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PubMed2006

Discovery of 2-iminobenzimidazoles as a new class of trypanothione reductase inhibitor by high-throughput screening.

A high-throughput screening campaign of a library of 100,000 lead-like compounds identified 2-iminobenzimidazoles as a novel class of trypanothione reductase inhibitors. These 2-iminobenzimidazoles display potent trypanocidal activity against Trypanosoma brucei rhodesiense, do not inhibit closely related human glutathione reductase and have low cytotoxicity against mammalian cells.

Animals↗
PubMedDate not supplied

Learning from the data: mining of large high-throughput screening databases.

High-throughput screening (HTS) campaigns in pharmaceutical companies have accumulated a large amount of data for several million compounds over a couple of hundred assays. Despite the general awareness that rich information is hidden inside the vast amount of data, little has been reported for a systematic data mining method that can reliably extract relevant knowledge of interest for chemists and biologists. We developed a data mining approach based on an algorithm called ontology-based pattern identification (OPI) and applied it to our in-house HTS database. We identified nearly 1500 scaffold families with statistically significant structure-HTS activity profile relationships. Among them, dozens of scaffolds were characterized as leading to artifactual results stemming from the screening technology employed, such as assay format and/or readout. Four types of compound scaffolds can be characterized based on this data mining effort: tumor cytotoxic, general toxic, potential reporter gene assay artifact, and target family specific. The OPI-based data mining approach can reliably identify compounds that are not only structurally similar but also share statistically significant biological activity profiles. Statistical tests such as Kruskal-Wallis test and analysis of variance (ANOVA) can then be applied to the discovered scaffolds for effective assignment of relevant biological information. The scaffolds identified by our HTS data mining efforts are an invaluable resource for designing SAR-robust diversity libraries, generating in silico biological annotations of compounds on a scaffold basis, and providing novel target family specific scaffolds for focused compound library design.

Algorithms↗
PubMed2003

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.

Computer Graphics↗
PubMed2005

Evaluating real-life high-throughput screening data.

High-throughput screening (HTS) is the result of a concerted effort of chemistry, biology, information technology, and engineering. Many factors beyond the biology of the assay influence the quality and outcome of the screening process, yet data analysis and quality control are often focused on the analysis of a limited set of control wells and the calculated values derived from these wells. Taking into account the large number of variables and the amount of data generated, multiple views of the screening data are necessary to guarantee quality and validity of HTS results. This article does not aim to give an exhaustive outlook on HTS data analysis but tries to illustrate the shortfalls of a reductionist approach focused on control wells and give examples for further analysis.

Biological Assay↗
PubMed2005

Development of a new high-throughput screening model for human high density lipoprotein receptor (CLA-1) agonists.

OBJECTIVE: To develop a new high-throughput screening model for human high-density lipoprotein (HDL) receptor (CD36 and LIMPII analogous-1, CLA-1) agonists using CLA-1-expressing insect cells. METHODS: With the total RNA of human hepatoma cells BEL-7402 as template, the complementary DNA (cDNA) of CLA-1 was amplified by reverse transcription-polymerase chain reaction (RT-PCR). Bac-to-Bac baculovirus expression system was used to express CLA-1 in insect cells. CLA-1 cDNA was cloned downstream of polyhedrin promoter of Autographa californica nuclear polyhedrosis virus (AcNPV) into donor vector pFastBac1 and recombinant pFastBac1-CLA-1 was transformed into E. coli DH10Bac to transpose CLA-1 cDNA to bacmid DNA. Recombinant bacmid-CLA-1 was transfected into Spodoptera frugiperda Sf9 insect cells to produce recombinant baculovirus particles. Recombinant CLA-1 was expressed on the membrane of Sf9 cells infected with the recombinant baculoviruses. A series of parameters of DiI-lipoprotein binding assays of CLA-1-expressing Sf9 cells in 96-well plates were optimized. RESULTS: Western blot analysis and DiI-lipoprotein binding assays confirmed that CLA-1 expressed in insect cells had similar immunoreactivity and ligand binding activity as its native counterpart. A reliable and sensitive in vitro cell-based assay was established to assess the activity of CLA-1 and used to screen agonists from different sample libraries. CONCLUSION: Human HDL receptor CLA-1 was successfully expressed in Sf9 insect cells and a novel high-throughput screening model for CLA-1 agonists was developed. Utilization of this model allows us to identify potent and selective CLA-1 agonists which might possibly be used as therapeutics for atherosclerosis.

Animals↗
PubMed1999

Natural Products in High Throughput Screening: Automated High-Quality Sample Preparation.

At present, compound libraries from combinatorial chemistry are the major source for high throughput screening (HTS) programs in drug discovery. On the other hand, nature has been proven to be an outstanding source for new and innovative drugs. Secondary metabolites from plants, animals, and microorganisms show a striking structural diversity that supplements chemically synthesized compounds or libraries in drug discovery programs. Unfortunately, extracts from natural sources are usually complex mixtures of compounds, often generated in time-consuming and, for the most part, manual processes. Because quality and quantity of the provided samples play a pivotal role in the success of HTS programs, this poses serious problems. In order to make samples of natural origin competitive with synthetic compound libraries, we devised a novel, automated sample preparation procedure based on solid-phase extraction (SPE). By making use of modified Zymark (Hopkinton, MA) RapidTrace® SPE workstations, we developed an easy-to-handle and effective fractionation method that generates high-quality samples from natural origin, fulfilling the requirements for an integration in high throughput drug discovery programs.

Journal Article↗
PubMed2005

Production and characterization of mouse ureteric bud cell-specific rat hybridoma antibodies utilizing subtractive immunization and high-throughput screening.

The highly branched collecting system of the kidney arises developmentally from the ureteric bud (UB) by a process of branching morphogenesis. This process is critical for the normal development of the collecting ducts and pelvis of the kidney, and is tightly controlled by the spatial and temporal expression of numerous proteins. To identify cell proteins that are differentially expressed by the UB relative to those expressed by the highly differentiated collecting ducts of the adult kidney, two mouse cell populations derived from either the early UB or the adult inner medullary collecting duct (IMCD) were used. A subtractive immunization strategy was performed in rats to generate monoclonal antibodies that preferentially reacted with antigens on UB, but not IMCD cells. In addition, the technique of antibody printing, a novel high-throughput antibody screening method for determining the specificities of a large number of monoclonal antibodies, is described. The methodologies outlined in this manuscript have broad applicability as they demonstrate that subtractive immunization can be performed in rats with cells derived from mice. Additionally, the high-throughput screening methods should facilitate the use of subtractive immunization for identifying antibodies that can distinguish differences in proteins expressed in closely related cell types.

Animals↗
PubMed1998

New assay technologies for high-throughput screening.

The use of high-throughput screening for early stage drug discovery imposes several constraints on the format of assays for therapeutic targets of interest. Homogeneous cell-free assays based on energy transfer, fluorescence polarization spectroscopy or fluorescence correlation spectroscopy provide the sensitivity, ease, speed and resistance to interference from test compounds needed to function in a high-throughput screening mode. Similarly, novel cell-based assays are now being adapted for high-throughput screening, providing for in situ analysis of a variety of biological targets. Finally, recent advances in assay miniaturization mark a transition to ultra high-throughput screening, ensuring that identification of lead compounds will not be the rate-limiting step in finding new drugs.

Animals↗
PubMedDate not supplied

The reduced graph descriptor in virtual screening and data-driven clustering of high-throughput screening data.

Virtual screening and high-throughput screening are two major components of lead discovery within the pharmaceutical industry. In this paper we describe improvements to previously published methods for similarity searching with reduced graphs, with a particular focus on ligand-based virtual screening, and describe a novel use of reduced graphs in the clustering of high-throughput screening data. Literature methods for reduced graph similarity searching encode the reduced graphs as binary fingerprints, which has a number of issues. In this paper we extend the definition of the reduced graph to include positively and negatively ionizable groups and introduce a new method for measuring the similarity of reduced graphs based on a weighted edit distance. Moving beyond simple similarity searching, we show how more flexible queries can be built using reduced graphs and describe a database system that allows iterative querying with multiple representations. Reduced graphs capture many important features of ligand-receptor interactions and, in conjunction with other whole molecule descriptors, provide an informative way to review HTS data. We describe a novel use of reduced graphs in this context, introducing a method we have termed data-driven clustering, that identifies clusters of molecules represented by a particular whole molecule descriptor and enriched in active compounds.

Journal Article↗
PubMed2005

Nanoliter homogenous ultra-high throughput screening microarray for lead discoveries and IC50 profiling.

Microfluidic technologies offer the potential for highly productive and low-cost ultra-high throughput screening and high throughput selectivity profiling. Such technologies need to provide the flexibility of plate-based assays as well as be less expensive to operate. Presented here is a unique microarray system (the Reaction Biology [Malvern, PA] DiscoveryDot), which runs over 6,000 homogeneous reactions per 1" x 3" microarray using chemical libraries or compound dilutions printed in 1-nl volumes. A simple and rapid piezo-activation method delivers from 30 to 300 pl of biochemical targets and detector chemistries to each reaction. The fluorescent signals are detected and analyzed with conventional microarray scanners and software. The DiscoveryDot platform is highly customizable, and reduces consumption of targets and reaction chemistries by >40-fold and the consumption of compounds by >10,000-fold, compared to 384-well plate assay. We demonstrate here that the DiscoveryDot platform is compatible with conventional large-volume well-based reactions, with a Z' factor of >0.6 for many enzymes, such as the caspase family enzymes, matrix metalloproteinase, serine proteases, kinases, and histone deacetylases. The platform is well equipped for 50% inhibitory concentration (IC50) profiling studies of enzyme inhibitors, with up to 10 dilution conditions of each test compound printed in duplicate, and each microarray chip can generate over 300 IC50 measurements against a given target.

Drug Design↗
PubMed2006

Statistical practice in high-throughput screening data analysis.

High-throughput screening is an early critical step in drug discovery. Its aim is to screen a large number of diverse chemical compounds to identify candidate 'hits' rapidly and accurately. Few statistical tools are currently available, however, to detect quality hits with a high degree of confidence. We examine statistical aspects of data preprocessing and hit identification for primary screens. We focus on concerns related to positional effects of wells within plates, choice of hit threshold and the importance of minimizing false-positive and false-negative rates. We argue that replicate measurements are needed to verify assumptions of current methods and to suggest data analysis strategies when assumptions are not met. The integration of replicates with robust statistical methods in primary screens will facilitate the discovery of reliable hits, ultimately improving the sensitivity and specificity of the screening process.

Biological Assay↗
PubMed2006

HTS-Corrector: software for the statistical analysis and correction of experimental high-throughput screening data.

MOTIVATION: High-throughput screening (HTS) plays a central role in modern drug discovery, allowing for testing of >100,000 compounds per screen. The aim of our work was to develop and implement methods for minimizing the impact of systematic error in the analysis of HTS data. To the best of our knowledge, two new data correction methods included in HTS-Corrector are not available in any existing commercial software or freeware. RESULTS: This paper describes HTS-Corrector, a software application for the analysis of HTS data, detection and visualization of systematic error, and corresponding correction of HTS signals. Three new methods for the statistical analysis and correction of raw HTS data are included in HTS-Corrector: background evaluation, well correction and hit-sigma distribution procedures intended to minimize the impact of systematic errors. We discuss the main features of HTS-Corrector and demonstrate the benefits of the algorithms.

Algorithms↗
PubMed2003

Emerging trends in high-throughput screening.

Novel technologies are emerging for high-throughput screening, driven by the needs and fine-tuning of established drug discovery activities, as well as by the emergence of novel target classes resulting from the deciphering of the human genome. Disciplines other than biology have now entered the screening scene, as bioinformatics, micro-technology and analytics provide powerful methodologies and applications that were not previously suitable for high-throughput screening. Many of these will move high-throughput screening from a numbers game to a content- and information-based approach to identify leads for novel disease targets.

Combinatorial Chemistry Techniques↗
PubMed2004

Deriving knowledge through data mining high-throughput screening data.

Deriving general knowledge from high-throughput screening data is made difficult by the significant amount of noise, arising primarily from false positives, in the data. The paradigm established for screening an encoded combinatorial library on polymeric support, an ECLiPS library, has a significant amount of built-in redundancy. Because of this redundancy, the resulting data can be interpreted through a rigorous statistical analysis procedure, thereby significantly reducing the number of false positives. Here, we develop the statistical models used to analyze data from high-throughput screens of ECLiPS libraries to derive unbiased true hit rates. These hit rates can also be calculated on subsets of the collection such as those compounds containing a carboxylic acid or those with molecular weight below 350 Da. The relative value of the hit rate on the subset of the collection can then be compared to the overall hit rate to determine the effect of the substructure or physical property on the likelihood of a molecule having biological activity. Here, we show the effects that various functional groups and the standard physical properties, molecular weight, hydrogen bond donors, hydrogen bond acceptors, log P, and rotatable bonds, have on the likelihood of a compound being biologically active. To our knowledge this is the first published account of the use of high-throughput screening data to elucidate the effects of physical properties and substructures on the likelihood of compounds showing biological activity over a broad range of pharmaceutically relevant targets.

Algorithms↗
PubMed2007

Alternative statistical parameter for high-throughput screening assay quality assessment.

High-throughput screening is an essential process in drug discovery. The ability to identify true active compounds depends on the high quality of assays and proper analysis of data. The Z factor, presented by Zhang et al. in 1999, provides an easy and useful summary of assay quality and has been a widely accepted standard. However, as data analysis has undergone much improvement recently, the assessment of assay quality has not evolved in parallel. In this article, the authors study the implications of Z factor values under different conditions and link the Z factor with the power of discovering true active compounds. They discuss the different interpretations of Z factor depending on error distributions and advocate direct analysis of power as assay quality assessment. They also propose that in estimating assay quality parameters, adjustments in data analysis should be taken into account. Studying the power of identifying true "hits" gives a more direct interpretation of assay quality and may provide guidance in assay optimization on some occasions.

Chemistry, Pharmaceutical↗
PubMed2002

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.

Biological Assay↗
PubMed2006

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.

Cluster Analysis↗
PubMed2002

Finding the needle in the haystack: why high-throughput screening is good for your health.

High-throughput screening is an essential component of the toolbox of modern technologies that improve speed and efficiency in contemporary cancer drug development. This is particularly important as we seek to exploit, for maximum therapeutic benefit, the large number of new molecular targets emerging from the Human Genome Project and cancer genomics. Screening of diverse collections of low molecular weight compounds plays a key role in providing chemical starting points for iterative optimisation by medicinal chemistry. Examples of successful drug discovery programmes based on high-throughput screening are described, and these offer potential in the treatment of breast cancer and other malignancies.

Antineoplastic Agents↗