Comparison of assay technologies for a tyrosine kinase assay generates different results in high throughput screening

In today's high-throughput screening (HTS) environment, an increasing number of assay detection technologies are routinely utilized in lead finding programs. Because of the relatively broad applicability of several of these technologies, one is often faced with a choice of which technology to utilize for a specific assay. The aim of this study was to address the question of whether the same compounds would be identified from screening a set of samples in three different versions of an HTS assay. Here, three different versions of a tyrosine kinase assay were established using scintillation proximity assay (SPA), homogeneous time-resolved fluorescence resonance energy transfer (HTR-FRET), and fluorescence polarization (FP) technologies. In this study, 30,000 compounds were evaluated in each version of the kinase assay in primary screening, deconvolution, and dose-response experiments. From this effort, there was only a small degree of overlap of active compounds identified subsequent to the deconvolution experiment. When all active compounds were then profiled in all three assays, 100 and 101 active compounds were identified in the HTR-FRET and FP assays, respectively. In contrast, 40 compounds were identified in the SPA version of the kinase assay, whereas all of these compounds were detected in the HTR-FRET assay only 35 were active in the FP assay. Although there was good correlation between the IC(50) values obtained in the HTR-FRET and FP assays, poor correlations were obtained with the IC(50) values obtained in the SPA assay. These findings suggest that significant differences can be observed from HTS depending on the assay technology that is utilized, particularly in assays with high hit rates.     

Probing the primary screening efficiency by multiple replicate testing: a quantitative analysis of hit confirmation and false screening results of a biochemical assay

Despite a large body of references on assay development, assay optimization, strategies, and methodologies for high-throughput screening (HTS), there have been few reports on investigations of the efficiency of primary screening in a systematic and quantitative manner for a typical HTS process. Recently, the authors investigated the primary hit comparison and the effect of measurement variability by screening a library of approximately 25,000 random compounds in multiple replicate tests in a nuclear receptor recruitment assay with 2 different assay detection technologies. In this report, we utilized these sets of multiple replicate screening data from a different perspective and conducted a systematic data analysis in order to gain some insights into the hit-finding efficiency of a typical primary screening process. Specifically, hit confirmation, false-positive (declaration) rates, and false-negative rates at different hit cutoff limits were explored and calculated from the 2 different assay formats. Results and analyses provided some quantitative estimation regarding the reliability and efficiency of the primary screening process. For the 2 assay formats tested in this report, the confirmation rate (activity repeated at or above a certain hit limit) was found to be 65% or above. It was also suggested that, at least in this case, applying some hit-selection strategies, it is possible to decrease the number of false-negative or false-positive hits without significantly increasing the efforts in primary screening.     

HTS promiscuity analyses for accelerating decision making

Frequent hitters are compounds that are detected as a "hit" in multiple high-throughput screening (HTS) assays. Such behavior is specific (e.g., target family related) or unspecific (e.g., reactive compounds) or can result from a combination of such behaviors. Detecting such hits while predicting the underlying reason behind their promiscuous behavior is desirable because it provides valuable information not only about the compounds themselves but also about the assay methodology and target classes at hand. This information can also greatly reduce cost and time during HTS hit profiling. The present study exemplifies how to mine large HTS data repositories, such as the one at Boehringer Ingelheim, to identify frequent hitters, gain further insights into the causes of promiscuous behavior, and generate models for predicting promiscuous compounds. Applications of this approach are demonstrated using two recent large-scale HTS assays. The authors believe this analysis and its concrete applications are valuable tools for streamlining and accelerating decision-making processes during the course of hit discovery.     

Using clustering techniques to improve hit selection in high-throughput screening

A typical modern high-throughput screening (HTS) operation consists of testing thousands of chemical compounds to select active ones for future detailed examination. The authors describe 3 clustering techniques that can be used to improve the selection of active compounds (i.e., hits). They are designed to identify quality hits in the observed HTS measurements. The considered clustering techniques were first tested on simulated data and then applied to analyze the assay inhibiting Escherichia coli dihydrofo-late reductase produced at the HTS laboratory of McMaster University.     

The effect of triton concentration on the activity of undecaprenyl pyrophosphate synthase inhibitors

Undecaprenyl pyrophosphate synthase (UPPS) catalyzes the consecutive condensation of 8 molecules of isopentenyl pyrophosphate with farnesyl pyrophosphate to yield C55-undecaprenyl pyrophosphate, which is required for bacterial cell wall synthesis. UPPS is found in both gram-positive and gram-negative bacteria, and based on the differences between bacterial variants of UPPS and their human counterpart, dolicopyrophosphate synthase, it was identified as an attractive antibacterial target. An assay, which monitors the release of Pi by coupling the UPPS catalyzed reaction with inorganic pyrophosphatase, was employed to conduct an HTS campaign using an inhouse collection of compounds. A direct assay measuring the incorporation of 14C-IPP (isopentenyl pyrophosphate) was used as a secondary assay to evaluate the high-throughput screening (HTS) hits. From the HTS campaign, a few classes of UPPS inhibitors were identified. During the process of hit evaluation by the direct assay, the authors observed that Triton, an essential factor for the enzyme activity and accurate formation of the natural product, dramatically altered the inhibitory activity of a particular class of compounds. Above its critical micellar concentration (CMC), Triton abolished the inhibitory activity of these compounds. Further research will be required to establish the biophysical phenomenon that causes this effect. Meanwhile, it can be speculated that Triton (and other detergents) above CMC may hinder the identification in screening compounds of certain classes of hits.     

A Simple Statistical Parameter for Use in Evaluation and Validation of High Throughput Screening Assays

The ability to identify active compounds (3hits2) from large chemical libraries accurately and rapidly has been the ultimate goal in developing high-throughput screening (HTS) assays. The ability to identify hits from a particular HTS assay depends largely on the suitability or quality of the assay used in the screening. The criteria or parameters for evaluating the 3suitability2 of an HTS assay for hit identification are not well defined and hence it still remains difficult to compare the quality of assays directly. In this report, a screening window coefficient, called 3Z-factor,2 is defined. This coefficient is reflective of both the assay signal dynamic range and the data variation associated with the signal measurements, and therefore is suitable for assay quality assessment. The Z-factor is a dimensionless, simple statistical characteristic for each HTS assay. The Z-factor provides a useful tool for comparison and evaluation of the quality of assays, and can be utilized in assay optimization and validation.     

Identifying actives from HTS data sets: practical approaches for the selection of an appropriate HTS data-processing method and quality control review

High-throughput screening (HTS) has achieved a dominant role in drug discovery over the past 2 decades. The goal of HTS is to identify active compounds (hits) by screening large numbers of diverse chemical compounds against selected targets and/or cellular phenotypes. The HTS process consists of multiple automated steps involving compound handling, liquid transfers, and assay signal capture, all of which unavoidably contribute to systematic variation in the screening data. The challenge is to distinguish biologically active compounds from assay variability. Traditional plate controls-based and non-controls-based statistical methods have been widely used for HTS data processing and active identification by both the pharmaceutical industry and academic sectors. More recently, improved robust statistical methods have been introduced, reducing the impact of systematic row/column effects in HTS data. To apply such robust methods effectively and properly, we need to understand their necessity and functionality. Data from 6 HTS case histories are presented to illustrate that robust statistical methods may sometimes be misleading and can result in more, rather than less, false positives or false negatives. In practice, no single method is the best hit detection method for every HTS data set. However, to aid the selection of the most appropriate HTS data-processing and active identification methods, the authors developed a 3-step statistical decision methodology. Step 1 is to determine the most appropriate HTS data-processing method and establish criteria for quality control review and active identification from 3-day assay signal window and DMSO validation tests. Step 2 is to perform a multilevel statistical and graphical review of the screening data to exclude data that fall outside the quality control criteria. Step 3 is to apply the established active criterion to the quality-assured data to identify the active compounds.     

Development of a scintillation proximity binding assay for high-throughput screening of hematopoietic prostaglandin D2 synthase

Prostaglandin D₂ synthase (PGDS) catalyzes the isomerization of prostaglandin H₂ (PGH₂) to prostaglandin D₂ (PGD₂). PGD₂ produced by hematopoietic prostaglandin D₂ synthase (H-PGDS) in mast cells and Th2 cells is proposed to be a mediator of allergic and inflammatory responses. Consequently, inhibitors of H-PGDS represent potential therapeutic agents for the treatment of inflammatory diseases such as asthma. Due to the instability of the PGDS substrate PGH₂, an in-vitro enzymatic assay is not feasible for large-scale screening of H-PGDS inhibitors. Herein, we report the development of a competition binding assay amenable to high-throughput screening (HTS) in a scintillation proximity assay (SPA) format. This assay was used to screen an in-house compound library of approximately 280,000 compounds for novel H-PGDS inhibitors. The hit rate of the H-PGDS primary screen was found to be 4%. This high hit rate suggests that the active site of H-PGDS can accommodate a large diversity of chemical scaffolds. For hit prioritization, these initial hits were rescreened at a lower concentration in SPA and tested in the LAD2 cell assay. 116 compounds were active in both assays with IC₅₀s ranging from 6 to 807 nM in SPA and 82 nM to 10 μM in the LAD2 cell assay.     

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.     

High-throughput identification of inhibitors of human mitochondrial peptide deformylase

The human mitochondrial peptide deformylase (HsPDF) provides a potential new target for broadly acting antiproliferative agents. To identify novel nonpeptidomimetic and nonhydroxamic acid-based inhibitors of HsPDF, the authors have developed a high-throughput screening (HTS) strategy using a fluorescence polarization (FP)-based binding assay as the primary assay for screening chemical libraries, followed by an enzymatic-based assay to confirm hits, prior to characterization of their antiproliferative activity against established tumor cell lines. The authors present the results and performance of the established strategy tested in a pilot screen of 2880 compounds and the identification of the 1st inhibitors. Two common scaffolds were identified within the hits. Furthermore, cytotoxicity studies revealed that most of the confirmed hits have antiproliferative activity. These findings demonstrate that the designed strategy can identify novel functional inhibitors and provide a powerful alternative to the use of functional assays in HTS and support the hypothesis that HsPDF inhibitors may constitute a new class of antiproliferative agent.     

Evaluation of the InteraX system technology in a high-throughput screening environment

The authors have developed a cell-based high-throughput screening (HTS)-compatible assay to measure EGFR dimerization using the InteraX enzyme complementation technology of Applied Biosystems. The cells contain 2 chimeric proteins with complementing deletion mutants of the beta galactosidase enzyme, each fused to the extracellular and transmembrane part of EGFR. On binding of EGF, EGF receptor dimerizes and an active beta galactosidase is built. The authors used this homogeneous 384-well assay to screen about 20,000 diverse compounds. From 2 independent primary screen runs 239 hits were identified. For run 1, a mean S/B ratio of 4.26 and a mean Z' factor of 0.74 were obtained, for run 2 a mean S/B ratio of 3.88 and a mean Z' factor of 0.71 were obtained. After hit confirmation, repeated 4 times, 112 hits remained with a confirmation rate of 48.9%. Thirty of the 112 could be identified as cytotoxic. Fifty-one of the remaining 82 compounds could be shown to be inhibitors of the beta galactosidase enzyme itself. In summary, 31 compounds remained as potential EGFR dimerization or EGF stimulation inhibitors. The authors conclude that the InteraX system technology is HTS capable and can detect small molecule inhibitors capable of inhibiting protein-protein interactions.     

Label Free Fragment Screening Using Surface Plasmon Resonance as a Tool for Fragment Finding – Analyzing Parkin,a Difficult CNS Target

Surface Plasmon Resonance (SPR) is rarely used as a primary High-throughput Screening (HTS) tool in fragment-based approaches. With SPR instruments becoming increasingly high-throughput it is now possible to use SPR as a primary tool for fragment finding. SPR becomes, therefore, a valuable tool in the screening of difficult targets such as the ubiquitin E3 ligase Parkin. As a prerequisite for the screen, a large number of SPR tests were performed to characterize and validate the active form of Parkin. A set of compounds was designed and used to define optimal SPR assay conditions for this fragment screen. Using these conditions, more than 5000 pre-selected fragments from our in-house library were screened for binding to Parkin. Additionally, all fragments were simultaneously screened for binding to two off target proteins to exclude promiscuous binding compounds. A low hit rate was observed that is in line with hit rates usually obtained by other HTS screening assays. All hits were further tested in dose responses on the target protein by SPR for confirmation before channeling the hits into Nuclear Magnetic Resonance (NMR) and other hit-confirmation assays.     

Statistical analysis of systematic errors in high-throughput screening

High-throughput screening (HTS) is an efficient technology for drug discovery. It allows for screening of more than 100,000 compounds a day per screen and requires effective procedures for quality control. The authors have developed a method for evaluating a background surface of an HTS assay; it can be used to correct raw HTS data. This correction is necessary to take into account systematic errors that may affect the procedure of hit selection. The described method allows one to analyze experimental HTS data and determine trends and local fluctuations of the corresponding background surfaces. For an assay with a large number of plates, the deviations of the background surface from a plane are caused by systematic errors. Their influence can be minimized by the subtraction of the systematic background from the raw data. Two experimental HTS assays from the ChemBank database are examined in this article. The systematic error present in these data was estimated and removed from them. It enabled the authors to correct the hit selection procedure for both assays.     

Activity in vivo of anti-Trypanosoma cruzi compounds selected from a high throughput screening

Novel technologies that include recombinant pathogens and rapid detection methods are contributing to the development of drugs for neglected diseases. Recently, the results from the first high throughput screening (HTS) to test compounds for activity against Trypanosoma cruzi trypomastigote infection of host cells were reported. We have selected 23 compounds from the hits of this HTS, which were reported to have high anti-trypanosomal activity and low toxicity to host cells. These compounds were highly purified and their structures confirmed by HPLC/mass spectrometry. The compounds were tested in vitro, where about half of them confirmed the anti-T. cruzi activity reported in the HTS, with IC50 values lower than 5 μM. We have also adapted a rapid assay to test anti-T. cruzi compounds in vivo using mice infected with transgenic T. cruzi expressing luciferase as a model for acute infection. The compounds that were active in vitro were also tested in vivo using this assay, where we found two related compounds with a similar structure and low in vitro IC50 values (0.11 and 0.07 μM) that reduce T. cruzi infection in the mouse model more than 90% after five days of treatment. Our findings evidence the benefits of novel technologies, such as HTS, for the drug discovery pathway of neglected diseases, but also caution about the need to confirm the results in vitro. We also show how rapid methods of in vivo screening based in luciferase-expressing parasites can be very useful to prioritize compounds early in the chain of development.     

Multidimensional profiling of CSF1R screening hits and inhibitors: assessing cellular activity, target residence time, and selectivity in a higher throughput way

Over the past years, improvements in high-throughput screening (HTS) technology and compound libraries have resulted in a dramatic increase in the amounts of good-quality screening hits, and there is a growing need for follow-on hit profiling assays with medium throughput to further triage hits. Here the authors present such assays for the colony-stimulating factor 1 receptor (CSF1R, Fms), including tests for cellular activity and a homogeneous assay to measure affinity for inactive CSF1R. They also present a high-throughput assay to measure target residence time, which is based on competitive binding kinetics. To better fit k(off) rates, they present a modified mathematical model for competitive kinetics. In all assays, they profiled eight reference inhibitors (imatinib, sorafenib, sunitinib, tandutinib, dasatinib, GW2580, Ki20227, and J&J's pyrido[2,3-d]pyrimidin-5-one). Using the known biochemical selectivities of these inhibitors, which can be quantified using metrics such as the selectivity entropy, the authors have determined which assay readout best predicts hit selectivity. Their profiling shows surprisingly that imatinib has a preference for the active form of CSF1R and that Ki20227 has an unusually slow target dissociation rate. This confirms that follow-on hit profiling is essential to ensure that the best hits are selected for lead optimization.     

Identification of novel Kv1.3 blockers using a fluorescent cell-based ion channel assay

A functional cell-based assay was developed using a generic proprietary assay protocol, based on a membrane-potential sensitive dye, for the identification of small-molecule antagonists against the Kv1.3 potassium ion channel. A high-throughput screen (HTS) was subsequently performed with 20,000 compounds from the Evotec library, preselected using known small molecule antagonists for both sodium and potassium ion channels. Following data analysis, the hit rate was measured at 1.72%, and subsequent dose-response analysis of selected hits showed a high hit confirmation rate yielding approximately 50 compounds with an apparent IC50 value lower than 10 microM. Subsequent electrophysiological characterization of selected hits confirmed the initial activity and potency of the identified hits on the Kv1.3 target and also selectivity toward Kv1.3 through measurements on HERG as well as Kv1.3-expressing cell lines. Follow-up structure-activity relationship analysis revealed a variety of different clusters distributed throughout the library as well as several singlicates. In comparison to known Kv1.3 blockers, new chemical entities and scaffolds showing potency and selectivity against the Kv1.3 ion channel were detected. In addition, a screening strategy for ion channel drug discovery HTS, medicinal chemistry, and electrophysiology is presented.     

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.     

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.     

A new method with flexible and balanced control of false negatives and false positives for hit selection in RNA interference high-throughput screening assays

The z-score method and its variants for testing mean difference are commonly used for hit selection in high-throughput screening (HTS) assays. Strictly standardized mean difference (SSMD) offers a way to measure and classify the short interfering RNA (siRNA) effects. In this article, based on SSMD, the authors propose a new testing method for hit selection in RNA interference (RNAi) HTS assays. This SSMD-based method allows the differentiation between siRNAs with large and small effects on the assay output and maintains flexible and balanced control of both the false-negative rate, in which the siRNAs with strong effects are not selected as hits, and the restricted false-positive rate, in which the siRNAs with weak or no effects are selected as hits. This method directly addresses the size of siRNA effects represented by the strength of difference between an siRNA and a negative reference, whereas the classic z-score method and t-test of testing no mean difference address whether the mean of an siRNA is exactly the same as the mean of a negative reference. This method can readily control the false-negative rate, whereas it is nontrivial for the classic z-score method and t-test to control the false-negative rate. Therefore, theoretically, the SSMD-based method offers better control of the sizes of siRNA effects and the associated false-positive and false-negative rates than the commonly used z-score method and t-test for hit selection in HTS assays. The SSMD-based method should generally be applicable to any assay in which the end point is a difference in signal compared to a reference sample, including those for RNAi, receptor, enzyme, and cellular function.