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.     

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.     

Cell-based screening: a high throughput flow cytometry platform for identification of cell-specific targeting molecules

Targeting of drugs and genes to specific cell types is an emerging paradigm in the treatment of many medical conditions. However, targeting structures such as peptides are susceptible to rapid inactivation in vivo. To address this problem, novel targeting molecules can now be rapidly synthesized using a combinatorial approach. Methods to screen the large libraries created in this process are often lacking or compatible only with solution-based screening. This report describes a high-throughput cell-based method utilizing flow cytometry, capable of rapidly screening large libraries of molecules simultaneously for biological functionality and stability. In this method, each library molecule is attached to a microsphere exhibiting a unique set of optical properties, or "fingerprint", conferring modularity and multiplex capability. We investigated the multiplex capability of our flow cytometric method to determine its capacity for high-throughput screening. Current instrumentation in our laboratory allows the screening of at least 75 unique compounds in a single well, a number comparable to available solution-based assays. In state-of-the-art configuration, however, this methodology can support the screening of up to 1875 compounds per well, achieving high-throughput potential in a single multiwell plate. We also investigated the binding capability of targeted microspheres to adherent target cells. These microspheres exhibited a 12-fold increase in binding over control, untargeted microspheres. Competitive inhibition experiments with soluble ligand confirmed the specificity of microsphere binding. Overall, the methodology proposed here is capable of quickly and effectively screening large libraries of targeting molecules using instrumentation readily available to the greater research community.     

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.     

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.     

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.     

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.     

Discovery of a new family of chromium ethylene polymerisation catalysts using high throughput screening methodology

Following a discovery that salicylaldimines bearing bulky ortho-phenoxy substituents and small imine substituents give very active chromium catalysts for ethylene polymerisation, High Throughput Screening (HTS) methodology has been employed to facilitate a further discovery of exceptionally active catalysts based on tridentate salicylaldimine ligands with bulky triptycenyl groups.     

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.     

Automatic poisson peak harvesting for high throughput protein identification

High throughput identification of proteins by peptide mass fingerprinting requires an efficient means of picking peaks from mass spectra. Here, we report the development of a peak harvester to automatically pick monoisotopic peaks from spectra generated on matrix-assisted laser desorption/ionisation time of flight (MALDI-TOF) mass spectrometers. The peak harvester uses advanced mathematical morphology and watershed algorithms to first process spectra to stick representations. Subsequently, Poisson modelling is applied to determine which peak in an isotopically resolved group represents the monoisotopic mass of a peptide. We illustrate the features of the peak harvester with mass spectra of standard peptides, digests of gel-separated bovine serum albumin, and with Escherictia coli proteins prepared by two-dimensional polyacrylamide gel electrophoresis. In all cases, the peak harvester proved effective in its ability to pick similar monoisotopic peaks as an experienced human operator, and also proved effective in the identification of monoisotopic masses in cases where isotopic distributions of peptides were overlapping. The peak harvester can be operated in an interactive mode, or can be completely automated and linked through to peptide mass fingerprinting protein identification tools to achieve high throughput automated protein identification.     

Design of new plasmepsin inhibitors: a virtual high throughput screening approach on the EGEE grid

Though different species of the genus Plasmodium may be responsible for malaria, the variant caused by P. falciparum is often very dangerous and even fatal if untreated. Hemoglobin degradation is one of the key metabolic processes for the survival of the Plasmodium parasite in its host. Plasmepsins, a family of aspartic proteases encoded by the Plasmodium genome, play a prominent role in host hemoglobin cleavage. In this paper we demonstrate the use of virtual screening, in particular molecular docking, employed at a very large scale to identify novel inhibitors for plasmepsins II and IV. A large grid infrastructure, the EGEE grid, was used to address the problem of large computation resources required for docking hundreds of thousands of chemical compounds on different plasmepsin targets of P. falciparum. A large compound library of about 1 million chemical compounds was docked on 5 different targets of plasmepsins using two different docking software, namely FlexX and AutoDock. Several strategies were employed to analyze the results of this virtual screening approach including docking scores, ideal binding modes, and interactions to key residues of the protein. Three different classes of structures with thiourea, diphenylurea, and guanidino scaffolds were identified to be promising hits. While the identification of diphenylurea compounds is in accordance with the literature and thus provides a sort of "positive control", the identification of novel compounds with a guanidino scaffold proves that high throughput docking can be effectively used to identify novel potential inhibitors of P. falciparum plasmepsins. Thus, with the work presented here, we do not only demonstrate the relevance of computational grids in drug discovery but also identify several promising small molecules which have the potential to serve as candidate inhibitors for P. falciparum plasmepsins. With the use of the EGEE grid infrastructure for the virtual screening campaign against the malaria causing parasite P. falciparum we have demonstrated that resource sharing on an eScience infrastructure such as EGEE provides a new model for doing collaborative research to fight diseases of the poor.     

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.     

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.     

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).     

Current trends in virtual high throughput screening using ligand-based and structure-based methods

High throughput in silico methods have offered the tantalizing potential to drastically accelerate the drug discovery process. Yet despite significant efforts expended by academia, national labs and industry over the years, many of these methods have not lived up to their initial promise of reducing the time and costs associated with the drug discovery enterprise, a process that can typically take over a decade and cost hundreds of millions of dollars from conception to final approval and marketing of a drug. Nevertheless structure-based modeling has become a mainstay of computational biology and medicinal chemistry, helping to leverage our knowledge of the biological target and the chemistry of protein-ligand interactions. While ligand-based methods utilize the chemistry of molecules that are known to bind to the biological target, structure-based drug design methods rely on knowledge of the three-dimensional structure of the target, as obtained through crystallographic, spectroscopic or bioinformatics techniques. Here we review recent developments in the methodology and applications of structure-based and ligand-based methods and target-based chemogenomics in Virtual High Throughput Screening (VHTS), highlighting some case studies of recent applications, as well as current research in further development of these methods. The limitations of these approaches will also be discussed, to give the reader an indication of what might be expected in years to come.