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.     

High throughput screening informatics

High throughput screening (HTS), an industrial effort to leverage developments in the areas of modern robotics, data analysis and control software, liquid handling devices, and sensitive detectors, has played a pivotal role in the drug discovery process, allowing researchers to efficiently screen millions of compounds to identify tractable small molecule modulators of a given biological process or disease state and advance them into high quality leads. As HTS throughput has significantly increased the volume, complexity, and information content of datasets, lead discovery research demands a clear corporate strategy for scientific computing and subsequent establishment of robust enterprise-wide (usually global) informatics platforms, which enable complicated HTS work flows, facilitate HTS data mining, and drive effective decision-making. The purpose of this review is, from the data analysis and handling perspective, to examine key elements in HTS operations and some essential data-related activities supporting or interfacing the screening process, and outline properties that various enabling software should have. Additionally, some general advice for corporate managers with system procurement responsibilities is offered.     

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.     

The use of immortalized cell lines in GPCR screening: the good, bad and ugly

For most membrane-bound molecular targets, including G protein linked receptors (GPCRs), the optimal approach in drug discovery involves the use of cell based high throughput screening (HTS) technologies to identify compounds that modulate target activity. Most GPCRs have been cloned and can therefore be routinely expressed in immortalized cell lines. These cells can be easily and rapidly grown in unlimited quantities making them ideal for use in current HTS technologies. A significant advantage of this approach is that immortalized recombinant cells provide a homogenous background for expression of the target which greatly facilitates consistency in screening, thus allowing for a better understanding of the mechanism of action of the interacting compound or drug. Nonetheless, it is now evident that numerous disparities exist between the physiological environment of screening systems using recombinant cells and natural tissues. This has lead to a problem in the validity of the pharmacological data obtained using immortalized cells in as much as such cells do not always reflect the desired clinical efficacy and safety of the compounds under examination. This brief review discusses these issues and describes how they influence the discovery of drugs using modern HTS.     

An overview of drug screening using primary and embryonic stem cells

Cellular technologies are widely used in drug discovery to treat human diseases. Most studies involve the expression of recombinant targets in immortalized cells and measure drug interactions using simple, quantifiable responses. Such cells are also amenable to high throughput screening (HTS) methods. However, the cell phenotype employed in HTS is often determined by the assay technology available, rather than the physiological relevance of the cell background. They are, therefore, suboptimal surrogates for cells that accurately reflect human diseases. Consequently, there is growing interest in adopting primary and embryonic stem cells in drug discovery. Primary cells are already used in secondary screening assays in conjunction with confocal imaging techniques, as well as in target validation studies employing, for example, gene silencing approaches. Stem cells can be grown in unlimited quantities and can be derived from transgenic animals engineered to express disease causing proteins better coupling the molecular target with function in vivo. Human stem cells also offer unique opportunities for drug discovery in that they can be directed to specific phenotypes thus providing a framework to identify tissue-selective agents. Organizing stem cells into networks resembling those in native tissues, potentially returns drug discovery back to the highly successful pharmacological methods of the past, in which organ and tissue based systems were used, but with the advantage that they can be utilized using modern HTS technologies. This emerging area will lead to discovery of compounds whose effect in vivo is more predictable thereby increasing the efficiency of drugs that ameliorate human disease.     

Fragment-based drug design: computational & experimental state of the art

Fragment-based screening is an emerging technology which is used as an alternative to high-throughput screening (HTS), and often in parallel. Fragment screening focuses on very small compounds. Because of their small size and simplicity, fragments exhibit a low to medium binding affinity (mM to μM) and must therefore be screened at high concentration in order to detect binding events. Since some issues are associated with high-concentration screening in biochemical assays, biophysical methods are generally employed in fragment screening campaigns. Moreover, these techniques are very sensitive and some of them can give precise information about the binding mode of fragments, which facilitates the mandatory hit-to-lead optimization. One of the main advantages of fragment-based screening is that fragment hits generally exhibit a strong binding with respect to their size, and their subsequent optimization should lead to compounds with better pharmacokinetic properties compared to molecules evolved from HTS hits. In other words, fragments are interesting starting points for drug discovery projects. Besides, the chemical space of low-complexity compounds is very limited in comparison to that of drug-like molecules, and thus easier to explore with a screening library of limited size. Furthermore, the "combinatorial explosion" effect ensures that the resulting combinations of interlinked binding fragments may cover a significant part of "drug-like" chemical space. In parallel to experimental screening, virtual screening techniques, dedicated to fragments or wider compounds, are gaining momentum in order to further reduce the number of compounds to test. This article is a review of the latest news in both experimental and in silico virtual screening in the fragment-based discovery field. Given the specificity of this journal, special attention will be given to fragment library design.     

Unmodified methodologies in target discovery for small molecule drugs: A rising star

Target discovery, involving target identification and validation, is the prerequisite for drug discovery and screening. Novel methodologies and technologies for the precise discovery and confirmation of drug targets are powerful tools in understanding the disease, looking for a drug and elucidating the mechanism of drug treatment. Among the common target identification and confirmation methods, the modified method is time-consuming and laborious, which may reduce or change the activity of natural products. The unmodified methods developed in recent years without chemical modification have gradually become an important means of studying drug targets. A wide range of unmodified approaches have been reported, introducing and analyzing the recent emerging methodologies and technologies. This review highlights the advantages and limitations of these methods for the application of drug target discovery and presents an overview of their contributions to the target discovery of small molecule drugs. The application and future development trends of methodologies in target discovery are also prospected to provide a reference for drug target research.     

分子阵列研究进展

小分子化合物可以调节生物学过程,是研究活性生物大分子（特别是蛋白质）以及药物的重要工具,而高通量筛选是发现活性分子的重要方法。分子阵列是近年来新出现的一种高通量筛选技术,上面含有成千上万种组合合成的化合物以及天然产物,可以用于发现新的先导化合物,以及筛选已有的先导化合物。现在分子阵列已经成功应用于蛋白分析、先导化合物的发现等许多领域。本文综述了近年来分子阵列的构建过程,原位合成、非原位合成等各种固定化策略以及荧光免疫检测,表面等离子体共振成像技术等检测手段,并介绍了化学分子印刷阵列方法,最后总结了分子阵列的应用,并对分子阵列在我国中药发展等有方面将起到的潜在作用作了展望。     

Binary quantitative structure-activity relationship (QSAR) analysis of estrogen receptor ligands

The use of high throughput screening (HTS) to identify lead compounds has greatly challenged conventional quantitative structure-activity relationship (QSAR) techniques that typically correlate structural variations in similar compounds with continuous changes in biological activity. A new QSAR-like methodology that can correlate less quantitative assay data (i.e., "active" versus "inactive"), as initially generated by HTS, has been introduced. In the present study, we have, for the first time, applied this approach to a drug discovery problem; that is, the study of the estrogen receptor ligands. The binding affinities of 463 estrogen analogues were transformed into a binary data format, and a predictive binary QSAR model was derived using 410 estrogen analogues as a training set. The model was applied to predict the activity of 53 estrogen analogues not included in the training set. An overall accuracy of 94% was obtained.     

Modern drug discovery technologies: opportunities and challenges in lead discovery

The identification of promising hits and the generation of high quality leads are crucial steps in the early stages of drug discovery projects. The definition and assessment of both chemical and biological space have revitalized the screening process model and emphasized the importance of exploring the intrinsic complementary nature of classical and modern methods in drug research. In this context, the widespread use of combinatorial chemistry and sophisticated screening methods for the discovery of lead compounds has created a large demand for small organic molecules that act on specific drug targets. Modern drug discovery involves the employment of a wide variety of technologies and expertise in multidisciplinary research teams. The synergistic effects between experimental and computational approaches on the selection and optimization of bioactive compounds emphasize the importance of the integration of advanced technologies in drug discovery programs. These technologies (VS, HTS, SBDD, LBDD, QSAR, and so on) are complementary in the sense that they have mutual goals, thereby the combination of both empirical and in silico efforts is feasible at many different levels of lead optimization and new chemical entity (NCE) discovery. This paper provides a brief perspective on the evolution and use of key drug design technologies, highlighting opportunities and challenges.     

Integration of NMR and high-throughput screening

NMR-based screening has become a powerful method for the identification and analysis of low-molecular weight organic compounds that bind to protein targets and can be utilized in drug discovery programs. In particular, heteronuclear NMR-based screening can yield information about both the affinity and binding location of potential lead compounds. In addition, heteronuclear NMR-based screening has wide applications in complementing and facilitating conventional high-throughout screening programs. This article will describe several strategies for the integration of NMR-based screening and high-throughput screening. The marriage of these two techniques promises to be of tremendous benefit in the triage of hits that come from HTS, and can aid the medicinal chemist in the identification of quality leads that have high potential for further optimization.     

Impact of novel screening technologies on ion channel drug discovery

Ion channels are a large superfamily of membrane proteins that pass ions across membranes. They are critical to diverse physiological functions in both excitable and nonexcitable cells and underlie many diseases. As a result, they are an important target class which is proven to be highly "druggable". However, for high throughput screening (HTS), ion channels are historically difficult as a target class due to their unique molecular properties and the limitations of assay technologies that are HTS-amendable. In this article, we describe the background of ion channels and current status and challenges for ion channel drug discovery, followed by an overview of both conventional and newly emerged ion channel screening technologies. The critical impact of such new technologies on current and future ion channel drug discovery is also discussed.     

Cytokine antibody arrays: a promising tool to identify molecular targets for drug discovery

Cytokines play important roles in normal cell functions and changes in cytokines have been implicated in many diseases. Recent efforts have focused on developing cytokine antibody arrays. These arrays allow investigators to simultaneously detect multiple cytokines in qualitative and quantitative ways. Cytokine antibody array systems feature high sensitivity, specificity and throughput. This novel technology opens up an expanding spectrum of applications in drug discovery, including target discovery, target validation, screening for lead compounds, compound optimization and clinical trials.     

Targeting chemical inputs and optimising HTS for agrochemical discovery

In vivo high throughput screening (HTS) has been adopted by most of the larger crop protection companies as an important tool for the discovery of new agrochemicals. There has been a paradigm shift in capabilities from screening a few thousand compounds a year to several hundred thousand and the quantity of screening sample required has fallen dramatically. The unifying goal now bringing together screens and inputs is the need to maximise the flow of useful information from HTS and thereby minimise the time taken to discover robust leads and new products. This review examines the positive changes that have occurred towards targeted design and selection of chemical inputs for agrochemical discovery over the last ten years and corresponding developments in HTS assays, data analysis and the logistics of compound storage and dispensing.     

Novel statistical approach for primary high-throughput screening hit selection

The standard activity threshold-based method (the "top X" approach), currently widely used in the high-throughput screening (HTS) data analysis, is ineffective at identifying good-quality hits. We have proposed a novel knowledge-based statistical approach, driven by the hidden structure-activity relationship (SAR) within a screening library, for primary hit selection. Application to an in-house ultrahigh-throughput screening (uHTS) campaign has demonstrated it can directly identify active scaffolds containing valuable SAR information with a greatly improved confirmation rate compared to the standard "top X" method (from 55% to 85%). This approach may help produce high-quality leads and expedite the hit-to-lead process in drug discovery.     

ALARM NMR: a rapid and robust experimental method to detect reactive false positives in biochemical screens

High-throughput screening (HTS) of large compound collections typically results in numerous small molecule hits that must be carefully evaluated to identify valid drug leads. Although several filtering mechanisms and other tools exist that can assist the chemist in this process, it is often the case that costly synthetic resources are expended in pursuing false positives. We report here a rapid and reliable NMR-based method for identifying reactive false positives including those that oxidize or alkylate a protein target. Importantly, the reactive species need not be the parent compound, as both reactive impurities and breakdown products can be detected. The assay is called ALARM NMR (a La assay to detect reactive molecules by nuclear magnetic resonance) and is based on monitoring DTT-dependent (13)C chemical shift changes of the human La antigen in the presence of a test compound or mixture. Extensive validation has been performed to demonstrate the reliability and utility of using ALARM NMR to assess thiol reactivity. This included comparing ALARM NMR to a glutathione-based fluorescence assay, as well as testing a collection of more than 3500 compounds containing HTS hits from 23 drug targets. The data show that current in silico filtering tools fail to identify more than half of the compounds that can act via reactive mechanisms. Significantly, we show how ALARM NMR data has been critical in identifying reactive compounds that would otherwise have been prioritized for lead optimization. In addition, a new filtering tool has been developed on the basis of the ALARM NMR data that can augment current in silico programs for identifying nuisance compounds and improving the process of hit triage.     

A new class of HIV-1 inhibitors and the target identification via proteomic profiling

Anti-HIV screening with the MT-4/MTT assay on a focused library of structurally diverse natural products has led to the discovery of a group of steroids with potent activities, which include four new ergostane-type steroids, named amotsterols A-D (1-4), together with two known analogs. Among them, the most potent amotsterol D (4) exhibited anti-HIV activity against wildtype and some clinically relevant multidrug resistant HIV-1 strains. Subsequent studies on its target identification through a proteomic approach found that compound 4 might target PKM2, a rate limiting enzyme of glycolysis, in host cells to restrict HIV replication. The docking model of compound 4 to PKM2 showed that the two hydroxyl groups of 4 form hydrogen bonds with the two parallel Y390 in each subunit of PKM2 separately, and the ring C of 4 is sandwiched between the two parallel aromatic rings of F26. The identified hit compound may have the potential to be further developed as a novel anti-HIV agent. These results demonstrated that an integrated approach, which combines new chemical structures and phenotypic screening with a proteomic approach, could not only identify novel HIV-1 inhibitors, but also elucidate the unknown targets of compound interactions in antiviral drug discovery.     

Chip-based high-throughput screening of herbal medicines

At present, high-throughput screening (HTS) programs in drug discovery rely mainly on compound libraries from combinational chemistry. Similarly, natural flora has been used as a prominent origin for new and potent herbal drugs. Herbal medicines have been used worldwide for thousands of years to cure many diseases. As such, herbal secondary metabolites show a remarkable structural diversity that supplements chemically synthesized compound analogs in drug discovery screening. Unfortunately, there is often a considerable deterioration in the quality of herbal drugs in such screening programs as there are time-consuming manual processes involved in the isolation of active ingredients from the highly complex mixtures of herbal plant products. The quality and quantity of herbal samples are critical for the success of HTS programs. In the recent past, there have been substantial improvements in HTS due to the miniaturization and integration of microchip (e.g., Herbochip(?), DNA chip, protein chip, cell chip, etc.)-based technologies so as to design herbal drugs that compete with synthetic drug analogs. Here we will review various technologies used for HTS of herbal medicines. Finally, we will summarize our efforts to develop a novel chip-based HTS assay to explore the antioxidant and radioprotective properties of herbal plants.     

多样性导向的“类天然产物”化合物库合成

天然产物是药物发现中先导化合物的重要来源.高通量筛选技术的发展和近年来化学生物学研究的深入,对拓展天然产物与活性相关的＂化学空间＂提出了新要求.用多样性导向合成方法建立骨架多样、构造复杂、立体化学多样性的＂类天然产物＂化合物库进行生物学相关研究,并以此为基础发现药物先导化合物正在成为一种趋势.在此过程中,发展具有立体选择性和区域选择性,能够广泛应用于多种底物的有机化学反应起着关键作用.