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.     

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.     

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.     

Docking, virtual high throughput screening and in silico fragment-based drug design

The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more rapidly and at lower costs. In silico drug design consists of a collection of tools helping to make rational decisions at the different steps of the drug discovery process, such as the identification of a biomolecular target of therapeutical interest, the selection or the design of new lead compounds and their modification to obtain better affinities, as well as pharmacokinetic and pharmacodynamic properties. Among the different tools available, a particular emphasis is placed in this review on molecular docking, virtual high-throughput screening and fragment-based ligand design.     

High-throughput siRNA-based functional target validation

The drug discovery process pursued by major pharmaceutical companies for many years starts with target identification followed by high-throughput screening (HTS) with the goal of identifying lead compounds. To accomplish this goal, significant resources are invested into automation of the screening process or HTS. Robotic systems capable of handling thousands of data points per day are implemented across the pharmaceutical sector. Many of these systems are amenable to handling cell-based screening protocols as well. On the other hand, as companies strive to develop innovative products based on novel mechanisms of action(s), one of the current bottlenecks of the industry is the target validation process. Traditionally, bioinformatics and HTS groups operate separately at different stages of the drug discovery process. The authors describe the convergence and integration of HTS and bioinformatics to perform high-throughput target functional identification and validation. As an example of this approach, they initiated a project with a functional cell-based screen for a biological process of interest using libraries of small interfering RNA (siRNA) molecules. In this protocol, siRNAs function as potent gene-specific inhibitors. siRNA-mediated knockdown of the target genes is confirmed by TaqMan analysis, and genes with impacts on biological functions of interest are selected for further analysis. Once the genes are confirmed and further validated, they may be used for HTS to yield lead compounds.     

High-throughput assays for lipases and esterases

In the past few years a considerable number of high-throughput screening (HTS) systems have been developed, especially for lipases and esterases. In this review, a range of HTS methods for the directed evolution of these hydrolases are covered. This includes spectrophotometric and fluorimetric formats as well as other approaches to allow for fast, efficient and reliable identification of desired enzyme variants within large mutant libraries. In addition, methods for library creation and application of lipases and esterases are briefly covered.     

Assay concordance between SPA and TR-FRET in high-throughput screening

High-throughput screening (HTS) of large chemical libraries has become the main source of new lead compounds for drug development. Several specialized detection technologies have been developed to facilitate the cost- and time-efficient screening of millions of compounds. However, concerns have been raised, claiming that different HTS technologies may produce different hits, thus limiting trust in the reliability of HTS data. This study was aimed to investigate the reliability of the authors most frequently used assay techniques: scintillation proximity assay (SPA) and homogeneous time-resolved fluorescence resonance energy transfer (TR-FRET). To investigate the data concordance between these 2 detection technologies, the authors screened a large subset of the Schering compound library consisting of 300,000 compounds for inhibitors of a nonreceptor tyrosine kinase. They chose to set up this study in realistic HTS scale to ensure statistical significance of the results. The findings clearly demonstrate that the choice of detection technology has no significant impact on hit finding, provided that assays are biochemically equivalent. Data concordance is up to 90%. The little differences in hit findings are caused by threshold setting but not by systematic differences between the technologies. The most significant difference between the compared techniques is that in the SPA format, more false-positive primary hits were obtained.     

Virtual high throughput screening (vHTS) - A perspective

With the exponential rise in the number of viable novel drug targets, computational methods are being increasingly applied to accelerate the drug discovery process. Virtual High Throughput Screening (vHTS) is one such established methodology to identify drug candidates from large collection of compound libraries. Although it complements the expensive and time consuming High Throughput Screening (HTS) of compound libraries, vHTS possess inherent challenges. The successful vHTS requires the careful implementation of each phase of computational screening experiment right from target preparation to hit identification and lead optimization. This article discusses some of the important considerations that are imperative for designing a successful vHTS experiment.     

Case studies of minimizing nonspecific inhibitors in HTS campaigns that use assay-ready plates

Identifying chemical lead matter by high-throughput screening (HTS) has been a common practice in early stage drug discovery. Evolution of small-molecule library composition to include more drug-like molecules with desirable physical chemical properties combined with improving assay technologies has vastly enhanced the capability of HTS. However, HTS campaigns can still be plagued by false positives arising from nonspecific inhibitors. The generation of assay-ready plates has permitted an incremental advancement to the speed and efficiency of HTS but has the potential to enhance the occurrence of nonspecific inhibitors. A subtle change in the order of reagent addition to the assay-ready plates can greatly alleviate false-positive inhibition. Our case studies with six different kinase and protease targets reveal that this type of inhibition affects targets regardless of enzyme class and is unpredictable based on protein construct or inhibitor chemical scaffold. These case studies support a model where a diversity set of compounds should be tested first for hit rates as a function of order of addition, carrier protein, and relevant mechanistic studies prior to launch of the HTS campaign.     

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.     

Development and validation of a generic fluorescent methyltransferase activity assay based on the transcreener AMP/GMP assay

Methylation is a ubiquitous covalent modification used to control the function of diverse biomolecules including hormones, neurotransmitters, xenobiotics, proteins, nucleic acids, and lipids. Histone methyltransferases (HMTs) are currently of high interest as drug targets because of their role in epigenetic regulation; however, most HMT assay methods are either not amenable to a high-throughput screening (HTS) environment or are applicable to a limited number of enzymes. The authors developed a generic methyltransferase assay method using fluorescent immunodetection of adenosine monophosphate (AMP), which is formed from the MT reaction product S-adenosylhomocysteine in a dual-enzyme coupling step. The detection range of the assay; its suitability for HTS, including stability of reagents following dispensing and after addition to reactions; and the potential for interference from drug-like molecules was investigated. In addition, the use of the assay for measuring inhibitor potencies with peptide or intact protein substrates was examined through pilot screening with selected reference enzymes including HMT G9a. By combining a novel enzymatic coupling step with the well-characterized Transcreener AMP/GMP assay, the authors have developed a robust HTS assay for HMTs that should be broadly applicable to other types of methyltransferases as well.     

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.     

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.     

Systematic error detection in experimental high-throughput screening

Background  

High-throughput screening (HTS) is a key part of the drug discovery process during which thousands of chemical compounds are screened and their activity levels measured in order to identify potential drug candidates (i.e., hits). Many technical, procedural or environmental factors can cause systematic measurement error or inequalities in the conditions in which the measurements are taken. Such systematic error has the potential to critically affect the hit selection process. Several error correction methods and software have been developed to address this issue in the context of experimental HTS [1–7]. Despite their power to reduce the impact of systematic error when applied to error perturbed datasets, those methods also have one disadvantage - they introduce a bias when applied to data not containing any systematic error [6]. Hence, we need first to assess the presence of systematic error in a given HTS assay and then carry out systematic error correction method if and only if the presence of systematic error has been confirmed by statistical tests.     

Determining the optimal size of small molecule mixtures for high throughput NMR screening

High-throughput screening (HTS) using NMR spectroscopy has become a common component of the drug discovery effort and is widely used throughout the pharmaceutical industry. NMR provides additional information about the nature of small molecule-protein interactions compared to traditional HTS methods. In order to achieve comparable efficiency, small molecules are often screened as mixtures in NMR-based assays. Nevertheless, an analysis of the efficiency of mixtures and a corresponding determination of the optimum mixture size (OMS) that minimizes the amount of material and instrumentation time required for an NMR screen has been lacking. A model for calculating OMS based on the application of the hypergeometric distribution function to determine the probability of a hit for various mixture sizes and hit rates is presented. An alternative method for the deconvolution of large screening mixtures is also discussed. These methods have been applied in a high-throughput NMR screening assay using a small, directed library.     

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.     

Cell-Based Assays for High-Throughput Screening

Cell-based assays represent approximately half of all high-throughput screens currently performed. Here, we review in brief the history and status of high-throughput screening (HTS), and summarize some of the challenges and benefits associated with the use of cell-based assays in HTS. Approaches for successful experimental design and execution of cell-based screens are introduced, including strategies for assay development, implementation of primary and secondary screens, and target identification. In doing so, we hope to provide a comprehensive review of the cell-based HTS process and an introduction to the methodologies and techniques used.     

An efficient method for the detection and elimination of systematic error in high-throughput screening

MOTIVATION: High-throughput screening (HTS) is an early-stage process in drug discovery which allows thousands of chemical compounds to be tested in a single study. We report a method for correcting HTS data prior to the hit selection process (i.e. selection of active compounds). The proposed correction minimizes the impact of systematic errors which may affect the hit selection in HTS. The introduced method, called a well correction, proceeds by correcting the distribution of measurements within wells of a given HTS assay. We use simulated and experimental data to illustrate the advantages of the new method compared to other widely-used methods of data correction and hit selection in HTS. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.     

Development and validation of a high-throughput screen for inhibitors of SARS CoV and its application in screening of a 100,000-compound library

The authors have developed a high-throughput screen (HTS) that allows for the identification of potential inhibitors of the severe acute respiratory syndrome coronavirus (SARS CoV) from large compound libraries. The luminescent-based assay measures the inhibition of SARS CoV-induced cytopathic effect (CPE) in Vero E6 cells. The assay was validated in 96-well plates in a BSL3 containment facility. The assay is sensitive and robust, with Z values > 0.6, signal to background (S/B) > 16, and signal to noise (S/N) > 3. The assay was further validated with 2 different diversity sets of compounds against the SARS CoV. The "hit" rate for both libraries was approximately 0.01%. The validated HTS assay was then employed to screen a 100,000-compound library against SARS CoV. The hit rate for the library in a single-dose format was determined to be approximately 0.8%. Screening of the 3 libraries resulted in the identification of several novel compounds that effectively inhibited the CPE of SARS CoV in vitro-compounds which will serve as excellent lead candidates for further evaluation. At a 10-microM concentration, 3 compounds with selective indexes (SI50) of > 53 were discovered.