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Taurine is one of the most abundant amino acids in mammalian tissues. It is obtained from the diet and by de novo synthesis, from cysteic acid or hypotaurine. Despite the discovery in 1954 that the oxygenation of hypotaurine produces taurine, the identification of an enzyme catalyzing this reaction has remained elusive. In large part this is due to the incorrect assignment, in 1962, of the enzyme as a NAD-dependent hypotaurine dehydrogenase. For more than 55 years the literature has continued to refer to this enzyme as such. Here we show, both in vivo and in vitro, that the enzyme that oxygenates hypotaurine to produce taurine is flavin-containing monooxygenase 1 (FMO1). Metabolite analysis of the urine of Fmo1-null mice by 1H NMR spectroscopy revealed a build-up of hypotaurine and a deficit of taurine in comparison with the concentrations of these compounds in the urine of wild-type mice. In vitro assays confirmed that FMO1 of human catalyzes the conversion of hypotaurine to taurine utilizing either NADPH or NADH as co-factor. FMO1 has a wide substrate range and is best known as a xenobiotic- or drug-metabolizing enzyme. The identification that the endogenous molecule hypotaurine is a substrate for the FMO1-catalyzed production of taurine resolves a long-standing mystery. This finding should help establish the role FMO1 plays in a range of biological processes in which taurine or its deficiency is implicated, including conjugation of bile acids, neurotransmitter, anti-oxidant and anti-inflammatory functions, the pathogenesis of obesity and skeletal muscle disorders.

Introduction.\ud The contraction in pharmaceutical drug discovery operations in the past decade has been counter-balanced by a significant rise in the number of academic drug discovery groups. In addition, pharmaceutical companies that used to operate in completely independent, vertically-integrated operations for drug discovery are now collaborating more with each other, and with academic groups. We are in a new era of drug discovery.\ud \ud Areas Covered. \ud This review provides an overview of the current status of academic drug discovery groups, their achievements and the challenges they face,, together with perspectives on ways to achieve improved outcomes.\ud \ud Expert Opinion. \ud Academic groups have made important contributions to drug discovery, from its earliest days and continue to do so today. However, modern drug discovery and development is exceedingly complex, and has high failure rates, principally because human biology is complex and poorly understood. Academic drug discovery groups need to play to their strengths and not just copy what has gone before. However, there are lessons to be learnt from the experiences of the industrial drug discoverers and four areas are highlighted for attention: (i) increased validation of targets, (ii) elimination of false hits from HTS, (iii) increasing the quality of molecular probes and (iv) investing in a high quality informatics infrastructure.

Pharmacogenomics is now over 50 years old and has had some impact in clinical practice, through its use to select patient subgroups who will enjoy efficacy without side effects when treated with certain drugs. However, pharmacogenomics, has had less impact than initially predicted. One reason for this is that many diseases, and the way in which the patients respond to drug treatments, have both genetic and environmental elements. Pure genomics is almost blind to the environmental elements. A new methodology has emerged, termed pharmacometabonomics that is concerned with the prediction of drug effects through the analysis of predose, biofluid metabolite profiles, which reflect both genetic and environmental influences on human physiology. In this review we will cover what pharmacometabonomics is, how it works, what applications exist and what the future might hold in this exciting new area.

Variable patient responses to drugs are a key issue for medicine and for drug discovery and development. Personalized medicine, that is the selection of medicines for subgroups of patients so as to maximize drug efficacy and minimize toxicity, is a key goal of twenty-first century healthcare. Currently, most personalized medicine paradigms rely on clinical judgment based on the patient's history, and on the analysis of the patients' genome to predict drug effects i.e., pharmacogenomics. However, variability in patient responses to drugs is dependent upon many environmental factors to which human genomics is essentially blind. A new paradigm for predicting drug responses based on individual pre-dose metabolite profiles has emerged in the past decade: pharmacometabonomics, which is defined as “the prediction of the outcome (for example, efficacy or toxicity) of a drug or xenobiotic intervention in an individual based on a mathematical model of pre-intervention metabolite signatures.” The new pharmacometabonomics paradigm is complementary to pharmacogenomics but has the advantage of being sensitive to environmental as well as genomic factors. This review will chart the discovery and development of pharmacometabonomics, and provide examples of its current utility and possible future developments.

NMR spectroscopy has been a technology of fundamental importance to drug discovery and development for the past 40–50 years, principally through its use in the structure elucidation of leads, drugs, their synthetic intermediates, and the degradation products and impurities of those drug molecules. In the past 30 years, another major area of application of NMR spectroscopy has been metabolic profiling or metabonomics studies of drug metabolism, drug safety, drug efficacy, and disease, through studies of biological fluids such as urine and plasma, representing a change in application from the chemical to the biological sciences. This trend has continued with significant progress in the application of in vivo MRI and magnetic resonance spectroscopy (MRS) to the study of disease states and their treatment in patients and in animal models. More recently, new applications of NMR spectroscopy have emerged such as hit-finding and hit-to-lead optimization, impacting directly on these early stages of the drug discovery process. Finally, the discovery of completely new areas, led by NMR spectroscopy, such as pharmacometabonomics, holds out the promise of improvements in personalized medicine in the future. This article will briefly cover all of these areas, and more, as a prelude to more detailed treatments in the following articles of this work.

High Throughput Screening (HTS) is a successful strategy for finding hits and leads that have the opportunity to be converted into drugs. In this paper we highlight novel computational methods used to select compounds to build a new screening file at Pfizer and the analytical methods we used to assess their quality. We also introduce the novel concept of molecular redundancy to help decide on the density of compounds required in any region of chemical space in order to be confident of running successful HTS campaigns.