the deep learning model can be tuned by adjusting the threshold. Moreover, for a subset of PAINS filters, this reactivity model can help discriminate between promiscuous and nonpromiscuous bioactive compounds even among compounds matching those filters. Critically, the reactivity model provides mechanistic hypotheses for assay interference by predicting the precise atoms involved in compound reactivity. Overall, our analysis suggests that deep learning approaches to modeling promiscuous compound bioactivity may provide a complementary approach to current methods for identifying promiscuous compounds.

Development of a High-Throughput Biochemical Assay to Screen for Inhibitors of Aerobactin Synthetase IucA

Acquiring sufficient quantities of iron to support survival is often a critical limitation for pathogenic bacteria. To meet this demand, bacteria have evolved unique strategies to scavenge iron and circumvent the nutritional immunity exerted by their hosts. One common strategy, which is often a key virulence factor for bacterial pathogens, involves the synthesis, secretion, and reuptake of iron chelators known as siderophores. In vitro and in vivo studies have demonstrated that the siderophore aerobactin is critical for virulence in the hypervirulent pathotype of Klebsiella pneumoniae (hvKP). Given the high rate of multidrug resistance in K. pneumoniae, and in light of the ever-increasing demand for novel Gram-negative therapeutic targets, we identified aerobactin production as a promising antivirulence target in hvKP. Herein, we describe the development of a high-throughput biochemical assay for identifying inhibitors of the aerobactin synthetase IucA. The assay was employed to screen ~110,000 compounds across several commercially available small-molecule libraries. IucA inhibitors with activity at micromolar concentrations were identified in our screening campaigns and confirmed using secondary orthogonal assays. However, the most potent compounds also exhibited some properties commonly observed with promiscuous/nonspecific inhibitors, including incubation time and target enzyme concentration dependence, as well as the potential to antagonize unrelated enzymes.

A natural compound, aristoyagonine, is identified as a potent bromodomain inhibitor by mid-throughput screening

Bromodomain-containing protein 4 (Brd4) is known to play a key role in tumorigenesis. It binds acetylated histones to regulate the expression of numerous genes. Because of the importance of brd4 in tumorigenesis, much research has been undertaken to develop brd4 inhibitors with therapeutic potential. As a result, various scaffolds for bromodomain inhibitors have been identified. To discover new scaffolds, we performed mid-throughput screening using two different enzyme assays, alpha-screen and ELISA. We found a novel bromodomain inhibitor with a unique scaffold, aristoyagonine. This natural compound showed inhibitory activity in vitro and tumor growth inhibition in a Ty82-xenograft mouse model. In addition, we tested Brd4 inhibitors in gastric cancer cell lines, and found that aristoyagonine exerted cytotoxicity not only in I-BET-762-sensitive cancer cells, but also in I-BET-762-resistant cancer cells. This is the first paper to describe a natural compound as a Brd4 bromodomain inhibitor.

Chemical probes of Skp2-mediated p27 ubiquitylation and degradation

Skp2 is a member of the F-box family of proteins that serve as substrate-specific adaptors in Skp1-CUL1-ROC1-F-box (SCF) E3 ubiquitin ligases. Skp2 (Fbxl1) directly binds to the tumor suppressor p27 in the context of the SCF^Skp2 E3 ubiquitin ligase to ubiquitylate and target-phosphorylated p27 for proteasomal degradation. As p27 is a powerful suppressor of growth in a variety of cells, and as Skp2 is also overexpressed in many human cancers, Skp2 is considered an oncogene and an intriguing drug target. However, despite 20 years of investigation, a valid chemical inhibitor of Skp2-mediated degradation of p27 has not been identified. Recently, an increasing number of compounds designed to have this bioactivity have been reported. Here, we conduct a meta-analysis of the evidence regarding bioactivity, structure, and medicinal chemistry in order to evaluate and compare these Skp2 inhibitor compounds. Despite chemically diverse compounds with a wide array of Skp2-mediated p27 ubiquitylation inhibition properties reported by several independent groups, no current chemical probe formally qualifies as a validated pharmaceutical hit compound. This finding suggests that our knowledge of the structural biochemistry of the Skp2-p27 complex remains incomplete and highlights the need for novel modes of inquiry.

A Scalable Pipeline for High-Throughput Flow Cytometry

Flow cytometry (FC) provides high-content data for a variety of applications, including phenotypic analysis of cell surface and intracellular markers, characterization of cell supernatant or lysates, and gene expression analysis. Historically, sample preparation, acquisition, and analysis have presented as a bottleneck for running such types of assays at scale. This article will outline the solutions that have been implemented at Novartis which have allowed high-throughput FC to be successfully conducted and analyzed for a variety of cell-based assays. While these experiments were generally conducted to measure phenotypic responses from a well-characterized and information-rich small molecular probe library known as the Mechanism-of-Action (MoA) Box, they are broadly applicable to any type of test sample. The article focuses on application of automated methods for FC sample preparation in 384-well assay plates. It also highlights a pipeline for analyzing large volumes of FC data, covering a visualization approach that facilitates review of screen-level data by dynamically embedding FlowJo (FJ) workspace images for each sample into a Spotfire file, directly linking them to the metric being observed. Finally, an application of these methods to a screen for MHC-I expression upregulators is discussed.

Reviewing Hit Discovery Literature for Difficult Targets: Glutathione Transferase Omega-1 as an Example

Early stage drug discovery reporting on relatively new or difficult targets is often associated with insufficient hit triage. Literature reviews of such targets seldom delve into the detail required to critically analyze the associated screening hits reported. Here we take the enzyme glutathione transferase omega-1 (GSTO1-1) as an example of a relatively difficult target and review the associated literature involving small-molecule inhibitors. As part of this process we deliberately pay closer-than-usual attention to assay interference and hit quality aspects. We believe this Perspective will be a useful guide for future development of GSTO1-1 inhibitors, as well serving as a template for future review formats of new or difficult targets.

Nuisance Compounds, PAINS Filters, and Dark Chemical Matter in the GSK HTS Collection

High-throughput screening (HTS) hits include compounds with undesirable properties. Many filters have been described to identify such hits. Notably, pan-assay interference compounds (PAINS) has been adopted by the community as the standard term to refer to such filters, and very useful guidelines have been adopted by the American Chemical Society (ACS) and subsequently triggered a healthy scientific debate about the pitfalls of draconian use of filters. Using an inhibitory frequency index, we have analyzed in detail the promiscuity profile of the whole GlaxoSmithKline (GSK) HTS collection comprising more than 2 million unique compounds that have been tested in hundreds of screening assays. We provide a comprehensive analysis of many previously published filters and newly described classes of nuisance structures that may serve as a useful source of empirical information to guide the design or growth of HTS collections and hit triaging strategies.

Characterization and Use of TurboLuc Luciferase as a Reporter for High-Throughput Assays

Luciferase-based reporter assays are powerful tools for monitoring gene expression in cells because of their ultrasensitive detection capacity and wide dynamic range. Here we describe the characterization and use of a luciferase reporter enzyme derived from the marine copepod Metridia luciferase family, referred to as TurboLuc luciferase (TurboLuc). To develop TurboLuc, the wild-type luciferase was modified to decrease its size, increase brightness, slow luminescent signal decay, and provide for efficient intracellular expression. To determine the enzyme susceptibility to compound inhibition and judge the suitability of using of TurboLuc as a reporter in screening assays, purified TurboLuc enzyme was screened for inhibitors using two different compound libraries. No inhibitors of this enzyme were identified in a library representative of typical diverse low molecular weight (LMW) compounds using a purified TurboLuc enzyme assay supporting that such libraries will show very low interference with this enzyme. We were able to identify a few inhibitors from a purified natural product library which can serve as useful tools to validate assays using TurboLuc. In addition to the inhibitor profile for TurboLuc we describe the use of this reporter in cells employing miniaturized assay volumes within 1536-well plates. TurboLuc luciferase is the smallest luciferase reporter enzyme described to date (16 kDa), shows bright luminescence and low interference by LMW compounds, and therefore should provide an ideal reporter in assays applied to high-throughput screening.

ALARM NMR for HTS triage and chemical probe validation

Nonspecific target engagement by test compounds and purported chemical probes is a significant source of assay interference and promiscuous bioactivity in high-throughput screening (HTS) and chemical biology. Most counter-screens for thiol-reactive compounds utilize mass spectrometry or fluorescence detection, and non-proteinaceous reporters like glutathione that may not always approximate the reactivity of protein side-chains. By contrast, a La assay to detect reactive molecules by nuclear magnetic resonance (ALARM NMR) is an industry-developed protein-based [¹H-¹³C]-heteronuclear multiple quantum coherence (HMQC) NMR counter-screen to identify nonspecific protein interactions by test compounds by reporting their tendencies to modulate the human La antigen conformation. This Current Protocol is a users-guide to the production of the ¹³C-labeled La antigen reporter protein, the reaction of test compounds with this reporter protein, as well as the collection and analysis of characteristic NMR spectra. Combined with other assay interference counter-screens, this assay will enhance chemical biology by helping researchers better prioritize chemical matter and which will increase the number of tractable HTS screening actives and aid in the development of better chemical probes.

Identification of inhibitors of Tartrate-resistant acid phosphatase (TRAP/ACP5) activity by small-molecule screening

Tartrate-resistant acid phosphatase (TRAP/ACP5) occurs as two isoforms-TRAP 5a with low enzymatic activity due to a loop interacting with the active site and the more active TRAP isoform 5b generated upon proteolytic cleavage of this loop. TRAP has been implicated in several diseases, including cancer. Thus, this study set out to identify small-molecule inhibitors of TRAP activity. A microplate-based enzymatic assay for TRAP 5b was applied in a screen of 30,315 compounds, resulting in the identification of 90 primary hits. After removal of promiscuous compounds, unwanted groups, and false positives by orthogonal assays and three-concentration validation, the properties of 52 compounds were further investigated to better understand their mechanism of action. Full-concentration-response curves for these compounds were established under different enzyme concentrations and (pre)incubation times to remove compounds with inconsistent results and low potencies. Full-concentration-response curves were also performed for both isoforms, to examine isoform prevalence. Filtering led to six prioritized compounds, representing different clusters. One of these, CBK289001 or (6S)-6-[3-(2H-1,3-benzodioxol-5-yl)-1,2,4-oxadiazol-5-yl]-N-(propan-2-yl)-1H,4H,5H,6H,7H-imidazo[4,5-c]pyridine-5-carboxamide, demonstrated efficacy in a migration assay and IC₅₀ values from 4 to 125 μm. Molecular docking studies and analog testing were performed around CBK289001 to provide openings for further improvement toward more potent blockers of TRAP activity.