Discovery of novel class 1 phosphatidylinositide 3-kinases (PI3K) fragment inhibitors through structure-based virtual screening

The discovery of ligand efficient and lipophilicity efficient fragment inhibitors of class 1 phosphatidylinositide 3-kinases (PI3K) is reported. A fragment version of the AstraZeneca compound bank was docked to a homology model of the PI3K p110β isoform. Interaction-based scoring of the predicted binding poses served to further prioritise the virtual fragment hits. Experimental screening confirmed potency for a total of 18 fragment inhibitors, belonging to five different structural classes.     

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.     

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

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

Calculating the probability of detection for inhibitors in enzymatic or binding reactions in high-throughput screening

In high-throughput screening (HTS) for drug candidates from a library containing tens of thousands to millions of chemical compounds, one problem is assessing the sensitivity of an assay for detecting compounds with a particular potency. For example, when looking for inhibitors of an enzyme, what is the potency of an inhibitor that will be readily detected by an enzyme inhibition assay? Similarly, when assessing compounds that inhibit binding between receptors and ligands or similar molecule-to-molecule interactions, what potency of an inhibitor will be readily detected? In this article, the well-established concepts of Michaelis-Menten kinetics and Langmuir binding isotherms are combined with fundamental statistical principles to yield a measure of assay sensitivity. The approach is general and can be modified to accommodate situations where the reaction kinetics is known to be more complicated than situations described by the Michaelis-Menten and Langmuir equations. The calculations presented take into account the concentration of inhibitor used, the variability of the assay, the relationship between the K(m) or K(d) of the reaction and the substrate or ligand concentration used, the threshold or cutoff value used for determining "hits," and the number of replicates used in screening.     

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.     

A miniaturized high-throughput screening assay for fucosyltransferase VII

Fucosyltransferase VII (FucTVII) is a very promising drug target for treatment of inflammatory skin diseases. Its activity is required for synthesis of the sialyl-Lewis X glycoepitopes on the E- and P-selectin ligands, necessary for lymphocyte migration into the skin. High-throughput screening (HTS) of large chemical libraries has become the main source of novel chemical entities for the pharmaceutical industry. The screening of very large compound collections requires the use of specialized assay techniques that minimize time and costs. We describe the development of a miniaturized scintillation proximity assay for human FucTVII based on a oligosaccharide acceptor substrate that is identical to the glycosylation of the physiological substrate. In addition to assay development, the assay performance in a HTS campaign is shown. We screened 798,131 compounds from the Schering AG HTS library and identified 233 IC50 hits; 229 hits were FucTVII specific in so far as they did not inhibit either alpha-fucosidase or galactosyltransferase. In addition to screening a drug-like small-molecule collection, we worked on rational approaches to develop inhibitors or glycosidic decoys based on oligosaccharide-substrate analogues. The structure-activity relationship observed thereby is very narrow and shows strict requirements that are consistent with the described substrate specificity of FucTVII.     

Automated multiple ligand screening by frontal affinity chromatography-mass spectrometry (FAC-MS)

High-throughput screening (HTS) efforts to discover "hits" typically rely on the large-scale parallel screening of individual compounds with attempts to screen mixtures of compounds typically and, unfortunately, giving rise to false positives and false negatives due to the nature of the HTS readout (% inhibition/activation above a defined threshold) that makes deconvolution virtually intractable. Bioaffinity screening methods have emerged as an alternative or orthogonal method to classic HTS. One of these methods, frontal affinity chromatography coupled to mass spectrometry detection (FAC-MS), although still a relatively new technique, is turning out to be a viable screening tool. However, to push FAC-MS more to the forefront as a moderate primary HTS system (or a secondary screening assay), automation needs to be addressed. An automated FAC-MS system is described using 2 columns containing immobilized hERbeta, whereby while 1 column is being regenerated, the other is being used. The authors are extrapolating that in a continuous 24-h operation, the number of ligands screened could potentially approach 10,000. In addition, preliminary structure-activity relationship binding information (typically not seen in early primary HTS) can be obtained by observing the rank order of the library members in the various mixtures.     

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.     

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

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

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.     

High throughput screening for small molecule therapy for Gaucher disease using patient tissue as the source of mutant glucocerebrosidase

Gaucher disease (GD), the most common lysosomal storage disorder, results from the inherited deficiency of the lysosomal enzyme glucocerebrosidase (GCase). Previously, wildtype GCase was used for high throughput screening (HTS) of large collections of compounds to identify small molecule chaperones that could be developed as new therapies for GD. However, the compounds identified from HTS usually showed reduced potency later in confirmatory cell-based assays. An alternate strategy is to perform HTS on mutant enzyme to identify different lead compounds, including those enhancing mutant enzyme activities. We developed a new screening assay using enzyme extract prepared from the spleen of a patient with Gaucher disease with genotype N370S/N370S. In tissue extracts, GCase is in a more native physiological environment, and is present with the native activator saposin C and other potential cofactors. Using this assay, we screened a library of 250,000 compounds and identified novel modulators of mutant GCase including 14 new lead inhibitors and 30 lead activators. The activities of some of the primary hits were confirmed in subsequent cell-based assays using patient-derived fibroblasts. These results suggest that primary screening assays using enzyme extracted from tissues is an alternative approach to identify high quality, physiologically relevant lead compounds for drug development.     

Efficiency of hit generation and structural characterization in fragment-based ligand discovery

Fragment-based ligand discovery constitutes a useful strategy for the generation of high affinity ligands with suitable physico-chemical properties to serve as drug leads. There is an increasing number of generic biophysical screening strategies established with the potential for accelerating the generation of useful fragment hits. Crystal structures of these hits can subsequently be used as starting points for fragment evolution to high affinity ligands. Emerging understanding of the efficiency and operative aspects of hit generation and structural characterization in FBLD suggests that this method should be well suited for academic ligand development of chemical tools and experimental therapeutics.     

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.     

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.     

Fragment based discovery of a novel and selective PI3 kinase inhibitor

We report the use of fragment screening and fragment based drug design to develop a PI3γ kinase fragment hit into a lead. Initial fragment hits were discovered by high concentration biochemical screening, followed by a round of virtual screening to identify additional ligand efficient fragments. These were developed into potent and ligand efficient lead compounds using structure guided fragment growing and merging strategies. This led to a potent, selective, and cell permeable PI3γ kinase inhibitor with good metabolic stability that was useful as a preclinical tool compound.     

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.     

Whole organism high-content screening by label-free, image-based bayesian classification for parasitic diseases

Sole reliance on one drug, Praziquantel, for treatment and control of schistosomiasis raises concerns about development of widespread resistance, prompting renewed interest in the discovery of new anthelmintics. To discover new leads we designed an automated label-free, high content-based, high throughput screen (HTS) to assess drug-induced effects on in vitro cultured larvae (schistosomula) using bright-field imaging. Automatic image analysis and Bayesian prediction models define morphological damage, hit/non-hit prediction and larval phenotype characterization. Motility was also assessed from time-lapse images. In screening a 10,041 compound library the HTS correctly detected 99.8% of the hits scored visually. A proportion of these larval hits were also active in an adult worm ex-vivo screen and are the subject of ongoing studies. The method allows, for the first time, screening of large compound collections against schistosomes and the methods are adaptable to other whole organism and cell-based screening by morphology and motility phenotyping.     

Median absolute deviation to improve hit selection for genome-scale RNAi screens

High-throughput screening (HTS) of large-scale RNA interference (RNAi) libraries has become an increasingly popular method of functional genomics in recent years. Cell-based assays used for RNAi screening often produce small dynamic ranges and significant variability because of the combination of cellular heterogeneity, transfection efficiency, and the intrinsic nature of the genes being targeted. These properties make reliable hit selection in the RNAi screen a difficult task. The use of robust methods based on median and median absolute deviation (MAD) has been suggested to improve hit selection in such cases, but mean and standard deviation (SD)-based methods are still predominantly used in many RNAi HTS. In an experimental approach to compare these 2 methods, a genome-scale small interfering RNA (siRNA) screen was performed, in which the identification of novel targets increasing the therapeutic index of the chemotherapeutic agent mitomycin C (MMC) was sought. MAD values were resistant to the presence of outliers, and the hits selected by the MAD-based method included all the hits that would be selected by SD-based method as well as a significant number of additional hits. When retested in triplicate, a similar percentage of these siRNAs were shown to genuinely sensitize cells to MMC compared with the hits shared between SD- and MAD-based methods. Confirmed hits were enriched with the genes involved in the DNA damage response and cell cycle regulation, validating the overall hit selection strategy. Finally, computer simulations showed the superiority and generality of the MAD-based method in various RNAi HTS data models. In conclusion, the authors demonstrate that the MAD-based hit selection method rescued physiologically relevant false negatives that would have been missed in the SD-based method, and they believe it to be the desirable 1st-choice hit selection method for RNAi screen results.     

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

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

Abbott Physicochemical Tiering (APT)--a unified approach to HTS triage

The selection of the highest quality chemical matter from high throughput screening (HTS) is the ultimate aim of any triage process. Typically there are many hundreds or thousands of hits capable of modulating a given biological target in HTS with a wide range of physicochemical properties that should be taken into consideration during triage. Given the multitude of physicochemical properties that define drug-like space, a system needs to be in place that allows for a rapid selection of chemical matter based on a prioritized range of these properties. With this goal in mind, we have developed a tool, coined Abbott Physicochemical Tiering (APT) that enables hit prioritization based on ranges of these important physicochemical properties. This tool is now used routinely at Abbott to help prioritize hits out of HTS during the triage process. Herein we describe how this tool was developed and validated using Abbott internal high throughput ADME data (HT-ADME).