Pharmacogenetics in diverse ethnic populations--implications for drug discovery and development

It is widely acknowledged that the vast quantities of data now publicly available as a result of the human genome initiative have the potential to revolutionize the pharmaceutical industry. More tangibly to the drug development business, the dawn of the pharmacogenetics era has the potential to impact not only the discovery of new medicines but also the safety and efficacy of pharmaceutical agents. Coincident with these scientific advances is the emergence of new markets for pharmaceutical agents. Japan, which represents the world's second biggest market, is a good example. With the ICH E5 agreement in 1998 and a rapid change in the drug registration process in Japan, there are increasing opportunities to improve access to more medicines in all parts of the world. However, it is increasingly clear that significant genetic variation still exists between populations, with a host of data on interethnic variation in drug metabolizing enzyme and drug transporter activity. Evidence suggesting that this genetic variation may play an important role in defining some of the interethnic variation in drug response to currently marketed compounds is reviewed here, and future possibilities of using such information to better streamline the drug development process are discussed.     

The many roles of molecular complexity in drug discovery

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Small diverse antioxidant functionalities for oxidative stress disease drug discovery

There is an up-surge of interest in antioxidants because of their potential use in mitigating a wide array of oxidative stress mediated diseases. In the course of our literature search for diverse functional groups, with utility in the design of potential drugs for preventing oxidative stress related cell injury, we have collected a small literature library of core structures or moieties possessing antioxidant activities. These functional groups can be re-configured into robust antioxidants drug molecules, in their own right, or incorporated into drug structures where the antioxidant capability is required. The lack of single papers presenting a collection of diverse small molecule antioxidant moieties as potential design leads prompted us to write this short review of twenty five such functionalities.     

Biomarkers of carcinogenicity and their roles in drug discovery and development

The screening of drug candidates to assess their carcinogenic potential has long been a challenge for drug development. While genotoxic compounds can be readily detected with a battery of standard tests, including short-term in vitro and in vivo assays, predicting nongenotoxic carcinogenicity remains a major challenge. The 2-year rodent bioassay has been held as the gold standard for the assessment of carcinogenic risk to humans. However, due primarily to the continuing doubt over their relevance to human risk assessment, there has been an increased demand for more efficient and accurate approaches to predict and understand human relevant risk of carcinogenicity. Novel biomarkers have helped to shed light on our understanding of the factors that lead to and are characteristic of the carcinogenic phenotypes. Tissue biomarkers of carcinogenicity identified to be concordant with drug exposures resulting in tumor outcome may assist the drug development process by resolving ambiguities, shortening timelines and enabling earlier decisions on compounds. This information could vastly improve the efficiency with which nongenotoxic carcinogens are identified and ensure earlier insight into the relevance for humans.     

Novel roles for arrestins in G protein-coupled receptor biology and drug discovery

The G protein-coupled receptors (GPCRs) are the largest family of membrane proteins and represent some of the most important pharmaceutical targets. These receptors, encoded by several hundred genes, are activated by a wide variety of endogenous and synthetic ligands. The study of the signal transduction pathways activated by these receptors and the associated mechanisms controlling biological responses have been pivotal in identifying key intracellular molecules for regulating receptor responsiveness. The beta-arrestin proteins, which were initially discovered due to their role in GPCR desensitization, serve equally important roles in regulating internalization and alternative signaling events. This review focuses on the different functions of beta-arrestins to demonstrate how these proteins can help to identify new ligands for GPCRs and how they can serve as a platform for drug discovery.     

网络药理学:药物发现的新思想

新药研发是医药产业发展的核心驱动力,也是社会发展的重要需求,但近年来,随着对药物研发要求的不断提高,新药研发正面临着巨大困难,单靶点高选择性的新药研发思想遇到了挑战,已经显示出发展的局限性。网络药理学是近年来在单靶点药物研究的基础上提出的新药发现新策略。本文围绕网络药理学的形成基础和目前研究现状,探讨网络药理学发展的方向和应用前景,同时分析网络药理学的局限性和存在的问题,并通过与传统中医药学理论和中药复方有效成分组学的思想相比较,探讨网络药理学在新药研发中的应用。     

Effect of diverse datasets on the predictive capability of ADME models in drug discovery

Accurate methods of predicting drug absorption in humans early in the drug discovery process are becoming increasingly important in the drive to evaluate chemical candidates for their product potential faster and cheaper than traditional experimentally based methods. The prediction of drug absorption in humans is used here as an example to describe the unique requirements and advantages of appropriately designed datasets in developing predictive models to simulate in vivo response from in vitro inputs. This approach is being successfully implemented in other ADME areas to develop a series of models that will ultimately predict bioavailability using chemical structure inputs.     

High-throughput gene expression analysis for drug discovery

The ability to rapidly survey and compare gene expression levels between reference and test samples is moving the drug discovery process towards a more genomic orientation. The success of the Human Genome Project and related private genomics initiatives, combined with new technologies to probe, image and access expression data, are responsible for this transformation. This article reviews the history, status and future direction of high-throughput gene expression analysis. It describes classical approaches, explains the development of methods such as differential display for discovering novel genes, and discusses how microarray technology is exploiting collections of known sequences to pinpoint drug targets.     

Current trends in modern pharmaceutical analysis for drug discovery

Traditionally, pharmaceutical analysis referred to the chemical analysis of drug molecules. However, over the years, modern pharmaceutical analysis has evolved beyond this to encompass combination techniques, high-throughput technologies, chemometrics, microdosing studies, miniaturization and nanotechnology. These analytical advances are now being employed in all stages of drug discovery and the focus of this review will be on how these technologies are being employed within this process. With new, improved and evolving technologies, as well as new applications for existing technology, the search for new drugs for the prevention and treatment of human diseases continues.     

Systematic analysis of large screening sets in drug discovery

Each year large pharmaceutical companies produce massive amounts of primary screening data for lead discovery. To make better use of the vast amount of information in pharmaceutical databases, companies have begun to scrutinize the lead generation stage to ensure that more and better qualified lead series enter the downstream optimization and development stages. This article describes computational techniques for end to end analysis of large drug discovery screening sets. The analysis proceeds in three stages: In stage 1 the initial screening set is filtered to remove compounds that are unsuitable as lead compounds. In stage 2 local structural neighborhoods around active compound classes are identified, including similar but inactive compounds. In stage 3 the structure-activity relationships within local structural neighborhoods are analyzed. These processes are illustrated by analyzing two large, publicly available databases.     

A guide to drug discovery: Target selection in drug discovery

Target selection in drug discovery--defined here as the decision to focus on finding an agent with a particular biological action that is anticipated to have therapeutic utility--is influenced by a complex balance of scientific, medical and strategic considerations. In this article, we provide an introduction to the key issues in target selection and discuss the rationale for decision making.     

Chromatography and computational chemical analysis for drug discovery

Analytical chemists have increasingly turned their attention to drug discovery and drug analysis and to solve fundamental questions of biological significance in physiology and genetics. New technologies have been developed, and a variety of instruments have been redesigned for biomedical applications. The development of high-performance liquid chromatography (HPLC) opened a new era in biorelated fields and allowed faster separations of fragile macromolecules. Capillary column gas chromatography (GC)/mass spectrometry (MS) have been used to achieve more powerful separation and to perform structural analysis of molecules, and laboratory automation including robotics has become a powerful trend in both analysis and synthesis. Liquid chromatography (LC)/MS is more suitable for biomedical applications than GC/MS because almost all biomolecules are heat sensitive. Furthermore, a combination of various mass spectrometers has been used even for proteins directly. Improving the sensitivity of nuclear magnetic resonance spectrometry (NMR) has permitted a direct connection with LC. Purification of biomolecules on-line by LC has been performed since the development of chip-electrophoresis, On the other hand, computational chemical analysis is a promising technique given the advancing the hardware and software for use in chemical fields. In this review, a combination of chromatography and computational chemistry for use in drug discovery studies is described. Fast LC analysis using a column switching technique was introduced for aromatic amino acid metabolites and guanidino compounds. Recent developments in related technologies are also included from review papers.     

Hot-spot analysis for drug discovery targeting protein-protein interactions

Introduction: Protein-protein interactions are important for biological processes and pathological situations, and are attractive targets for drug discovery. However, rational drug design targeting protein-protein interactions is still highly challenging. Hot-spot residues are seen as the best option to target such interactions, but their identification requires detailed structural and energetic characterization, which is only available for a tiny fraction of protein interactions.

Areas covered: In this review, the authors cover a variety of computational methods that have been reported for the energetic analysis of protein-protein interfaces in search of hot-spots, and the structural modeling of protein-protein complexes by docking. This can help to rationalize the discovery of small-molecule inhibitors of protein-protein interfaces of therapeutic interest. Computational analysis and docking can help to locate the interface, molecular dynamics can be used to find suitable cavities, and hot-spot predictions can focus the search for inhibitors of protein-protein interactions.

Expert opinion: A major difficulty for applying rational drug design methods to protein-protein interactions is that in the majority of cases the complex structure is not available. Fortunately, computational docking can complement experimental data. An interesting aspect to explore in the future is the integration of these strategies for targeting PPIs with large-scale mutational analysis.     

Lipophilicity in drug discovery

Importance of the field: The role of lipophilicity in determining the overall quality of candidate drug molecules is of paramount importance. Recent developments suggest that, as well as determining pre-clinical ADMET (absorption, distribution, metabolism, elimination and toxicology) properties, compounds of optimal lipophilicity might have increased chances of success in development.

Areas covered in this review: The review covers aspects of methods of prediction of lipophilicity in frequent use and describes the most relevant literature analyses linking individual ADMET parameters and more composite measures of overall compound ‘quality’ with lipophilicity.

What the reader will gain: The aim is to provide an overview of the relevant literature in an attempt to summarise where the optimum region of lipophilicity lies and to highlight which particular issues and risks might be expected when operating outside this region.

Take home message: The review of the data shows that this optimal space is defined by a narrow range of logD between ～ 1 and 3. Some of the implications of this for medicinal chemistry optimisation are discussed.     

Chronicles in drug discovery

Chronicles in Drug Discovery is a series of brief reports on timely topics in the field of drug R&D. This month's chronicles contain the following reports: Targeting DNA repair enzymes instead of viral proteins provides a great advantage in preventing the emergence of resistant mutants. A striking increase in therapeutic approaches for the treatment of IBD has been fueled by an improved understanding of the mechanisms that underlie its pathophysiology. Peptide deformylase inhibitors are under active investigation for bacterial infections and cancer treatment. Dopamine D3 receptors present an attractive target for alcoholism therapy since they are involved in the mechanisms of alcohol dependency and abuse.     

Chronicles in drug discovery

Chronicles in Drug Discovery features special interest reports on advances in drug discovery. This month we highlight agents that target and deplete immunosuppressive regulatory T cells, which are produced by tumor cells to hinder innate immunity against, or chemotherapies targeting, tumor-associated antigens. Antiviral treatments for respiratory syncytial virus, a severe and prevalent infection in children, are limited due to their side effect profiles and cost. New strategies currently under clinical development include monoclonal antibodies, siRNAs, vaccines and oral small molecule inhibitors. Recent therapeutic lines for Huntington's disease include gene therapies that target the mutated human huntingtin gene or deliver neuroprotective growth factors and cellular transplantation in apoptotic regions of the brain. Finally, we highlight the antiinflammatory and antinociceptive properties of new compounds targeting the somatostatin receptor subtype sst4, which warrant further study for their potential application as clinical analgesics.     

Chronicles in drug discovery

Chronicles in Drug Discovery features special interest reports on advances in drug discovery. This month we highlight new options to prevent oral mucositis, a treatment-limiting adverse effect of chemotherapy. Studies are currently focusing on mechanism-based therapies to prevent or repair DNA damage to epithelial and submucosal cells and the cascade or events that follow to cause tissue damage or analgesics to ease the associated oral cavity pain. Therapeutic limitations also exist for the use of the highly effective antibiotic gentamicin, as it evokes acute renal failure. Mechanistic investigations have shed some light on potential targets: the kallikreins, peroxynitrite-related pathways, superoxide production and the accumulation of aminoglycosides. New antibiotic strategies for trachoma, the leading cause of preventable blindness, are also explored along with studies to aid the development of vaccine candidates. Finally, we discuss the utility of allosteric-potentiating ligands to modulate nicotinic acetylcholine receptors, mimicking the reward/addictive effects of nicotine, as potential strategies for smoking cessation.