Evolving cryo-EM structural approaches for GPCR drug discovery

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Genomic approaches to drug discovery

Considerable progress has been made in exploiting the enormous amount of genomic and genetic information for the identification of potential targets for drug discovery and development. New tools that incorporate pathway information have been developed for gene expression data mining to reflect differences in pathways in normal and disease states. In addition, forward and reverse genetics used in a high-throughput mode with full-length cDNA and RNAi libraries enable the direct identification of components of signaling pathways. The discovery of the regulatory function of microRNAs highlights the importance of continuing the investigation of the genome with sophisticated tools. Furthermore, epigenetic information including DNA methylation and histone modifications that mediate important biological processes add to the possibilities to identify novel drug targets and patient populations that will benefit from new therapies.     

New approaches to antidepressant drug discovery: beyond monoamines

All available antidepressant medications are based on serendipitous discoveries of the clinical efficacy of two classes of antidepressants more than 50 years ago. These tricyclic and monoamine oxidase inhibitor antidepressants were subsequently found to promote serotonin or noradrenaline function in the brain. Newer agents are more specific but have the same core mechanisms of action in promoting these monoamine neurotransmitters. This is unfortunate, because only approximately 50% of individuals with depression show full remission in response to these mechanisms. This review summarizes the obstacles that have hindered the development of non-monoamine-based antidepressants, and provides a progress report on some of the most promising current strategies.     

Innovative approaches to novel antibacterial drug discovery

Increasing antibiotic resistance in microorganisms and new emerging pathogens have become a major problem in our society. Rising to satisfy this urgent medical need is a recent confluence of powerful new drug discovery technologies: combinatorial chemistry; sequence and functional genomic analysis; and novel methods of high-throughput screening. The combination of these technologies will bring to bear untapped power in the search for new antimicrobials.     

Modern approaches to drug discovery and design: setting the scene

The raison d'ítre for the drug discovery and development process is to provide safe and effective treatments for diseases. Bringing a new drug to market, however, is a time-consuming and expensive process and it remains an imperative for drug companies that they identify ways in which they can accelerate the identification of potential targets and their screening and development in order to maintain a competitive edge. Successful drug discovery efforts include biochemical, biophysical, genetic and immunological approaches, targeting such processes as signal transduction, cell cycle control, apoptosis, gene regulation and metastasis. As the number of these biological targets increases, reliance on bioinformatics and chemoinformatics to improve decision making, by identifying characteristics of successful drugs and sharing knowledge gained within the scientific community, has become a burgeoning area in the post-genomic era of drug discovery.     

Computational chemistry approaches to drug discovery in signal transduction

The advent of therapeutic strategies aimed at targeting specific macromolecular components of deregulated signaling pathways associated with particular disease states has given rise to the idea that it should be possible to design ligands as drug candidates to these targets from first principles. This concept has been beckoning for a long time but structure-based ligand design only became feasible once it was possible to determine the 3-D structures of molecular targets at atomic resolution. However, structure-based design turned out to be difficult, chiefly because under physiological conditions both receptors and ligands are not static but they behave dynamically. While it is possible to design ligands with high steric and electronic complementarity to a receptor site, it is always uncertain how biologically relevant the assumed conformations of both ligand and receptor actually are. The fact that it remains beyond our current abilities to predict with sufficient accuracy the affinity between hypothetical ligand and receptor poses is in part connected with this problem and continues to confound the reliable prediction of drug-like ligands for therapeutic targets. Nevertheless, significant progress has been made and so-called virtual screening methods that use computational methods to dock candidate ligands into receptor sites and to score the resulting complexes are now used routinely as one of the components in drug discovery screening campaigns. Here an overview is given of the underlying principles, implementations, and applications of structure-guided computational design technologies. Although the emphasis is on receptor-based strategies, mention will also be made of some of the more established ligand-based approaches, such as similarity analyses and quantitative structure-activity relationship methods.     

Bioinformatics approaches for new drug discovery: a review

Prolonged antibiotic therapy for the bacterial infections has resulted in high levels of antibiotic resistance. Initially, bacteria are susceptible to the antibiotics, but can gradually develop resistance. Treating such drug-resistant bacteria remains difficult or even impossible. Hence, there is a need to develop effective drugs against bacterial pathogens. The drug discovery process is time-consuming, expensive and laborious. The traditionally available drug discovery process initiates with the identification of target as well as the most promising drug molecule, followed by the optimization of this, in-vitro, in-vivo and in pre-clinical studies to decide whether the compound has the potential to be developed as a drug molecule. Drug discovery, drug development and commercialization are complicated processes. To overcome some of these problems, there are many computational tools available for new drug discovery, which could be cost effective and less time-consuming. In-silico approaches can reduce the number of potential compounds from hundreds of thousands to the tens of thousands which could be studied for drug discovery and this results in savings of time, money and human resources. Our review is on the various computational methods employed in new drug discovery processes.     

Progress in functional genomics approaches to antifungal drug target discovery

Antifungal drug discovery is starting to benefit from the enormous advances in the genomics field, which have occurred in the past decade. As traditional drug screening on existing targets is not delivering the long-awaited potent antifungals, efforts to use novel genetics and genomics-based strategies to aid in the discovery of novel drug targets are gaining increased importance. The current paradigm in antifungal drug target discovery focuses on basically two main classes of targets to evaluate: genes essential for viability and virulence or pathogenicity factors. Here we report on recent advances in genetics and genomics-based technologies that will allow us not only to identify and validate novel fungal drug targets, but hopefully in the longer run also to discover potent novel therapeutic agents. Fungal pathogens have typically presented significant obstacles when subjected to genetics, but the creativity of scientists in the anti-infectives field and the cross-talk with scientists in other areas is now yielding exciting new tools and technologies to tackle the problem of finding potent, specific and non-toxic antifungal therapeutics.     

GPCRs: Emerging anti-cancer drug targets

G protein-coupled receptors (GPCRs) constitute the largest and most diverse protein family in the human genome with over 800 members identified to date. They play critical roles in numerous cellular and physiological processes, including cell proliferation, differentiation, neurotransmission, development and apoptosis. Consequently, aberrant receptor activity has been demonstrated in numerous disorders/diseases, and as a result GPCRs have become the most successful drug target class in pharmaceuticals treating a wide variety of indications such as pain, inflammation, neurobiological and metabolic disorders. Many independent studies have also demonstrated a key role for GPCRs in tumourigenesis, establishing their involvement in cancer initiation, progression, and metastasis. Given the growing appreciation of the role(s) that GPCRs play in cancer pathogenesis, it is surprising to note that very few GPCRs have been effectively exploited in pursuit of anti-cancer therapies. The present review provides a broad overview of the roles that various GPCRs play in cancer growth and development, highlighting the potential of pharmacologically modulating these receptors for the development of novel anti-cancer therapeutics.     

Synaptic plasticity and neuropathology: new approaches in drug discovery

Neuronal plasticity is now known to be very important in the adult, both in the formation of new synaptic connections and of new neurones (neurogenesis) and of glial cells. However, old age and stress can inhibit this plasticity and lead to cerebral atrophy. The time course of changes in neuronal plasticity involves, in the first milliseconds to seconds, changes in synaptic strength (long term potentialisation, LTP, or long term depression, LTD), then, over minutes to hours, changes in the number of synaptic connections (linked to changes in neurotrophic factors), and over weeks to months, to changes in neuronal reconfiguration. These changes in brain systems are particularly targeted in psychiatric disorders to the areas which are sensitive to stress and play roles in memory and emotion (hippocampus, amygdala and prefrontal cortex). The discovery and development of drugs modifying neuronal plasticity and neurotrophins production has been a priority for Servier research for the last ten years; Servier has a clinically effective antidepressant, tianeptine (Stablon), with a favourable side effect profile, but which does not inhibit the uptake of serotonin, or other monoamines. However, this drug can reverse the deleterious effects of stress on neuronal plasticity, thereby acting on the causes of psychiatric disorders. Furthermore, a new research area is being investigated - facilitation of AMPA receptors, favouring the production of neurotrophic factors.     

Fragment-based approaches in drug discovery and chemical biology

Fragment-based approaches to finding novel small molecules that bind to proteins are now firmly established in drug discovery and chemical biology. Initially developed primarily in a few centers in the biotech and pharma industry, this methodology has now been adopted widely in both the pharmaceutical industry and academia. After the initial success with kinase targets, the versatility of this approach has now expanded to a broad range of different protein classes. Herein we describe recent fragment-based approaches to a wide range of target types, including Hsp90, β-secretase, and allosteric sites in human immunodeficiency virus protease and fanesyl pyrophosphate synthase. The role of fragment-based approaches in an academic research environment is also examined with an emphasis on neglected diseases such as tuberculosis. The development of a fragment library, the fragment screening process, and the subsequent fragment hit elaboration will be discussed using examples from the literature.     

Novel and revisited approaches in antituberculosis drug discovery

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Image source (SEM of Mtb): NIAID.