Combinatorial Chemistry & High Throughput Screening - Volume 11, Issue 3, 2008

The last two decades have seen the rapid and extensive adoption of an increasingly diverse portfolio of automated high throughput technologies by the pharmaceutical and biotechnology industries. Such approaches are now established as a ubiquitous and integral component of modern drug discovery. From the inception of high throughput screening up until the early 90s', such techniques were predominantly applied to facilitate rapid high volume evaluation of low molecular weight chemical libraries. These early screening campaigns were performed primarily by the pharmaceutical industry with the goal of identifying small molecule modulators for novel drug targets. Today the preponderance of chemical drug leads are derived from high throughput screening, the success of which has resulted in over a hundred candidates in clinical trials or approved for marketing. At the beginning of the new millennium, sequencing of the human genome marked the beginning of what has popularly been termed the “genomic revolution”. High throughput technologies were enthusiastically adopted by biotechnology companies and applied to many aspects of modern biomedical research enabling systematic research endeavors on a scale not previously possible. Notable examples include expansive campaigns to sequence genomes or ESTs, automated gene expression profiling programs and protein/protein interaction mapping projects etc. This new target discovery paradigm generated many potential drug targets, which in turn needed to be screened against compound libraries to identify new drug candidates. In consequence, the demand for more, better, faster, more flexible and cost-effective technologies grew and was eagerly addressed by an ever growing field of equipment manufacturers and service companies. These new machines increasingly opened the world of high throughput research to ever more scientists across a broadening and increasingly diverse catalogue of disciplines. Consequently, high throughput approaches are no longer limited to industry, as they largely were in the early days; many academic institutions have established screening and technology centers. In addition, the application of high throughput techniques has expanded far beyond pharmaceutical and genomics laboratories and is revolutionizing all aspects of biology and drug discovery. Inevitably, new opportunities have brought new challenges. In particular, the enormous quantity of data now being routinely generated has driven the rapid development of new data capture, analysis and storage capabilities. This has been, and remains, critical in overcoming persistent limitations in the timely and effective utilization of the new data. This special issue of Combinatorial Chemistry & High Throughput Screening was conceived with the objective of bringing together leading scientists from diverse fields to give a broad overview of the impact of modern high throughput approaches on the whole process of drug discovery from target identification to lead identification and lead optimization.

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.

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.

GPCRs had significant representation in the drug discovery portfolios of most major commercial drug discovery organizations for many years. This is due in part to the diverse biological roles mediated by GPCRs as a class, as well as the empirical discovery that they have proven relatively tractable to the development of small molecule therapeutics. Publication of the human genome sequence in 2001 confirmed GPCRs as the largest single gene superfamily with more than 700 members, furthering the already strong appeal of addressing this target class using efficient and highly parallelized platform approaches. The GPCR research platform implemented at Amgen is used as a case study to review the evolution and implementation of available assays and technologies applicable to GPCR drug discovery. The strengths, weaknesses, and applications of assay technologies applicable to Gαs, Gαi and Gαq-coupled receptors are described and their relative merits evaluated. Particular consideration is made of the role and practice of “de-orphaning” and signaling pathway characterization as a pre-requisite to establishing effective screens. In silico and in vitro methodology developed for rapid, parallel high throughput hit characterization and prioritization is also discussed extensively.

High-Content Analysis (HCA) has developed into an established tool and is used in a wide range of academic laboratories and pharmaceutical research groups. HCA is now routinely proving to be effective in providing functionally relevant results. It is essential to select the appropriate HCA application with regard to the targeted compound's cellular function. The cellular impact and compound specificity as revealed by HCA analysis facilitates reaching definitive conclusions at an early stage in the drug discovery process. This technology therefore has the potential to substantially improve the efficiency of pharmaceutical research. Recent advances in fluorescent probes have significantly boosted the success of HCA. Auto-fluorescent proteins which minimally hinder the functioning of the living cell have been playing a decisive role in cell biology research. For companies the severely restricted license conditions regarding auto-fluorescent proteins hamper their general use in pharmaceutical research. This has opened the field for other solutions such as selflabeling protein technology, which could potentially replace the well established methods that utilize auto-fluorescent proteins. In addition, direct labeling techniques have improved considerably and may supersede many of the approaches based on fusion proteins. Following sample preparation, treated cells are imaged and the resulting multiple fluorescent signals are subjected to contextual and statistical analysis. The extraordinary advantage of HCA is that it enables the large-scale and simultaneous quantification and correlation of multiple phenotypic responses and physiological reactions using sophisticated software solutions that permit assay-specific image analysis. Hence, HCA once more has demonstrated its outstanding potential to significantly support establishing effective pharmaceutical research processes in order to both advance research projects and cut costs.

Small molecule high-throughput screening in drug discovery today is dominated by techniques which are dependent upon artificial labels or reporter systems. While effective, these approaches can be affected by certain experimental limitations, such as conformational restrictions imposed by the selected label or compound fluorescence/quenching. Label-free approaches potentially address many of these issues by allowing researchers to investigate more native systems without fluorescence- or luminescence-based readouts. However, due to throughput and expense constraints, label-free methods have been largely relegated to a supporting role as the basis of secondary assays. In this review, we describe recent improvements in impedance-based, optical biosensor-based, automated patch clamp and mass spectrometry technologies that have enhanced their ease of use and throughput and, hence, their utility for primary screening of small- to medium-sized compound libraries. The ultimate maturation of these techniques will enable drug discovery researchers to screen large chemical libraries against minimally manipulated biological systems.

High throughput screening (HTS) for complex diseases is challenging. This stems from the fact that complex phenotypes are difficult to adapt to rapid, high throughput assays. We describe the recent development of high throughput and high-content screens (HCS) for neurodegenerative diseases, with a focus on inherited neurodegenerative disorders, such as Huntington's disease. We describe, among others, HTS assays based on protein aggregation, neuronal death, caspase activation and mutant protein clearance. Furthermore, we describe high-content screens that are being used to prioritize hits identified in such HTS assays. These assays and screening approaches should accelerate drug discovery for neurodegenerative disorders and guide the development of screening approaches for other complex disease phenotypes.

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.

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.

Dr. Holger Wesche is a Principal Scientist at Amgen Inc. in South San Francisco (formerly Tularik), where he has been working for the past 10 years. His group is involved in the identification and validation of novel targets for pharmaceutical intervention. Dr. Wesche's lab also works on assay development for HTS and SAR support for development candidates. His research focus is the mechanism of signal transduction and gene regulation in inflammation and cancer. Dr. Wesche received his Ph.D. in Biochemistry and Immunology in 1997 from the University of Hannover, Germany. Dr. Shou-Hua (Josh) Xiao has worked in the biotech industry for about 10 years in drug discovery. He is currently Principal Scientist, leading the assay development and HTS group in the Lead Discovery Department of Amgen, San Francisco. His responsibility and experiences include assay development and high throughput screening for GPCRs, protein kinases and other classes of enzymes and mechanistic enzymology. His group has also set up high throughput eADME assays and hERG profiling. Previously in 2003, Dr. Xiao joined Tularik (acquired by Amgen in 2004) in similar role. Prior to joining Tularik, Dr. Xiao had worked at Millennium Pharmaceuticals for five years, also in Lead Discovery, where he and his group established a very effective substrate ID platform for novel protein kinase targets from functional genomics. Dr. Xiao obtained his Ph.D. degree in Biochemistry from Louisiana State University and conducted his postdoctoral research with Dr. James Manley at Columbia University, New York. Dr. Steve Young is an Executive Director at Amgen Inc. where he heads up the Lead Discovery organization. After working at the South San Francisco site for 5 years, he is currently based in Seattle where he is engaged in establishing an HTS laboratory at Amgen's Washington facility. His research interests revolve around the application of high throughput technologies to Drug Discovery. In recent years, the work of his research team has increasingly expanded from an historic focus on High Throughput Screening to include the implementation of genomics based technologies in target discovery and validation. Dr. Young received his Ph.D. in Biochemistry in 1994 from the University of Bristol, U.K. for research into Insulin Receptor Mediated Signal Transduction.