High-throughput siRNA-based functional target validation

The drug discovery process pursued by major pharmaceutical companies for many years starts with target identification followed by high-throughput screening (HTS) with the goal of identifying lead compounds. To accomplish this goal, significant resources are invested into automation of the screening process or HTS. Robotic systems capable of handling thousands of data points per day are implemented across the pharmaceutical sector. Many of these systems are amenable to handling cell-based screening protocols as well. On the other hand, as companies strive to develop innovative products based on novel mechanisms of action(s), one of the current bottlenecks of the industry is the target validation process. Traditionally, bioinformatics and HTS groups operate separately at different stages of the drug discovery process. The authors describe the convergence and integration of HTS and bioinformatics to perform high-throughput target functional identification and validation. As an example of this approach, they initiated a project with a functional cell-based screen for a biological process of interest using libraries of small interfering RNA (siRNA) molecules. In this protocol, siRNAs function as potent gene-specific inhibitors. siRNA-mediated knockdown of the target genes is confirmed by TaqMan analysis, and genes with impacts on biological functions of interest are selected for further analysis. Once the genes are confirmed and further validated, they may be used for HTS to yield lead compounds.     

The future of high-throughput screening

High-throughput screening (HTS) is a well-established process in lead discovery for pharma and biotech companies and is now also being set up for basic and applied research in academia and some research hospitals. Since its first advent in the early to mid-1990s, the field of HTS has seen not only a continuous change in technology and processes but also an adaptation to various needs in lead discovery. HTS has now evolved into a quite mature discipline of modern drug discovery. Whereas in previous years, much emphasis has been put toward a steady increase in capacity ("quantitative increase") via various strategies in the fields of automation and miniaturization, the past years have seen a steady shift toward higher content and quality ("quality increase") for these biological test systems. Today, many experts in the field see HTS at the crossroads with the need to decide either toward further increase in throughput or more focus toward relevance of biological data. In this article, the authors describe the development of HTS over the past decade and point out their own ideas for future directions of HTS in biomedical research. They predict that the trend toward further miniaturization will slow down with the implementation of 384-well, 1536-well, and 384 low-volume-well plates. The authors predict that, ultimately, each hit-finding strategy will be much more project related, tailor-made, and better integrated into the broader drug discovery efforts.     

Marcel Faber Roundtable: Is our antibiotic pipeline unproductive because of starvation, constipation or lack of inspiration?

There are few new antibiotics in the pipeline today. The reasons may include starvation at the front of the pipeline due to inadequate sources of suitable compounds to screen coupled with poorly validated discovery methodologies. A successful antibiotic discovery approach in the past, based upon whole cell antibiotic screening of natural products from actinomycetes and fungi, eventually suffered from constipation in the middle of the pipeline due to rediscovery of known compounds, even though low throughput methodology was employed at the front end. The current lack of productivity may be attributed to the poor choice of strategies to address the discovery of new antibiotics. Recent applications of high throughput in vitro screening of individual antibacterial targets to identify lead compounds from combinatorial chemical libraries, traditional chemical libraries, and partially purified natural product extracts has not produced any significant clinical candidates. The solution to the current dilemma may be to return to natural product whole cell screening. For this approach to work in the current millennium, the process needs to be miniaturized to increase the throughput by orders of magnitude over traditional screening, and the rediscovery of known antibiotics needs to be minimized by methods that can be readily monitored and improved over time.     

Fragment-based lead discovery: a chemical update

Fragment-based lead discovery constructs drug leads from small molecular fragments. In theory, this is a highly efficient method for drug discovery, and the technique has become enormously popular in the past few years. In this review, I describe how a variety of approaches in fragment-based lead discovery--including NMR, X-ray crystallography, mass spectrometry, functional screening, and in silico screening--have produced drug leads. Although the examples show that the technique can reliably generate potent molecules, there is still much work to be done to maintain the efficiency of molecules' binding affinities as fragments are linked, expanded, and otherwise improved.     

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.     

Multiplexing nuclear receptors for agonist identification in a cell-based reporter gene high-throughput screen

High-throughput screening (HTS) has become an essential part of the drug discovery process. Due to the rising requirements for both data quality and quantity, along with increased screening cost and the demand to shorten the time for lead identification, increasing throughput and cost-effectiveness has become a necessity in the hit identification process. The authors present a multiplexed HTS for 2 nuclear receptors, the farnesoid X-activated receptor and the peroxisome proliferator-activated receptor delta in a viable cell-based reporter gene assay. The 2 nuclear receptors were individually transfected into human hepatoma cells, and the transient transfected cell lines were pooled for the multiplexed screen. Hits identified by the multiplexed screen are similar to those identified by the individual receptor screens. Furthermore, the multiplexed screen provides selectivity information if ligands selective for one and not the other receptor are one of the hit criteria. The data demonstrate that multiplexing nuclear receptors can be a simple, efficient, cost-effective, and reliable alternative to traditional HTS of individual targets without compromising data quality.     

Design and Implementation of High Throughput Screening Assays

High throughput screening (HTS) is at the core of the drug discovery process, and so it is critical to design and implement HTS assays in a comprehensive fashion involving scientists from the disciplines of biology, chemistry, engineering, and informatics. This requires careful analysis of many variables, starting with the choice of assay target and ending with the discovery of lead compounds. At every step in this process, there are decisions to be made that can greatly impact the outcome of the HTS effort, to the point of making it a success or a failure. Although specific guidelines should be established to insure that the screening assay reaches an acceptable level of quality, many choices require pragmatism and the ability to compromise opposing forces.     

Statistical and graphical methods for quality control determination of high-throughput screening data

High-throughput screening (HTS) is used in modern drug discovery to screen hundreds of thousands to millions of compounds on selected protein targets. It is an industrial-scale process relying on sophisticated automation and state-of-the-art detection technologies. Quality control (QC) is an integral part of the process and is used to ensure good quality data and mini mize assay variability while maintaining assay sensitivity. The authors describe new QC methods and show numerous real examples from their biologist-friendly Stat Server HTS application, a custom-developed software tool built from the commercially available S-PLUS and Stat Server statistical analysis and server software. This system remotely processes HTS data using powerful and sophisticated statistical methodology but insulates users from the technical details by outputting results in a variety of readily interpretable graphs and tables. It allows users to visualize HTS data and examine assay performance during the HTS campaign to quickly react to or avoid quality problems.     

Virtual screening strategies in drug discovery

The identification of novel therapeutic targets and characterization of their 3D structures is increasing at a dramatic rate. Computational screening methods continue to be developed and improved as credible and complementary alternatives to high-throughput biochemical compound screening (HTS). While the majority of drug candidates currently being developed have been found using HTS methods, high-throughput docking and pharmacophore-based searching algorithms are gaining acceptance and becoming a major source of lead molecules in drug discovery. Refinements and optimization of high-throughput docking methods have lead to improvements in reproducing experimental data and in hit rates obtained, validating their use in hit identification. In parallel with virtual screening methods, concomitant developments in cheminformatics including identification, design and manipulation of drug-like small molecule libraries have been achieved. Herein, currently used in silico screening techniques and their utility on a comparative and target dependent basis is discussed.     

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.     

LC-NMR: a new tool to expedite the dereplication and identification of natural products

The rapid identification of known or undesirable compounds from natural products extracts — “dereplication” — is an important step in an efficiently run natural products discovery program. Dereplication strategies use analytical techniques and database searching to determine the identity of an active compound at the earliest possible stage in the discovery process. In the past few years, advances in technology have allowed the development of tandem analytical techniques such as liquid chromatography mass spectrometry (LC-MS), LC-MS-MS, liquid chromatography nuclear magnetic resonance (LC-NMR), and LC-NMR-MS. LC-NMR, despite its lower sensitivity as compared to LC-MS, provides a powerful tool for rapid identification of known compounds and identification of structure classes of novel compounds. LC-NMR is especially useful in instances where the data from LC-MS are incomplete or do not allow confident identification of the active component of a sample. LC-NMR has been used to identify the marine alkaloid aaptamine as the active component in an extract of the sponge Aaptos sp. This extract had been identified as an enzyme inhibitor by a high throughput screening (HTS) effort. Isolated aaptamine exhibited an IC₅₀=120 μM against this enzyme. Strategies for the identification of aaptamine and for the use of LC-NMR in a natural products HTS program are discussed. Journal of Industrial Microbiology & Biotechnology (2000) 25, 342–345. Received 30 March 2000/ Accepted in revised form 03 July 2000     

Novel miniaturized systems in high-throughput screening

High-throughput screening (HTS) using high-density microplates is the primary method for the discovery of novel lead candidate molecules. However, new strategies that eschew 2D microplate technology, including technologies that enable mass screening of targets against large combinatorial libraries, have the potential to greatly increase throughput and decrease unit cost. This review presents an overview of state-of-the-art microplate-based HTS technology and includes a discussion of emerging miniaturized systems for HTS. We focus on new methods of encoding combinatorial libraries that promise throughputs of as many as 100,000 compounds per second.     

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.     

Virtual high-throughput in silico screening

In silico methods may benefit drug discovery and development significantly by saving an average of $130 million and 0.8 years per drug. Virtual high-throughput screening (vHTS) applies in silico approaches, such as docking and alignment, to large virtual molecular databases to enrich biologically active compounds in order to yield lead structures. In an industrial environment, the commonly used ligand-based and receptor-based methods outlined here need to be computationally faster to return the utmost benefit. Intelligent database searching using new fast feedback-driven screening methods appears to be particularly rewarding in terms of both cost and time benefits.     

Docking, virtual high throughput screening and in silico fragment-based drug design

The drug discovery process has been profoundly changed recently by the adoption of computational methods helping the design of new drug candidates more rapidly and at lower costs. In silico drug design consists of a collection of tools helping to make rational decisions at the different steps of the drug discovery process, such as the identification of a biomolecular target of therapeutical interest, the selection or the design of new lead compounds and their modification to obtain better affinities, as well as pharmacokinetic and pharmacodynamic properties. Among the different tools available, a particular emphasis is placed in this review on molecular docking, virtual high-throughput screening and fragment-based ligand design.     

Joint effects of acetochlor and urea on germinating characteristics of crop seeds

Neuraminidase (NA) is one of the most important targets to screen the drugs of anti-influenza virus A and B. After virtual screening approaches were applied to a compound database which possesses more than 10000 compound structures, 160 compounds were selected for bioactivity assay, then a High Throughput Screening (HTS) model established for influenza virus NA inhibitors was applied to detect these compounds. Finally, three compounds among them displayed higher inhibitory activities, the range of their IC5o was from 0.1 μmol/L to 3 μmol/L. Their structural scaffolds are novel and different from those of NA inhibitors approved for influenza treatment, and will be useful for the design and research of new NA inhibitors. The result indicated that the combination of virtual screening with HTS was very significant to drug screening and drug discovery.     

Drug screening for influenza neuraminidase inhibitors

Neuraminidase (NA) is one of the most important targets to screen the drugs of anti-influenza virus A and B. After virtual screening approaches were applied to a compound database which possesses more than 10000 compound structures, 160 compounds were selected for bioactivity assay, then a High Throughput Screening (HTS) model established for influenza virus NA inhibitors was applied to detect these compounds. Finally, three compounds among them displayed higher inhibitory activities, the range of their IC50 was from 0.1 μmol/L to 3μmol/L. Their structural scaffolds are novel and different from those of NA inhibitors approved for influenza treatment, and will be useful for the design and research of new NA inhibitors. The resuit indicated that the combination of virtual screening with HTS was very significant to drug screening and drug discovery.     

High-throughput screening: update on practices and success

High-throughput screening (HTS) has become an important part of drug discovery at most pharmaceutical and many biotechnology companies worldwide, and use of HTS technologies is expanding into new areas. Target validation, assay development, secondary screening, ADME/Tox, and lead optimization are among the areas in which there is an increasing use of HTS technologies. It is becoming fully integrated within drug discovery, both upstream and downstream, which includes increasing use of cell-based assays and high-content screening (HCS) technologies to achieve more physiologically relevant results and to find higher quality leads. In addition, HTS laboratories are continually evaluating new technologies as they struggle to increase their success rate for finding drug candidates. The material in this article is based on a 900-page HTS industry report involving 54 HTS directors representing 58 HTS laboratories and 34 suppliers.     

Miniaturization of a Mammalian Cell-Based Assay: Luciferase Reporter Gene Readout in a 3 Microliter 1536-Well Plate

The combined efforts of the fields of combinatorial chemistry and genomics have significantly increased the number of compounds and therapeutic targets available for screening. The number of compounds will reach into the million range in the near future and provide vast chemical diversity for drug discovery. However, this reservoir of chemical diversity creates downstream hurdles for any screening effort. Properly examining this number of compounds increases investments dramatically, both in the number of dollars spent and amount of limited reagents depleted. Traditional HTS techniques, such as the use of 96-well microtiter plates, have paved the way for faster processing speeds, but are being rapidly overwhelmed by screening demands. Miniaturization of such assays will allow for greater throughput, while concurrently reducing cost. To date, miniaturization efforts have been most successfully applied to bacterial and soluble protein based assays. Questions about the ability to deliver microquantities of mammalian cells without disruption of the cell membrane and/or activation of stress responses have been raised. An assay has been developed in which a human T-cell screen has been adapted to a 1536-well plate format. Through the use of a luciferase reporter gene system, it is shown that a mammalian cell-based assay may be successfully performed in 3 μl and potent inhibitors of the target of interest identified.     

The High Throughput Screening Infrastructure: The Right Tools for the Task

HTS is a key component of pharmaceutical lead identification process. Over recent years, the pharmaceutical industry has experienced significant increases in the throughput capabilities of its HTS functions. In those companies where HTS has been effectively deployed, it is now possible to screen the entire corporate compound collection against a pharmacological target within a timescale of several weeks to a few months. This capability has been realized, not as a result of the purchase of any one particular piece of hardware, but rather through the development of a truly effective HTS infrastructure that matches the needs of the parent organization. Central to this is the need to understand how to effectively combine the use of the different types of hardware available to the HTS specialist. The use of both modular workstations and single-arm robotic systems have underpinned most HTS groups operations. Recent advances in the field of multiple-arm robotic systems and dedicated automation systems offer even further potential for increasing productivity. This article describes our experience with the use of a dedicated automation system for HTS applications.