Fragment-based drug discovery (FBDD) has become established in both industry and academia as an alternative approach to high-throughput screening for the generation of chemical leads for drug targets. In FBDD, specialised detection methods are used to identify small chemical compounds (fragments) that bind to the drug target, and structural biology is usually employed to establish their binding mode and to facilitate their optimisation. In this article, we present three recent and successful case histories in FBDD. We then re-examine the key concepts and challenges of FBDD with particular emphasis on recent literature and our own experience from a substantial number of FBDD applications. Our opinion is that careful application of FBDD is living up to its promise of delivering high quality leads with good physical properties and that in future many drug molecules will be derived from fragment-based approaches.
Conditioned place preference (CPP) is a learned behavior shown in many vertebrates, including humans. CPP occurs when a subject comes to prefer one place more than others because the preferred location has been paired previously with rewarding events. The CPP paradigm is widely used to explore the reinforcing effects of natural and pharmacological stimuli, including drugs of addiction. There is a general assumption that an acquired place preference is based on classical conditioning derived ‘incentive motivation’. However, this may be an oversimplification of the multiple learning processes involved. We argue that although CPP may appear as an incentive-driven behavior related to secondary reinforcers, it may also be a result of operant conditioning of behavior prevailing at the conditioning site, as well as a result of conditioned treatment effects. Here, we outline alternative explanations for an observed CPP, which may fundamentally affect the interpretation of results with this paradigm in its use as a screening tool for rewarding properties of treatments.
Drug repositioning is an innovation stream of pharmaceutical development that offers advantages for drug developers along with safer medicines for patients. Several drugs have been successfully repositioned to a new indication, with the most prominent of them being viagra and thalidomide, which have generated historically high revenues. In line with these developments, most of the recent articles and reviews on repositioning are focused on success stories, leaving behind the challenges that repositioned compounds have on the way to the clinic. Here, I analyze repositioning as a business opportunity for pharmaceutical companies, weighing both challenges and opportunities of repositioning. In addition, I suggest extended profiling as a lower-risk cost-effective repositioning model for pharmaceutical companies and elucidate the novel collaborative business opportunities that help to realize repositioning of shelved and marketed compounds.
Carbonic anhydrase isoform IX (CA IX) is highly overexpressed in many types of cancer. Its expression, which is regulated by the HIF-1 transcription factor, is strongly induced by hypoxia and correlates with a poor response to classical chemo- and radiotherapies. CA IX contributes to acidification of the tumor environment by efficiently catalyzing the hydration of carbon dioxide to bicarbonate and protons, thereby leading to acquisition of metastasic phenotypes and chemoresistance to weakly basic anticancer drugs. Inhibition of this enzymatic activity by specific inhibitors, such as the sulfonamide indisulam, reverts these processes, establishing a clear-cut role for CA IX in tumorigenesis. Thus, selective CA IX inhibitors could prove useful for elucidating the role of CA IX in hypoxic cancers, for controlling the pH imbalance in tumor cells and for developing diagnostic or therapeutic applications for tumor management. Indeed, fluorescent inhibitors and membrane-impermeant sulfonamides have recently been used as proof-of-concept tools, demonstrating that CA IX is an interesting target for anticancer drug development.
Allosteric drugs are increasingly used because they produce fewer side effects. Allosteric signal propagation does not stop at the ‘end’ of a protein, but may be dynamically transmitted across the cell. We propose here that the concept of allosteric drugs can be broadened to ‘allo-network drugs’ – whose effects can propagate either within a protein, or across several proteins, to enhance or inhibit specific interactions along a pathway. We posit that current allosteric drugs are a special case of allo-network drugs, and suggest that allo-network drugs can achieve specific, limited changes at the systems level, and in this way can achieve fewer side effects and lower toxicity. Finally, we propose steps and methods to identify allo-network drug targets and sites that outline a new paradigm in systems-based drug design.
The pursuit for drugs that inhibit cyclin-dependent kinases (CDKs) has been an intense area of research for more than 15 years. The first-generation inhibitors, Flavopiridol and CY-202, are in late-stage clinical trials, but so far have demonstrated only modest activity. Several second-generation inhibitors are now in clinical trials. Future approaches to determine clinical benefit need to incorporate both the lessons learned from these early compounds and information recently obtained from the genetic analysis of CDKs in preclinical models. Here we discuss key concepts that should be considered when validating the clinical utility of CDK inhibitors in cancer therapy.
Multidrug and toxic compound extrusion (MATE) proteins, comprising the most recently designated family of multidrug transporter proteins, are widely distributed in all kingdoms of living organisms, although their function is far from understood. The bacterial MATE-type transporters that have been characterized function as exporters of cationic drugs, such as norfloxacin and ethidium, through H or Na exchange. Plant MATE-type transporters are involved in the detoxification of secondary metabolites, including alkaloids. Mammalian MATE-type transporters are responsible for the final step in the excretion of metabolic waste and xenobiotic organic cations in the kidney and liver through electroneutral exchange of H . Thus, we propose that members of the MATE family are organic cation exporters that excrete metabolic or xenobiotic organic cations from the body.
Highlights • Heat shock factor (Hsf)1 and nuclear factor-erythroid 2 p45-related factor (Nrf)2 orchestrate comprehensive cytoprotective transcriptional programs. • Hsf1 and Nrf2 control overlapping target genes and may compensate for each other. • Activation of Hsf1 and Nrf2 promotes reducing cellular environment. • Lack of Hsf1 or Nrf2 is associated with impaired mitochondrial function.
MicroRNAs (miRNAs) are small noncoding RNAs that regulate gene expression at the post-transcriptional level by either degradation or translational repression of a target mRNA. More than 400 miRNAs have been identified in the human genome, but the relevance of most of them to physiological and pathological processes remains unclear. Although downregulation of the miRNA-processing enzymes Dicer and Drosha is known to impair angiogenesis, only a few specific miRNAs targeting endothelial cell function and angiogenesis have been identified. miR-221 and miR-222 block endothelial cell migration, proliferation and angiogenesis in vitro by targeting the stem cell factor receptor c-Kit and indirectly regulating expression of endothelial nitric oxide synthase. A pro-angiogenic function has been established for the miR-17-92 cluster, which promotes tumor angiogenesis in vivo . Expression of let7-f and miR-27b contributes to in vitro angiogenesis. We review recent studies on the involvement of miRNA in angiogenesis and discuss their implications for miRNA-based therapeutic strategies targeting this process in disease.
Highlights • Many relevant resources from systems biology and pharmacology can be combined into a general map. • Data from the resources can be converted into networks, gene-set libraries, and bipartite graphs. • Indirect relationships (e.g., matching drugs to patients) can be identified by data integration. • Combining independent sources can be used to validate computational and experimental methods. • Predictions can be improved when two independent networks are used to predict a third network.