"Plate cherry picking": a novel semi-sequential screening paradigm for cheaper, faster, information-rich compound selection

This work describes a novel semi-sequential technique for in silico enhancement of high-throughput screening (HTS) experiments now employed at Novartis. It is used in situations in which the size of the screen is limited by the readout (e.g., high-content screens) or the amount of reagents or tools (proteins or cells) available. By performing computational chemical diversity selection on a per plate basis (instead of a per compound basis), 25% of the 1,000,000-compound screening was optimized for general initial HTS. Statistical models are then generated from target-specific primary results (percentage inhibition data) to drive the cherry picking and testing from the entire collection. Using retrospective analysis of 11 HTS campaigns, the authors show that this method would have captured on average two thirds of the active compounds (IC(50) < 10 microM) and three fourths of the active Murcko scaffolds while decreasing screening expenditure by nearly 75%. This result is true for a wide variety of targets, including G-protein-coupled receptors, chemokine receptors, kinases, metalloproteinases, pathway screens, and protein-protein interactions. Unlike time-consuming "classic" sequential approaches that require multiple iterations of cherry picking, testing, and building statistical models, here individual compounds are cherry picked just once, based directly on primary screening data. Strikingly, the authors demonstrate that models built from primary data are as robust as models built from IC(50) data. This is true for all HTS campaigns analyzed, which represent a wide variety of target classes and assay types.     

High throughput screening of potentially selective MMP-13 exosite inhibitors utilizing a triple-helical FRET substrate

The major components of the cartilage extracellular matrix are type II collagen and aggrecan. Matrix metalloproteinase 13 (MMP-13) has been implicated as the protease responsible for collagen degradation in cartilage during osteoarthritis (OA). In the present study, a triple-helical FRET substrate has been utilized for high throughput screening (HTS) of MMP-13 with the MLSCN compound library (n approximately 65,000). Thirty-four compounds from the HTS produced pharmacological dose-response curves. A secondary screen using RP-HPLC validated 25 compounds as MMP-13 inhibitors. Twelve of these compounds were selected for counter-screening with 6 representative MMP family members. Five compounds were found to be broad-spectrum MMP inhibitors, 3 inhibited MMP-13 and one other MMP, and 4 were selective for MMP-13. One of the selective inhibitors was more active against MMP-13 triple-helical peptidase activity compared with single-stranded peptidase activity. Since the THP FRET substrate has distinct conformational features that may interact with MMP secondary binding sites (exosites), novel non-active site-binding inhibitors may be identified via HTS protocols utilizing such assays.     

Discovery of novel benzoquinazolinones and thiazoloimidazoles, inhibitors of influenza H5N1 and H1N1 viruses, from a cell-based high-throughput screen

A highly reproducible and robust cell-based high-throughput screening (HTS) assay was adapted for screening of small molecules for antiviral activity against influenza virus strain A/Vietnam/1203/2004 (H5N1). The NIH Molecular Libraries Small Molecule Repository (MLSMR) Molecular Libraries Screening Centers Network (MLSCN) 100,000-compound library was screened at 50 μM. The "hit" rate (>25% inhibition of the viral cytopathic effect) from the single-dose screen was 0.32%. The hits were evaluated for their antiviral activity, cell toxicity, and selectivity in dose-response experiments. The screen yielded 5 active compounds (SI value >3). One compound showed an SI(50) value of greater than 3, 3 compounds had SI values ranging from greater than 14 to 34, and the most active compound displayed an SI value of 94. The active compounds represent 2 different classes of molecules, benzoquinazolinones and thiazoloimidazoles, which have not been previously identified as having antiviral/anti-influenza activity. These molecules were also effective against influenza A/California/04/2009 virus (H1N1) and other H1N1 and H5N1 virus strains in vitro but not H3N2 strains. Real-time qRT-PCR results reveal that these chemotypes significantly reduced M1 RNA levels as compared to the no-drug influenza-infected Madin Darby canine kidney cells.     

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.     

High-throughput screening of a 100,000-compound library for inhibitors of influenza A virus (H3N2)

Using a highly reproducible and robust cell-based high-throughput screening (HTS) assay, the authors screened a 100,000-compound library at 14- and 114-microM compound concentration against influenza strain A/Udorn/72 (H3N2). The "hit" rates (>50% inhibition of the viral cytopathic effect) from the 14- and 114-microM screens were 0.022% and 0.38%, respectively. The hits were evaluated for their antiviral activity, cell toxicity, and selectivity in dose-response experiments. The screen at the lower concentration yielded 3 compounds, which displayed moderate activity (SI(50) = 10-49). Intriguingly, the screen at the higher concentration revealed several additional hits. Two of these hits were highly active with an SI(50) > 50. Time of addition experiments revealed 1 compound that inhibited early and 4 other compounds that inhibited late in the virus life cycle, suggesting they affect entry and replication, respectively. The active compounds represent several different classes of molecules such as carboxanilides, 1-benzoyl-3-arylthioureas, sulfonamides, and benzothiazinones, which have not been previously identified as having antiviral/anti-influenza activity.     

Fragment screening: an introduction

There are clearly many different philosophies associated with adapting fragment screening into mainstream Drug Discovery Lead Generation strategies. Scientists at Astex, for instance, focus entirely on strategies involving use of X-ray crystallography and NMR. However, AstraZeneca uses a number of different fragment screening strategies. One approach is to screen a 2000 compound fragment set (with close to "lead-like" complexity) at 100 microM in parallel with every HTS such that the data are obtained on the entire screening collection at 10 microM plus the extra samples at 100 microM; this provides valuable compound potency data in a concentration range that is usually unexplored. The fragments are then screen-specific "privileged structures" that can be searched for in the rest of the HTS output and other databases as well as having synthesis follow-up. A typical workflow for a fragment screen within AstraZeneca is shown below (Figure 24) and highlights the desirability (particularly when screening >100 microM) for NMR and X-ray information to validate weak hits and give information on how to optimise them. In this chapter, we have provided an introduction to the theoretical and practical issues associated with the use of fragment methods and lead-likeness. Fragment-based approaches are still in an early stage of development and are just one of many interrelated techniques that are now used to identify novel lead compounds for drug development. Fragment based screening has some advantages, but like every other drug hunting strategy will not be universally applicable. There are in particular some practical challenges associated with fragment screening that relate to the generally lower level of potency that such compounds initially possess. Considerable synthetic effort has to be applied for post-fragment screening to build the sort of potency that would be expected to be found from a traditional HTS. However, if there are no low-hanging fruit in a screening collection to be found by HTS then the use of fragment screening can help find novelty that may lead to a target not being discarded as intractable. As such, the approach offers some significant advantages by providing less complex molecules, which may have better potential for novel drug optimisation and by enabling new chemical space to be more effectively explored. Many literature examples that cover examples of fragment screening approaches are still at the "proof of concept" stage and although delivering inhibitors or ligands, may still prove to be unsuitable when further ADMET and toxicity profiling is done. The next few years should see a maturing of the area, and as our understanding of how the concepts can be best applied, there are likely to be many more examples of attractive, small molecule hits, leads and candidate drugs derived from the approaches described.     

High-throughput screening of RNA polymerase inhibitors using a fluorescent UTP analog

RNA polymerase (RNAP) is a well-validated target for the development of antibacterial and antituberculosis agents. Because the purification of large quantities of native RNA polymerase from pathogenic mycobacteria is hazardous and cumbersome, the primary screening was carried out using Escherichia coli RNAP. The authors have developed a high-throughput screening (HTS) assay to screen for novel inhibitors of RNAP. In this assay, a fluorescent analog of UTP, gamma-amino naphthalene sulfonic acid (gamma-AmNS) UTP, was used as one of the nucleotide substrates. Incorporation of UMP in RNA results in the release of gamma-AmNS-PPi, which has higher intrinsic fluorescence than (gamma-AmNS) UTP. The assay was optimized in a 384-well format and used to screen 670,000 compounds at a concentration of 10 microM. About 0.1% of the compounds showed more than 60% inhibition in the primary HTS. All the primary actives tested for dose response using the same assay had an EC(50) below 100 microM. Eighty percent of the primary HTS actives obtained using E. coli RNAP showed comparable activity against Mycobacterium smegmatis RNAP in the conventional radioactive assay. Activity of hits selected for the hit-to-lead optimization was also confirmed against Mycobacterium bovis RNAP which has >99% sequence identity with Mycobacterium tuberculosis RNAP subunits.     

Use of mixture distributions to deconvolute the behavior of "hits" and controls in high-throughput screening data

The stochastic nature of high-throughput screening (HTS) data indicates that information may be gleaned by applying statistical methods to HTS data. A foundation of parametric statistics is the study and elucidation of population distributions, which can be modeled using modern spreadsheet software. The methods and results described here use fundamental concepts of statistical population distributions analyzed using a spreadsheet to provide tools in a developing armamentarium for extracting information from HTS data. Specific examples using two HTS kinase assays are analyzed. The analyses use normal and gamma distributions, which combine to form mixture distributions. HTS data were found to be described well using such mixture distributions, and deconvolution of the mixtures to the constituent gamma and normal parts provided insight into how the assays performed. In particular, the proportion of hits confirmed was predicted from the original HTS data and used to assess screening assay performance. The analyses also provide a method for determining how hit thresholds--values used to separate active from inactive compounds--affect the proportion of compounds verified as active and how the threshold can be chosen to optimize the selection process.     

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.     

A new approach to drug discovery: high-throughput screening of microbial natural extracts against Aspergillus fumigatus using resazurin

Natural products are an inexhaustible source for drug discovery. However, the validation and selection of primary screening assays are vital to guarantee a selection of extracts or molecules with relevant pharmacological action and worthy of following up. The assay must be rapid, simple, easy to implement, and produce quick results and preferably at a low cost. In this work, we developed and validated a colorimetric microtiter assay using the resazurin viability dye. The parameters of the resazurin method for high-throughput screening (HTS) using natural extracts against Aspergillus fumigatus were optimized and set up. The extracts plus RPMI-1640 modified medium containing the spores and 0.002% resazurin were added per well. The fluorescence was read after 24 to 30 h of incubation. The resazurin proved to be as suitable as Alamar Blue for determining the minimal inhibitory concentration of different antifungals against A. fumigatus and effective to analyze fungicidal and fungistatic compounds. An HTS of 12 000 microbial extracts was carried out against two A. fumigatus strains, and 2.7% of the extracts displayed antifungal activity. Our group has been the first to use this methodology for screening a collection of natural extracts to identify compounds with antifungal activity against the medically important human pathogen A. fumigatus.     

Identification of novel drug scaffolds for inhibition of SARS-CoV 3-Chymotrypsin-like protease using virtual and high-throughput screenings

We have used a combination of virtual screening (VS) and high-throughput screening (HTS) techniques to identify novel, non-peptidic small molecule inhibitors against human SARS-CoV 3CLpro. A structure-based VS approach integrating docking and pharmacophore based methods was employed to computationally screen 621,000 compounds from the ZINC library. The screening protocol was validated using known 3CLpro inhibitors and was optimized for speed, improved selectivity, and for accommodating receptor flexibility. Subsequently, a fluorescence-based enzymatic HTS assay was developed and optimized to experimentally screen approximately 41,000 compounds from four structurally diverse libraries chosen mainly based on the VS results. False positives from initial HTS hits were eliminated by a secondary orthogonal binding analysis using surface plasmon resonance (SPR). The campaign identified a reversible small molecule inhibitor exhibiting mixed-type inhibition with a K_i value of 11.1 μM. Together, these results validate our protocols as suitable approaches to screen virtual and chemical libraries, and the newly identified compound reported in our study represents a promising structural scaffold to pursue for further SARS-CoV 3CLpro inhibitor development.     

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.     

High-throughput screening of a diversity collection using biodefense category a and B priority pathogens

One of the objectives of the National Institutes of Allergy and Infectious Diseases (NIAID) Biodefense Program is to identify or develop broad-spectrum antimicrobials for use against bioterrorism pathogens and emerging infectious agents. As a part of that program, our institution has screened the 10 000-compound MyriaScreen Diversity Collection of high-purity druglike compounds against three NIAID category A and one category B priority pathogens in an effort to identify potential compound classes for further drug development. The effective use of a Clinical and Laboratory Standards Institute-based high-throughput screening (HTS) 96-well-based format allowed for the identification of 49 compounds that had in vitro activity against all four pathogens with minimum inhibitory concentration values of ≤16 μg/mL. Adaptation of the HTS process was necessary to conduct the work in higher-level containment, in this case, biosafety level 3. Examination of chemical scaffolds shared by some of the 49 compounds and assessment of available chemical databases indicates that several may represent broad-spectrum antimicrobials whose activity is based on novel mechanisms of action.     

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.     

Support vector machines in HTS data mining: Type I MetAPs inhibition study

This article reports a successful application of support vector machines (SVMs) in mining high-throughput screening (HTS) data of a type I methionine aminopeptidases (MetAPs) inhibition study. A library with 43,736 small organic molecules was used in the study, and 1355 compounds in the library with 40% or higher inhibition activity were considered as active. The data set was randomly split into a training set and a test set (3:1 ratio). The authors were able to rank compounds in the test set using their decision values predicted by SVM models that were built on the training set. They defined a novel score PT50, the percentage of the test set needed to be screened to recover 50% of the actives, to measure the performance of the models. With carefully selected parameters, SVM models increased the hit rates significantly, and 50% of the active compounds could be recovered by screening just 7% of the test set. The authors found that the size of the training set played a significant role in the performance of the models. A training set with 10,000 member compounds is likely the minimum size required to build a model with reasonable predictive power.     

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 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.     

High throughput screening identifies novel inhibitors of Escherichia coli dihydrofolate reductase that are competitive with dihydrofolate

This communication describes the high-throughput screen of a diverse library of 50,000 small molecules against Escherichia coli dihydrofolate reductase to detect inhibitors. Sixty-two compounds were identified as having significant inhibitory activity against the enzyme. Secondary screening of these revealed twelve molecules that were competitive with dihydrofolate, nine of which have not been previously characterized as inhibitors of dihydrofolate reductase. These novel molecules ranged in potency (K(i)) from 26 nM to 11 microM and may represent fresh starting points for new small molecule therapeutics directed against dihydrofolate reductase.     

Stacker Modules Used in a High-Capacity Robotics System for High Throughput Screening Compound Replication

High throughput screening is now established as a key component of the pharmaceutical lead identification process in many pharmaceutical companies. Over recent years, thanks to advances in assay technology, process automation, and logistics control, the throughput capacity of HTS groups has increased significantly. It is now entirely possible to screen corporate compound collections against an individual pharmacological target within a timescale of several weeks. Despite these improvements, many HTS groups find that their capacity is limited by the rate at which they can provide test compounds in a "screen-ready" format. This limitation is usually imposed by the capacity and productivity of the single-armed robotic systems utilized. We have recently constructed a robotic system aimed at overcoming this particular problem. This system uses purpose-built microplate stacker units that provide high-capacity microplate storage and, importantly, provide an easy and fast interface between the robotic system and the human operators. This paper describes this automation project and the benefits that have resulted from its deployment.