Comparison of miniaturized time-resolved fluorescence resonance energy transfer and enzyme-coupled luciferase high-throughput screening assays to discover inhibitors of Rho-kinase II (ROCK-II)

Kinases are important drug discovery targets for a wide variety of therapeutic indications; consequently, the measurement of kinase activity remains a common high-throughput screening (HTS) application. Recently, enzyme-coupled luciferase-kinase (LK) format assays have been introduced. This format measures luminescence resulting from metabolism of adenosine triphosphate (ATP) via a luciferin/luciferase-coupled reaction. In the research presented here, 1536-well format time-resolved fluorescence resonance energy transfer (TR-FRET) and LK assays were created to identify novel Rho-associated kinase II (ROCK-II) inhibitors. HTS campaigns for both assays were conducted in this miniaturized format. It was found that both assays were able to consistently reproduce the expected pharmacology of inhibitors known to be specific to ROCK-II (fasudil IC50: 283 +/- 27 nM and 336 +/- 54 nM for TR-FRET and LK assays, respectively; Y-27632 IC50: 133 +/- 7.8 nM and 150 +/- 22 nM for TR-FRET and LK assays, respectively). In addition, both assays proved robust for HTS efforts, demonstrating excellent plate Z' values during the HTS campaign (0.84 +/- 0.03; 0.72 +/- 0.05 for LK and TR-FRET campaigns, respectively). Both formats identified scaffolds of known and novel ROCK-II inhibitors with similar sensitivity. A comparison of the performance of these 2 assay formats in an HTS campaign was enabled by the existence of a subset of 25,000 compounds found in both our institutional and the Molecular Library Screening Center Network screening files. Analysis of the HTS campaign results based on this subset of common compounds showed that both formats had comparable total hit rates, hit distributions, amount of hit clusters, and format-specific artifact. It can be concluded that both assay formats are suitable for the discovery of ROCK-II inhibitors, and the choice of assay format depends on reagents and/or screening technology available.     

Hypothesis testing in high-throughput screening for drug discovery

Following the success of small-molecule high-throughput screening (HTS) in drug discovery, other large-scale screening techniques are currently revolutionizing the biological sciences. Powerful new statistical tools have been developed to analyze the vast amounts of data in DNA chip studies, but have not yet found their way into compound screening. In HTS, characterization of single-point hit lists is often done only in retrospect after the results of confirmation experiments are available. However, for prioritization, for optimal use of resources, for quality control, and for comparison of screens it would be extremely valuable to predict the rates of false positives and false negatives directly from the primary screening results. Making full use of the available information about compounds and controls contained in HTS results and replicated pilot runs, the Z score and from it the p value can be estimated for each measurement. Based on this consideration, we have applied the concept of p-value distribution analysis (PVDA), which was originally developed for gene expression studies, to HTS data. PVDA allowed prediction of all relevant error rates as well as the rate of true inactives, and excellent agreement with confirmation experiments was found.     

Oncology drug discovery applications using the FMAT 8100 HTS system

High-throughput screening (HTS) for potential anticancer agents requires a broad portfolio of assay platforms that may include kinase enzyme assays, protein-protein binding assays, and functional cell-based apoptosis assays. The authors have explored the use of fluorometric microvolume assay technology (the FMAT 8100 HTS System) in three distinct homogeneous HTS assays: (1). a Src tyrosine kinase enzyme assay, (2). a Grb2-SH2 protein-peptide interaction assay, and (3). an annexin V binding apoptosis assay. Data obtained from all three assays suggest that the FMAT system should facilitate the implementation of homogeneous assays for a wide variety of molecular targeted and cell-based screens.     

Improved statistical methods for hit selection in high-throughput screening

High-throughput screening (HTS) plays a central role in modern drug discovery, allowing the rapid screening of large compound collections against a variety of putative drug targets. HTS is an industrial-scale process, relying on sophisticated automation, control, and state-of-the art detection technologies to organize, test, and measure hundreds of thousands to millions of compounds in nano- to microliter volumes. Despite this high technology, hit selection for HTS is still typically done using simple data analysis and basic statistical methods. The authors discuss in this article some shortcomings of these methods and present alternatives based on modern methods of statistical data analysis. Most important, they describe and show numerous real examples from the biologist-friendly Stat Server HTS application (SHS), a custom-developed software tool built on the commercially available S-PLUS and StatServer statistical analysis and server software. This system remotely processes HTS data using powerful and sophisticated statistical methodology but insulates users from the technical details by outputting results in a variety of readily interpretable graphs and tables.     

Statistical and graphical methods for quality control determination of high-throughput screening data

High-throughput screening (HTS) is used in modern drug discovery to screen hundreds of thousands to millions of compounds on selected protein targets. It is an industrial-scale process relying on sophisticated automation and state-of-the-art detection technologies. Quality control (QC) is an integral part of the process and is used to ensure good quality data and mini mize assay variability while maintaining assay sensitivity. The authors describe new QC methods and show numerous real examples from their biologist-friendly Stat Server HTS application, a custom-developed software tool built from the commercially available S-PLUS and Stat Server statistical analysis and server software. This system remotely processes HTS data using powerful and sophisticated statistical methodology but insulates users from the technical details by outputting results in a variety of readily interpretable graphs and tables. It allows users to visualize HTS data and examine assay performance during the HTS campaign to quickly react to or avoid quality problems.     

A novel platform for accelerated pharmacodynamic profiling for lead optimization of anticancer drug candidates

Oncology drug discovery is, by definition, a target-rich enterprise. High-throughput screening (HTS) laboratories have supported a wide array of molecularly targeted and chemical genomic approaches for anticancer lead generation, and the number of hits emerging from such campaigns has increased dramatically. Although automation of HTS processes has eliminated primary screening as a bottleneck, the demands on secondary screening in appropriate cell-based assays have increased concomitantly with the numbers of hits delivered to therapeutic area laboratories. The authors describe herein the implementation of a novel platform using off-the-shelf solutions that have allowed them to efficiently characterize hundreds of HTS hits using a palette of Western blot-based pharmacodynamic assays. The platform employs a combination of a flatbed bufferless SDS-PAGE system, a dry ultra-rapid electroblotting apparatus, and a highly sensitive and quantitative infrared imaging system. Cumulatively, this platform has significantly reduced the cycle time for HTS hit evaluation. In addition, the routine use of this platform has resulted in higher quality data that have allowed the development of structure-activity databases that have tangibly improved lead optimization. The authors describe in detail the application of this platform, designated the Accelerated Pharmaco-Dynamic Profiler (APDP), to the annotation of inhibitors of 2 attractive oncology targets, BRAF kinase and Hsp90.     

Reducing agents affect inhibitory activities of compounds: results from multiple drug targets

High-throughput screening (HTS) of large compound libraries has become a commonly used method for the identification of drug leads, and nonphysiological reducing agents have been widely used for HTS. However, a comparison of the difference in the HTS results based on the choice of reducing agent used and potency comparisons of selected inhibitors has not been done with the physiological reducing agent reduced glutathione (GSH). Here, we compared the effects of three reducing agents-dithiothreitol (DTT), β-mercaptoethanol (β-MCE), and tris(2-carboxyethyl)phosphine (TCEP)-as well as GSH against three drug target proteins. Approximately 100,000 compounds were computationally screened for each target protein, and experimental testing of high-scoring compounds (~560 compounds) with the four reducing agents surprisingly produced many nonoverlapping hits. More importantly, we found that various reducing agents altered inhibitor potency (IC(50)) from approximately 10 μM with one reducing agent to complete loss (IC(50)>200 μM) of inhibitory activity with another reducing agent. Therefore, the choice of reducing agent in an HTS is critical because this may lead to the pursuit of falsely identified active compounds or failure to identify the true active compounds. We demonstrate the feasibility of using GSH for in vitro HTS assays with these three target enzymes.     

Multiplexing nuclear receptors for agonist identification in a cell-based reporter gene high-throughput screen

High-throughput screening (HTS) has become an essential part of the drug discovery process. Due to the rising requirements for both data quality and quantity, along with increased screening cost and the demand to shorten the time for lead identification, increasing throughput and cost-effectiveness has become a necessity in the hit identification process. The authors present a multiplexed HTS for 2 nuclear receptors, the farnesoid X-activated receptor and the peroxisome proliferator-activated receptor delta in a viable cell-based reporter gene assay. The 2 nuclear receptors were individually transfected into human hepatoma cells, and the transient transfected cell lines were pooled for the multiplexed screen. Hits identified by the multiplexed screen are similar to those identified by the individual receptor screens. Furthermore, the multiplexed screen provides selectivity information if ligands selective for one and not the other receptor are one of the hit criteria. The data demonstrate that multiplexing nuclear receptors can be a simple, efficient, cost-effective, and reliable alternative to traditional HTS of individual targets without compromising data quality.     

Evaluation of division-arrested cells for cell-based high-throughput screening and profiling

Just-in-time cell supply for cell-based high-throughput screening (HTS) is frequently problematic. In addition to scheduling and logistical issues, quality issues and variability due to passage effect, cell cycle, or confluency contribute to day-to-day signal variability in the course of cell-based HTS campaigns. Cell division-arrest and cryopreservation technologies permit the use of cells as assay-ready reagents for HTS and other cell-based profiling and structure-activity studies. In this report, the authors compare division-arrested and dividing cells in 2 assay types that are dependent on movement of proteins within or through cell membranes: a receptor tyrosine kinase assay involving A431 cells responsive to epidermal growth factor, and a secretion reporter assay, which measures secretion of a reporter gene, secreted alkaline phosphatase. In both assays, dividing and division-arrested cells yielded similar basal and maximal signals at a given cell density. Similar IC50s were obtained for reference inhibitors in each assay, type in both dividing and division-arrested cells. In addition, for the secretion reporter assay, when comparing IC50s obtained from 44 compounds randomly chosen from a primary screening hit list, the rank order of potency obtained from dividing cells and division-arrested cells was essentially identical. Furthermore, the results show that, under certain assay conditions, data generated using division-arrested cells are less variable than those generated using dividing cells. In summary, the results suggest that, in many cases, division-arrested cells can substitute for dividing cells and offer certain advantages for cell-based assays.     

MScreen: An Integrated Compound Management and High-Throughput Screening Data Storage and Analysis System

High-throughput screening (HTS) has historically been used by the pharmaceutical industry to rapidly test hundreds of thousands of compounds to identify potential drug candidates. More recently, academic groups have used HTS to identify new chemical probes or small interfering RNA (siRNA) that can serve as experimental tools to examine the biology or physiology of novel proteins, processes, or interactions. HTS presents a significant challenge with the vast and complex nature of data generated. This report describes MScreen, a Web-based, open-source cheminformatics application for chemical library and siRNA plate management, primary HTS and dose-response data handling, structure search, and administrative functions. Each project in MScreen can be secured with passwords or shared in an open-information environment that enables collaborators to easily compare data from many screens, providing a useful means to identify compounds with desired selectivity. Unique features include compound, substance, mixture, and siRNA plate creation and formatting; automated dose-response fitting and quality control (QC); and user, target, and assay method administration. MScreen provides an effective means to facilitate HTS information handling and analysis in the academic setting so that users can efficiently view their screening data and evaluate results for follow-up.     

TR-FRET-based high-throughput screening assay for identification of UBC13 inhibitors

UBC13 is a noncanonical ubiquitin conjugating enzyme (E2) that has been implicated in a variety of cellular signaling processes due to its ability to catalyze formation of lysine 63-linked polyubiquitin chains on various substrates. In particular, UBC13 is required for signaling by a variety of receptors important in immune regulation, making it a candidate target for inflammatory diseases. UBC13 is also critical for double-strand DNA repair and thus a potential radiosensitizer and chemosensitizer target for oncology. The authors developed a high-throughput screening (HTS) assay for UBC13 based on the method of time-resolved fluorescence resonance energy transfer (TR-FRET). The TR-FRET assay combines fluorochrome (Fl)-conjugated ubiquitin (fluorescence acceptor) with terbium (Tb)-conjugated ubiquitin (fluorescence donor), such that the assembly of mixed chains of Fl- and Tb-ubiquitin creates a robust TR-FRET signal. The authors defined conditions for optimized performance of the TR-FRET assay in both 384- and 1536-well formats. Chemical library screens (total 456 865 compounds) were conducted in high-throughput mode using various compound collections, affording superb Z' scores (typically >0.7) and thus validating the performance of the assays. Altogether, the HTS assays described here are suitable for large-scale, automated screening of chemical libraries in search of compounds with inhibitory activity against UBC13.     

High-throughput determination of mode of inhibition in lead identification and optimization

After finishing the primary high-throughput screening, the screening team is often faced with thousands of hits to be evaluated further. Effective filtering of these hits is crucial in identifying leads. Mode of inhibition (MOI) study is extremely useful in validating whether the observed compound activity is specific to the biological target. In this article, the authors describe a high-throughput MOI determination method for evaluating thousands of compounds using an existing screening infrastructure. Based on enzyme or receptor kinetics theory, the authors developed the method by measuring the ratio of IC(50) or percent inhibition at 2 carefully chosen substrate or ligand concentrations to define an inhibitor as competitive, uncompetitive, or noncompetitive. This not only facilitates binning of HTS hits according to their MOI but also greatly expands HTS utility in support of the medicinal chemistry team's lead optimization practice. Three case studies are presented to demonstrate how the method was applied successfully in 3 discovery programs targeting either an enzyme or a G-protein-coupled receptor.     

Ranking the selectivity of PubChem screening hits by activity-based protein profiling: MMP13 as a case study

High-throughput screening (HTS) has become an integral part of academic and industrial efforts aimed at developing new chemical probes and drugs. These screens typically generate several 'hits', or lead active compounds, that must be prioritized for follow-up medicinal chemistry studies. Among primary considerations for ranking lead compounds is selectivity for the intended target, especially among mechanistically related proteins. Here, we show how the chemical proteomic technology activity-based protein profiling (ABPP) can serve as a universal assay to rank HTS hits based on their selectivity across many members of an enzyme superfamily. As a case study, four metalloproteinase-13 (MMP13) inhibitors of similar potency originating from a publically supported HTS and reported in PubChem were tested by ABPP for selectivity against a panel of 27 diverse metalloproteases. The inhibitors could be readily separated into two groups: (1) those that were active against several metalloproteases and (2) those that showed high selectivity for MMP13. The latter set of inhibitors was thereby designated as more suitable for future medicinal chemistry optimization. We anticipate that ABPP will find general utility as a platform to rank the selectivity of lead compounds emerging from HTS assays for a wide variety of enzymes.     

Enrichment of extremely noisy high-throughput screening data using a naïve Bayes classifier

The noise level of a high-throughput screening (HTS) experiment depends on various factors such as the quality and robustness of the assay itself and the quality of the robotic platform. Screening of compound mixtures is noisier than screening single compounds per well. A classification model based on na?ve Bayes (NB) may be used to enrich such data. The authors studied the ability of the NB classifier to prioritize noisy primary HTS data of compound mixtures (5 compounds/well) in 4 campaigns in which the percentage of noise presumed to be inactive compounds ranged between 81% and 91%. The top 10% of the compounds suggested by the classifier captured between 26% and 45% of the active compounds. These results are reasonable and useful, considering the poor quality of the training set and the short computing time that is needed to build and deploy the classifier.     

Miniaturization of whole live cell-based GPCR assays using microdispensing and detection systems

Cell-based beta-lactamase reporter gene assays designed to measure the functional responses of G-protein-coupled receptors (GPCRs) were miniaturized to less than 2 microL total assay volume in a 3456-well microplate. Studies were done to evaluate both receptor agonists and antagonists. The pharmacology of agonists and antagonists for target GPCRs originally developed in a 96-well format was recapitulated in a 3456-well microplate format without compromising data quality or EC(50)/IC(50) precision. These assays were employed in high-throughput screening campaigns, allowing the testing of more than 150,000 compounds in 8 h. The instrumentation used and practical aspects of the assay development are discussed.     

Virtual screening to enrich hit lists from high-throughput screening: a case study on small-molecule inhibitors of angiogenin

"Hit lists" generated by high-throughput screening (HTS) typically contain a large percentage of false positives, making follow-up assays necessary to distinguish active from inactive substances. Here we present a method for improving the accuracy of HTS hit lists by computationally based virtual screening (VS) of the corresponding chemical libraries and selecting hits by HTS/VS consensus. This approach was applied in a case study on the target-enzyme angiogenin, a potent inducer of angiogenesis. In conjunction with HTS of the National Cancer Institute Diversity Set and ChemBridge DIVERSet E (approximately 18,000 compounds total), VS was performed with two flexible library docking/scoring methods, DockVision/Ludi and GOLD. Analysis of the results reveals that dramatic enrichment of the HTS hit rate can be achieved by selecting compounds in consensus with one or both of the VS functions. For example, HTS hits ranked in the top 2% by GOLD included 42% of the true hits, but only 8% of the false positives; this represents a sixfold enrichment over the HTS hit rate. Notably, the HTS/VS method was effective in selecting out inhibitors with midmicromolar dissociation constants typical of leads commonly obtained in primary screens.     

Quantitative assessment of hit detection and confirmation in single and duplicate high-throughput screenings

The process of identifying active targets (hits) in high-throughput screening (HTS) usually involves 2 steps: first, removing or adjusting for systematic variation in the measurement process so that extreme values represent strong biological activity instead of systematic biases such as plate effect or edge effect and, second, choosing a meaningful cutoff on the calculated statistic to declare positive compounds. Both false-positive and false-negative errors are inevitable in this process. Common control or estimation of error rates is often based on an assumption of normal distribution of the noise. The error rates in hit detection, especially false-negative rates, are hard to verify because in most assays, only compounds selected in primary screening are followed up in confirmation experiments. In this article, the authors take advantage of a quantitative HTS experiment in which all compounds are tested 42 times over a wide range of 14 concentrations so true positives can be found through a dose-response curve. Using the activity status defined by dose curve, the authors analyzed the effect of various data-processing procedures on the sensitivity and specificity of hit detection, the control of error rate, and hit confirmation. A new summary score is proposed and demonstrated to perform well in hit detection and useful in confirmation rate estimation. In general, adjusting for positional effects is beneficial, but a robust test can prevent overadjustment. Error rates estimated based on normal assumption do not agree with actual error rates, for the tails of noise distribution deviate from normal distribution. However, false discovery rate based on empirically estimated null distribution is very close to observed false discovery proportion.     

The confirmation rate of primary hits: a predictive model

HTS data from primary screening are usually analyzed by setting a cutoff for activity, in order to minimize both false-negative and false-positive rates. An alternative approach, based on a calculated probability of being active, is presented here. Given the predicted confirmation rate derived from this probability, the number of primary positives selected for follow-up can be optimized to maximize the number of true positives without picking too many false positives. Typical cutoff-determining methods are more serendipitous in their nature and not easily optimized in an effort to optimize screening efforts. An additional advantage of calculating a probability of being active for each compound screened is that orthogonal mixtures can be deconvoluted without presetting a deconvolution threshold. An important consequence of using the probability of being active with orthogonal mixtures is that individual compound screening results can be recorded irrespective of whether the assays were performed on single compounds or on cocktails.     

SpeedScreen: The "missing link" between genomics and lead discovery

SpeedScreen is a novel, label-free, in-solution, affinity-based selection methodology for high-throughput screening (HTS) developed at Novartis Pharma. The SpeedScreen protocol comprises in-solution affinity selection, followed by size exclusion chromatography in combination with microbore-liquid-chromatography/electrospray-ionization mass spectrometry (micro-LC/ESI-MS). The authors describe the basic concept behind assay development, HTS, and data analysis with the SpeedScreen technology. Advantages and limitations of SpeedScreen compared to alternative screening technologies are discussed, and an example is given from a SpeedScreen campaign applying this innovative affinity selection concept in HTS.     

Efficient hit-finding approaches for histone methyltransferases: the key parameters

For many novel epigenetics targets the chemical ligand space and structural information were limited until recently and are still largely unknown for some targets. Hit-finding campaigns are therefore dependent on large and chemically diverse libraries. In the specific case of the histone methyltransferase G9a, the authors have been able to apply an efficient process of intelligent selection of compounds for primary screening, rather than screening the full diverse deck of 900 000 compounds to identify hit compounds. A number of different virtual screening methods have been applied for the compound selection, and the results have been analyzed in the context of their individual success rates. For the primary screening of 2112 compounds, a FlashPlate assay format and full-length histone H3.1 substrate were employed. Validation of hit compounds was performed using the orthogonal fluorescence lifetime technology. Rated by purity and IC(50) value, 18 compounds (0.9% of compound screening deck) were finally considered validated primary G9a hits. The hit-finding approach has led to novel chemotypes being identified, which can facilitate hit-to-lead projects. This study demonstrates the power of virtual screening technologies for novel, therapeutically relevant epigenetics protein targets.