Retroviral display and high throughput screening

Retroviruses distinguish themselves from all other mammalian viruses by their abilities to infect and propagate in mammalian cells without causing a cytopathic effect and to stably integrate their genetic information into the genome of the host cell. These unique properties make them an ideal platform for the display and directed evolution of proteins in a mammalian cell environment. This review will describe the essentials about retrovirus biology and then discuss in detail display and screening strategies that have been developed during the past 15 years of retroviral display technology.     

Predictive models for cytochrome p450 isozymes based on quantitative high throughput screening data

The human cytochrome P450 (CYP450) isozymes are the most important enzymes in the body to metabolize many endogenous and exogenous substances including environmental toxins and therapeutic drugs. Any unnecessary interactions between a small molecule and CYP450 isozymes may raise a potential to disarm the integrity of the protection. Accurately predicting the potential interactions between a small molecule and CYP450 isozymes is highly desirable for assessing the metabolic stability and toxicity of the molecule. The National Institutes of Health Chemical Genomics Center (NCGC) has screened a collection of over 17,000 compounds against the five major isozymes of CYP450 (1A2, 2C9, 2C19, 2D6, and 3A4) in a quantitative high throughput screening (qHTS) format. In this study, we developed support vector classification (SVC) models for these five isozymes using a set of customized generic atom types. The CYP450 data sets were randomly split into equal-sized training and test sets. The optimized SVC models exhibited high predictive power against the test sets for all five CYP450 isozymes with accuracies of 0.93, 0.89, 0.89, 0.85, and 0.87 for 1A2, 2C9, 2C19, 2D6, and 3A4, respectively, as measured by the area under the receiver operating characteristic (ROC) curves. The important atom types and features extracted from the five models are consistent with the structural preferences for different CYP450 substrates reported in the literature. We also identified novel features with significant discerning power to separate CYP450 actives from inactives. These models can be useful in prioritizing compounds in a drug discovery pipeline or recognizing the toxic potential of environmental chemicals.     

Gene expression analysis for high throughput screening applications

To meet growing needs for high throughput gene expression profiling, we established a new automated high throughput TaqMan RT-PCR method for quantitative mRNA expression analysis. In this method, the Allegro( trade mark ) (Zymark) system conducts all sample tracking and liquid handling steps, and ABI PRISM 7900 HT (Applied Biosystems) is used to conduct real-time determination of the C(t) value when amplification of PCR products is first detected and accumulation of inhibitory PCR products is unlikely to occur. The ABI PRISM 7900 HT Sequence Detection System features a real-time PCR instrument with 384-well-plate compatibility and robotic loading, and continuous wavelength detection, which enables the use of multiple fluorophores in a single reaction. The Allegro System offers an assembly line approach with a modular design that allows reconfiguration of the components to accommodate variations in the assay flow. In the present study, we have established and validated a new automated High Throughput (HT) TaqMan RT-PCR- based method for quantitative mRNA expression analysis. The data demonstrate that HT-Taqman PCR is a powerful tool that can be used for measuring low concentrations of mRNA, and is highly accurate, reproducible, and amenable to high throughput analysis. Results suggest that HT-TaqMan is a reliable method for the quantification of low-expression genes and a powerful tool with HT capability for target identification/validation, structure-activity relationship (SAR) study, compound selection for efficacy studies, and biomarker identification in drug discovery and development.     

Virtual high throughput screening in new lead identification

Drug discovery continues to be one of the greatest contemporary challenges and rational application of modelling approaches is the first important step to obtain lead compounds, which can be optimised further. Virtual high throughput screening (VHTS) is one of the efficient approaches to obtain lead structures for a given target. Strategic application of different screening filters like pharmacophore mapping, shape-based, ligand-based, molecular similarity etc., in combination with other drug design protocols provide invaluable insights in lead identification and optimization. Screening of large databases using these computational methods provides potential lead compounds, thus triggering a meaningful interplay between computations and experiments. In this review, we present a critical account on the relevance of molecular modelling approaches in general, lead optimization and virtual screening methods in particular for new lead identification. The importance of developing reliable scoring functions for non-bonded interactions has been highlighted, as it is an extremely important measure for the reliability of scoring function. The lead optimization and new lead design has also been illustrated with examples. The importance of employing a combination of general and target specific screening protocols has also been highlighted.     

Design of a compound screening collection for use in high throughput screening

In this paper we introduce a quantitative model that relates chemical structural similarity to biological activity, and in particular to the activity of lead series of compounds in high-throughput assays. From this model we derive the optimal screening collection make up for a given fixed size of screening collection, and identify the conditions under which a diverse collection of compounds or a collection focusing on particular regions of chemical space are appropriate strategies. We derive from the model a diversity function that may be used to assess compounds for acquisition or libraries for combinatorial synthesis by their ability to complement an existing screening collection. The diversity function is linked directly through the model to the goal of more frequent discovery of lead series from high-throughput screening. We show how the model may also be used to derive relationships between collection size and probabilities of lead discovery in high-throughput screening, and to guide the judicious application of structural filters.     

A high throughput metabolic stability screening workflow with automated assessment of data quality in pharmaceutical industry

One of the most commonly performed in vitro ADME assays during the lead generation and lead optimization stage of drug discovery is metabolic stability evaluation. Metabolic stability is typically assessed in liver microsomes, which contain Phase I metabolizing enzymes, mainly cytochrome P450 enzymes (CYPs). The amount of parent drug metabolized by these CYPs is determined by LC/MS/MS. The metabolic stability data are typically used to rank order compounds for in vivo evaluation. We describe a streamlined and intelligent workflow for the metabolic stability assay that permits high throughput analyses to be carried out while maintaining the standard of high quality. This is accomplished in the following ways: a novel post-incubation pooling strategy based on c Log D_3.0 values, coupled with ultra-performance liquid chromatography/tandem mass spectrometry (UPLC/MS/MS), enables sample analysis times to be reduced significantly while ensuring adequate chromatographic separation of compounds within a group, so as to reduce the likelihood of compound interference. Assay quality and fast turnaround of data reports is ensured by performing automated real-time intelligent re-analysis of discrete samples for compounds that do not pass user-definable criteria during the pooling analysis. Intelligent, user-independent data acquisition and data evaluation are accomplished via a custom visual basic program that ties together every step in the workflow, including cassette compound selection, compound incubation, compound optimization, sample analysis and re-analysis (when appropriate), data processing, data quality evaluation, and database upload. The workflow greatly reduces labor and improves data turnaround time while maintaining high data quality.     

Functional nucleic acids in high throughput screening and drug discovery

In vitro selection can be used to generate functional nucleic acids such as aptamers and ribozymes that can recognize a variety of molecules with high affinity and specificity. Most often these recognition events are associated with structural alterations that can be converted into detectable signals. Several signaling aptamers and ribozymes constructed by both design and selection have been successfully utilized as sensitive detection reagents. Here we summarize the development of different types of signaling nucleic acids, and approaches that have been implemented in the screening format.     

Recent advances in high throughput screening for ADME properties

With the increase in the numbers of molecules synthesized in a typical drug discovery program, as well as the large amount of information utilized in the selection of a drug candidate, there is a need for a plethora of drug metabolism and pharmacokinetic (DMPK) information to be regularly generated in discovery. Over the past decade, many in vitro, and even in vivo, DMPK screens have been developed and routinely deployed to generate this information in support of drug discovery efforts. In the past few years, newer methods, or adaptations to methods, have been published, and this review attempts to summarize these advances. In particular, advances have been reported for experimental approaches to metabolic clearance, CYP inhibition, in vivo exposure, and distribution, as well as in silico determinations of absorption, distribution, metabolism, and excretion (ADME) properties. Bioanalytical approaches aimed at optimizing analyte method development, sample preparation, and analyte detection, have also been reported. Future advances will further improve the ability to make decisions on molecules earlier in drug discovery.     

Fluorescence-based adenylyl cyclase assay adaptable to high throughput screening

The second messenger cAMP has been implicated in numerous cellular processes such as glycogen metabolism, muscle contraction, learning and memory, and differentiation and development. Genetic evidence suggests that the enzyme that produces cAMP, adenylyl cyclase (AC), may be involved in pathogenesis in many of these cellular processes. In addition, these data suggest that membrane-bound ACs may be valuable targets for therapeutics to treat pathogenesis of these processes. The development of a robust real-time adenylyl cyclase assay that can be scalable to high-throughput screening could help in the development of novel therapeutics. Here we report a novel fluorescence-based cyclase assay using Bodipy FL GTPgammaS (BGTPgammaS). The fluorescence of the Bodipy moiety of BGTPgammaS was dramatically enhanced by incubation with the minimal catalytic core of wild-type-AC (wt-AC) and a mutant with decreased purine selectivity (mut-AC), in an AC activation-dependent manner. No increase in fluorescence was observed using Bodipy FL ATPgammaS (BATPgammaS) as substrate for either wt-AC or mut-AC. Using BGTPgammaS, forskolin, Gsalpha.GTPgammaS and the divalent cation Mn(2+) potently enhanced the rate of fluorescence increase in a concentration-dependent manner. The fluorescence enhancement of the Bodipy moiety was inhibited by known inhibitors of AC such as 2'deoxy,3'AMP and 2',5'-dideoxy-3'ATP. Furthermore, the fluorescence assay is adaptable to 96-well and 384-well multiplate format and is thus applicable to high throughput screening methodologies.     

Integration of virtual and high throughput screening in lead discovery settings

In the last decade mass screening strategies became the main source of leads in drug discovery settings. Although high throughput (HTS) and virtual screening (VS) realize the same concept the different nature of these lead discovery strategies (experimental vs theoretical) results that they are typically applied separately. The majority of drug leads are still identified by hit-to-lead optimization of screening hits. Structural information on the target as well as on bound ligands, however, make structure-based and ligand-based virtual screening available for the identification of alternative chemical starting points. Although, the two techniques have rarely been used together on the same target, here we review the existing prominent studies on their true integration. Various approaches have been shown to apply the combination of HTS and VS and to better use them in lead generation. Although several attempts on their integration have only been considered at a conceptual level, there are numerous applications underlining its relevance that early-stage pharmaceutical drug research could benefit from a combined approach.     

Discovery of novel targets with high throughput RNA interference screening

High throughput technologies have the potential to affect all aspects of drug discovery. Considerable attention is paid to high throughput screening (HTS) for small molecule lead compounds. The identification of the targets that enter those HTS campaigns had been driven by basic research until the advent of genomics level data acquisition such as sequencing and gene expression microarrays. Large-scale profiling approaches (e.g., microarrays, protein analysis by mass spectrometry, and metabolite profiling) can yield vast quantities of data and important information. However, these approaches usually require painstaking in silico analysis and low-throughput basic wet-lab research to identify the function of a gene and validate the gene product as a potential therapeutic drug target. Functional genomic screening offers the promise of direct identification of genes involved in phenotypes of interest. In this review, RNA interference (RNAi) mediated loss-of-function screens will be discussed and as well as their utility in target identification. Some of the genes identified in these screens should produce similar phenotypes if their gene products are antagonized with drugs. With a carefully chosen phenotype, an understanding of the biology of RNAi and appreciation of the limitations of RNAi screening, there is great potential for the discovery of new drug targets.     

K-Screen: a free application for high throughput screening data analysis, visualization, and laboratory information management

High throughput screening (HTS) has emerged as an important technique for allowing researchers to rapidly profile very large numbers of chemicals against drug targets. As recent and future advances make HTS cheaper to perform on even larger scales, the amount of data that has to be processed, analyzed, and searched will only grow larger in size and harder for researchers to manually sift through. It is therefore an unavoidable requirement that institutions utilizing HTS technology will need to begin looking for effective solutions in the maturing area of laboratory information management systems like many other types of labs have already done. K-Screen is one such solution. Our initial goal with K-Screen was to have an integrated application environment that supported data analysis, management, and presentation so we could efficiently perform client requested screens and searches as well as generate detailed reports on the results of those. Previously, we had attempted but failed to locate an existing software suite that sufficiently addressed all our requirements. K-Screen is a web accessible application that offers the ability to host a large chemical structure library, process and store single-dose (primary) and dose response (secondary) screening data, perform searches based on screening results, plate coordinates, and structure, substructure and structure similarity. It uses heat maps and histograms to visualize screen or plate level statistics. Interfaces to external searches against PubChem and ZINC databases are also provided. We feel that these features make K-Screen a practical and effective alternative to other commercial or academic HTS LIMS systems.     

Microfluidics for cell-based high throughput screening platforms—A review

In the last decades, the basic techniques of microfluidics for the study of cells such as cell culture, cell separation, and cell lysis, have been well developed. Based on cell handling techniques, microfluidics has been widely applied in the field of PCR (Polymerase Chain Reaction), immunoassays, organ-on-chip, stem cell research, and analysis and identification of circulating tumor cells. As a major step in drug discovery, high-throughput screening allows rapid analysis of thousands of chemical, biochemical, genetic or pharmacological tests in parallel. In this review, we summarize the application of microfluidics in cell-based high throughput screening. The screening methods mentioned in this paper include approaches using the perfusion flow mode, the droplet mode, and the microarray mode. We also discuss the future development of microfluidic based high throughput screening platform for drug discovery.     

Surrogate docking: structure-based virtual screening at high throughput speed

Summary Structure-based screening using fully flexible docking is still too slow for large molecular libraries. High quality docking of a million molecule library can take days even on a cluster with hundreds of CPUs. This performance issue prohibits the use of fully flexible docking in the design of large combinatorial libraries. We have developed a fast structure-based screening method, which utilizes docking of a limited number of compounds to build a 2D QSAR model used to rapidly score the rest of the database. We compare here a model based on radial basis functions and a Bayesian categorization model. The number of compounds that need to be actually docked depends on the number of docking hits found. In our case studies reasonable quality models are built after docking of the number of molecules containing 50 docking hits. The rest of the library is screened by the QSAR model. Optionally a fraction of the QSAR-prioritized library can be docked in order to find the true docking hits. The quality of the model only depends on the training set size – not on the size of the library to be screened. Therefore, for larger libraries the method yields higher gain in speed no change in performance. Prioritizing a large library with these models provides a significant enrichment with docking hits: it attains the values of 13 and 35 at the beginning of the score-sorted libraries in our two case studies: screening of the NCI collection and a combinatorial libraries on CDK2 kinase structure. With such enrichments, only a fraction of the database must actually be docked to find many of the true hits. The throughput of the method allows its use in screening of large compound collections and in the design of large combinatorial libraries. The strategy proposed has an important effect on efficiency but does not affect retrieval of actives, the latter being determined by the quality of the docking method itself. Electronic supplementary material is available at http://dx.doi.org/10.1007/s10822-005-9002-6.     

Homogeneous single-label tyrosine kinase activity assay for high throughput screening

Protein post-translational modifications (PTMs) are regulatory mechanisms carried out by different enzymes in a cell. Kinase catalyzed phosphorylation is one of the most important PTM affecting the protein activity and function. We have developed a single-label quenching resonance energy transfer (QRET) assay to monitor tyrosine phosphorylation in a homogeneous high throughput compatible format. Epidermal growth factor receptor (EGFR) induced phosphorylation was monitored using Eu³⁺-chelate labeled peptide and label-free phosphotyrosine specific antibody in presence of a soluble quencher molecule. In the QRET kinase assay, antibody binding to phosphorylated Eu³⁺-peptide protects the Eu³⁺-chelate from luminescence quenching, monitoring high time-resolved luminescence (TRL) signals. In the presence of specific kinase inhibitor, antibody recognition and Eu³⁺-chelate protection is prevented, allowing an efficient luminescence quenching. The assay functionality was demonstrated with a panel of EGFR inhibitors (AG-1478, compound 56, erlotinib, PD174265, and staurosporine). The monitored IC₅₀ values ranged from 0.08 to 155.3 nM and were comparable to those found in the literature. EGFR activity and inhibition assays were performed using low nanomolar enzyme and antibody concentration in a 384-well plate format, demonstrating its compatibility for high throughput screening (HTS).