Opioid receptor interactions: local and nonlocal,symmetric and asymmetric,physical and functional

The pharmacological effects of opioid drugs and endogenous opioid peptides are mediated by several kinds of receptors, the major ones being mu, delta and kappa. Though classically it has been thought that a particular effect mediated by a drug or other ligand results from its interaction with a single type of receptor, accumulating evidence demonstrates that interactions between receptors play a major role in opioid actions. These interactions may be either local, involving receptors within the same tissue, or nonlocal, between receptors located in different tissues. Nonlocal interactions always involve intercellular mechanisms, whereas local interactions may involve either intercellular or intracellular interactions, the latter including physical association of receptors. Both local and nonlocal interactions, moreover, may be either symmetric, with ligand interaction at one receptor affecting interaction at the other, or asymmetric; and either potentiating or inhibitory. In this article we discuss major examples of these kinds of interactions, and their role in the acute and chronic effects of opioids. Knowledge of these interactions may have important implications for the design of opioids with more specific actions, and for eliminating the addictive liability of these drugs.     

Recognizing and reporting adverse drug reactions.

Although physicians in practice are most likely to see patients with adverse drug reactions, they may fail to recognize an adverse effect or to attribute it to a drug effect and, when recognized, they may fail to report serious reactions to the US Food and Drug Administration (FDA). To recognize and attribute an adverse event to a drug effect, physicians should review the patient''s clinical course, looking at patient risk factors, the known adverse reactions to the suspected drug, and the likelihood of a causal relationship between the drug and the adverse event-based on the temporal relationship, response to stopping or restarting the drug, and whether other factors could explain the reaction. Once an adverse drug reaction has been identified, the patient should be informed and appropriate documentation made in the patient''s medical record. Serious known reactions and all reactions to newly released drugs or those not previously known to occur (even if the certainty is low) should be reported to the FDA.     

The application of solid-state NMR spectroscopy to study candesartan cilexetil (TCV-116) membrane interactions. Comparative study with the AT1R antagonist drug olmesartan

ΑΤ1 receptor (AT1R) antagonists exert their antihypertensive effects by preventing the vasoconstrictive hormone AngII to bind to the AT1 receptor. It has been proposed that these biological effects are mediated through a two-step mechanism reaction. In the first step, they are incorporated in the core of the lipid bilayers and in the second step they reach the active site of the receptor through lateral diffusion. In this model, drug/membrane interactions are key elements for the drugs achieving inhibition at the AT1 receptor. In this work, the interactions of the prodrug candesartan cilexetil (TCV-116) with lipid bilayers are studied at molecular detail. Solid-state ¹³C-CP/MAS, 2D ¹H-¹H NOESY NMR spectroscopy and in silico calculations are used. TCV-116 and olmesartan, another drug which acts as an AT1R antagonist are compared for their dynamic effects in lipid bilayers using solid-state ²H-NMR. We find a similar localization of TCV-116 compared to other AT1 antagonists in the intermediate polar region. In addition, we can identify specific local interactions. These interactions may be associated in part with the discrete pharmacological profiles observed for different antagonists.     

Cytochrome P450 Enzymes and Drug Metabolism—Basic Concepts and Methods of Assessment

1. The cytochrome P450 enzyme family is one of the major drug metabolizing systems in man.2. Factors such as age, gender, race, environment, and drug treatment may have considerable influence on the activity of these enzymes.3. There are now well-established in vitro techniques for assessing the role of specific cytochrome P450 enzymes in the metabolism of drugs, as well as the inhibitory or inducing effects of drugs on enzyme activity. In vitro data have been utilized to predict clinical outcomes (i.e., pharmacokinetic interactions), with close correlations between in vitro and in vivo data.4. This information can be of considerable practical assistance to clinicians, to help with rational prescribing or to prevent or minimize the potential for drug interactions.     

Systematic discovery of drug interaction mechanisms

Drug combinations are increasingly important in disease treatments, for combating drug resistance, and for elucidating fundamental relationships in cell physiology. When drugs are combined, their individual effects on cells may be amplified or weakened. Such drug interactions are crucial for treatment efficacy, but their underlying mechanisms remain largely unknown. To uncover the causes of drug interactions, we developed a systematic approach based on precise quantification of the individual and joint effects of antibiotics on growth of genome‐wide Escherichia coli gene deletion strains. We found that drug interactions between antibiotics representing the main modes of action are highly robust to genetic perturbation. This robustness is encapsulated in a general principle of bacterial growth, which enables the quantitative prediction of mutant growth rates under drug combinations. Rare violations of this principle exposed recurring cellular functions controlling drug interactions. In particular, we found that polysaccharide and ATP synthesis control multiple drug interactions with previously unexplained mechanisms, and small molecule adjuvants targeting these functions synthetically reshape drug interactions in predictable ways. These results provide a new conceptual framework for the design of multidrug combinations and suggest that there are universal mechanisms at the heart of most drug interactions.     

Topical Cream-Based Dosage Forms of the Macrocyclic Drug Delivery Vehicle Cucurbit[6]uril

The macrocycle family of molecules called cucurbit[n]urils are potential drug delivery vehicles as they are able to form host-guest complexes with many different classes of drugs. This study aimed to examine the utility of Cucurbit[6]uril (CB[6]) in topical cream-based formulations for either localised treatment or for transdermal delivery. Cucurbit[6]uril was formulated into both buffered cream aqueous- and oily cream-based dosage forms. The solid state interaction of CB[6] with other excipients was studied by differential scanning calorimetry and the macrocycle''s transdermal permeability was determined using rat skin. Significant solid state interactions were observed between CB[6] and the other dosage form excipients. At concentrations up to 32% w/w the buffered aqueous cream maintained its normal consistency and could be effectively applied to skin, but the oily cream was too stiff and is not suitable as a dosage form. Cucurbit[6]uril does not permeate through skin; as such, the results imply that cucurbituril-based topical creams may potentially only have applications for localised skin treatment and not for transdermal drug delivery.     

Efflux transporters- and cytochrome P-450-mediated interactions between drugs of abuse and antiretrovirals

Multidrug regimens and corresponding drug interactions cause many adverse reactions and treatment failures. Drug efflux transporters: P-gp, MRP, BCRP in conjunction with metabolizing enzymes (CYPs) are major factors in such interactions. Most effective combination antiretrovirals (ARV) therapy includes a PI or a NNRTI or two NRTI. Coadministration of such ARV may induce efflux transporters and/or CYP3A4 resulting in sub-therapeutic blood levels and therapeutic failure due to reduced absorption and/or increased metabolism. A similar prognosis is true for ARV-compounds and drugs of abuse combinations. Morphine and nicotine enhance CYP3A4 and MDR1 expression in vitro. A 2.5 fold rise of cortisol metabolite was evident in smokers relative to nonsmokers. Altered functions of efflux transporters and CYPs in response to ARV and drugs of abuse may result in altered drug absorption and metabolism. Appropriate in vitro models can be employed to predict such interactions. Influence of genetic polymorphism, SNP and inter-individual variation in drug response has been discussed. Complexity underlying the relationship between efflux transporters and CYP makes it difficult to predict the outcome of HAART as such, particularly when HIV patients taking drugs of abuse do not adhere to HAART regimens. HIV(+) pregnant women on HAART medications, indulging in drugs of abuse, may develop higher viral load due to such interactions and lead to increase in mother to child transmission of HIV. A multidisciplinary approach with clear understanding of mechanism of interactions may allow proper selection of regimens so that desired therapeutic outcome of HAART can be reached without any side effects.     

Interference with the Host Haemostatic System by Schistosomes

Schistosomes, parasitic flatworms that cause the tropical disease schistosomiasis, are still a threat. They are responsible for 200 million infections worldwide and an estimated 280,000 deaths annually in sub-Saharan Africa alone. The adult parasites reside as pairs in the mesenteric or perivesicular veins of their human host, where they can survive for up to 30 years. The parasite is a potential activator of blood coagulation according to Virchow''s triad, because it is expected to alter blood flow and endothelial function, leading to hypercoagulability. In contrast, hepatosplenic schistosomiasis patients are in a hypocoagulable and hyperfibrinolytic state, indicating that schistosomes interfere with the haemostatic system of their host. In this review, the interactions of schistosomes with primary haemostasis, secondary haemostasis, fibrinolysis, and the vascular tone will be discussed to provide insight into the reduction in coagulation observed in schistosomiasis patients.Interference with the haemostatic system by pathogens is a common mechanism and has been described for other parasitic worms, bacteria, and fungi as a mechanism to support survival and spread or enhance virulence. Insight into the mechanisms used by schistosomes to interfere with the haemostatic system will provide important insight into the maintenance of the parasitic life cycle within the host. This knowledge may reveal new potential anti-schistosome drug and vaccine targets. In addition, some of the survival mechanisms employed by schistosomes might be used by other pathogens, and therefore, these mechanisms that interfere with host haemostasis might be a broad target for drug development against blood-dwelling pathogens. Also, schistosome antithrombotic or thrombolytic molecules could form potential new drugs in the treatment of haemostatic disorders.     

Identifying Novel Drug Indications through Automated Reasoning

Background

With the large amount of pharmacological and biological knowledge available in literature, finding novel drug indications for existing drugs using in silico approaches has become increasingly feasible. Typical literature-based approaches generate new hypotheses in the form of protein-protein interactions networks by means of linking concepts based on their cooccurrences within abstracts. However, this kind of approaches tends to generate too many hypotheses, and identifying new drug indications from large networks can be a time-consuming process.

Methodology

In this work, we developed a method that acquires the necessary facts from literature and knowledge bases, and identifies new drug indications through automated reasoning. This is achieved by encoding the molecular effects caused by drug-target interactions and links to various diseases and drug mechanism as domain knowledge in AnsProlog, a declarative language that is useful for automated reasoning, including reasoning with incomplete information. Unlike other literature-based approaches, our approach is more fine-grained, especially in identifying indirect relationships for drug indications.

Conclusion/Significance

To evaluate the capability of our approach in inferring novel drug indications, we applied our method to 943 drugs from DrugBank and asked if any of these drugs have potential anti-cancer activities based on information on their targets and molecular interaction types alone. A total of 507 drugs were found to have the potential to be used for cancer treatments. Among the potential anti-cancer drugs, 67 out of 81 drugs (a recall of 82.7%) are indeed known cancer drugs. In addition, 144 out of 289 drugs (a recall of 49.8%) are non-cancer drugs that are currently tested in clinical trials for cancer treatments. These results suggest that our method is able to infer drug indications (original or alternative) based on their molecular targets and interactions alone and has the potential to discover novel drug indications for existing drugs.     

Drugs of abuse and stress trigger a common synaptic adaptation in dopamine neurons

Drug seeking and drug self-administration in both animals and humans can be triggered by drugs of abuse themselves or by stressful events. Here, we demonstrate that in vivo administration of drugs of abuse with different molecular mechanisms of action as well as acute stress both increase strength at excitatory synapses on midbrain dopamine neurons. Psychoactive drugs with minimal abuse potential do not cause this change. The synaptic effects of stress, but not of cocaine, are blocked by the glucocorticoid receptor antagonist RU486. These results suggest that plasticity at excitatory synapses on dopamine neurons may be a key neural adaptation contributing to addiction and its interactions with stress and thus may be an attractive therapeutic target for reducing the risk of addiction.     

Network Neighbors of Drug Targets Contribute to Drug Side-Effect Similarity

In pharmacology, it is essential to identify the molecular mechanisms of drug action in order to understand adverse side effects. These adverse side effects have been used to infer whether two drugs share a target protein. However, side-effect similarity of drugs could also be caused by their target proteins being close in a molecular network, which as such could cause similar downstream effects. In this study, we investigated the proportion of side-effect similarities that is due to targets that are close in the network compared to shared drug targets. We found that only a minor fraction of side-effect similarities (5.8 %) are caused by drugs targeting proteins close in the network, compared to side-effect similarities caused by overlapping drug targets (64%). Moreover, these targets that cause similar side effects are more often in a linear part of the network, having two or less interactions, than drug targets in general. Based on the examples, we gained novel insight into the molecular mechanisms of side effects associated with several drug targets. Looking forward, such analyses will be extremely useful in the process of drug development to better understand adverse side effects.     

The use of oral topically acting glucocorticosteroids in the treatment of inflammatory bowel disease.

Glucocorticosteroids are the mainstay of treatment of active Crohn''s disease and ulcerative colitis. These drugs however carry important cosmetic short-term side effects and when used long-term they induce severe irreversible complications. Topically acting glucocorticosteroids, especially budesonide, have been designed to achieve local effect at the site of inflammation without systemic effects of the drug. The first results of clinical trials are promising and budesonide has been shown to have an improved safety with almost comparable efficacy in comparison with prednisolone. The optimal enema dose seems to be 2 mg/100 ml at night whereas 9 mg o.m. is the optimal dose to treat ileal or right ileocolonic Crohn''s disease. Topically acting GCS, like standard GCS are not effective for maintenance of remission of Crohn''s disease or recurrence prevention after resection of the involved Crohn''s segment.     

Metabolism, Pharmacogenetics, and Metabolic Drug–Drug Interactions of Antipsychotic Drugs

1. Antipsychotic drugs are extensively metabolised by cytochrome P450 (CYP) enzymes.2. Dispositions of a number of antipsychotic drugs have been shown to cosegregate with polymorphism of CYP2D6.3. Metabolic drug–drug interactions have frequently been observed when antipsychotics are coadministered with other drugs.4. Many antipsychotic drugs are converted to active metabolites which can contribute to the therapeutic or side effects of the parent drug.5. Information concerning the individual CYP isoenzymes involved in the metabolism of antipsychotic drugs is important for the safe clinical use of this group of drugs.     

Chemogenomic Approaches for Revealing Drug Target Interactions in Drug Discovery

The drug discovery process has been a crucial and cost-intensive process. This cost is not only monetary but also involves risks, time, and labour that are incurred while introducing a drug in the market. In order to reduce this cost and the risks associated with the drugs that may result in severe side effects, the in silico methods have gained popularity in recent years. These methods have had a significant impact on not only drug discovery but also the related areas such as drug repositioning, drug-target interaction prediction, drug side effect prediction, personalised medicine, etc. Amongst these research areas predicting interactions between drugs and targets forms the basis for drug discovery. The availability of big data in the form of bioinformatics, genetic databases, along with computational methods, have further supported data-driven decision-making. The results obtained through these methods may be further validated using in vitro or in vivo experiments. This validation step can further justify the predictions resulting from in silico approaches, further increasing the accuracy of the overall result in subsequent stages. A variety of approaches are used in predicting drug-target interactions, including ligand-based, molecular docking based and chemogenomic-based approaches. This paper discusses the chemogenomic methods, considering drug target interaction as a classification problem on whether or not an interaction between a particular drug and target would serve as a basis for understanding drug discovery/drug repositioning. We present the advantages and disadvantages associated with their application.     

Relevance of Higher-Order Epistasis in Drug Resistance

We studied five chemically distinct but related 1,3,5-triazine antifolates with regard to their effects on growth of a set of mutants in dihydrofolate reductase. The mutants comprise a combinatorially complete data set of all 16 possible combinations of four amino acid replacements associated with resistance to pyrimethamine in the malaria parasite Plasmodium falciparum. Pyrimethamine was a mainstay medication for malaria for many years, and it is still in use in intermittent treatment during pregnancy or as a partner drug in artemisinin combination therapy. Our goal was to investigate the extent to which the alleles yield similar adaptive topographies and patterns of epistasis across chemically related drugs. We find that the adaptive topographies are indeed similar with the same or closely related alleles being fixed in computer simulations of stepwise evolution. For all but one of the drugs the topography features at least one suboptimal fitness peak. Our data are consistent with earlier results indicating that third order and higher epistatic interactions appear to contribute only modestly to the overall adaptive topography, and they are largely conserved. In regard to drug development, our data suggest that higher-order interactions are likely to be of little value as an advisory tool in the choice of lead compounds.     

Neurotrophins as mediators of drug effects on mood, addiction, and neuroprotection

The induction of synthesis or release of endogenous neurotrophic factors in the brain by low-molecular-weight drugs could be a feasible alternative for the direct administration of neurotrophic factors for the treatment of central nervous system disorders. Recent data suggest that several drugs already in clinical use increase the synthesis, release, or signaling of neurotrophins. Antidepressant drugs increase the synthesis and signaling of brain-derived neurotrophic factor (BDNF), and BDNF signaling appears to be both sufficient and necessary for the antidepressant-induced behavioral effects. Furthermore, neurotrophins and other neurotrophic factors play a role in the acute and chronic responses produced by addictive drugs. Moreover, several neuroprotective drugs influence neurotrophin synthesis or signaling, although the significance of these effects is still unclear. These findings reveal a wider role for neurotrophic factors in drug action than has previously been expected, and they suggest that neurotrophin-induced trophic responses in neuronal connectivity and plasticity may be involved in the mechanism of action of several classes of CNS drugs. Improved assay systems are needed for the systematic screening of the effects of putative neuroprotective drugs on the synthesis, release, and signaling of neurotrophic factors, and for the evaluation of the functional role of these factors in the action of novel drug candidates.     

A Network Inference Method for Large-Scale Unsupervised Identification of Novel Drug-Drug Interactions

Characterizing interactions between drugs is important to avoid potentially harmful combinations, to reduce off-target effects of treatments and to fight antibiotic resistant pathogens, among others. Here we present a network inference algorithm to predict uncharacterized drug-drug interactions. Our algorithm takes, as its only input, sets of previously reported interactions, and does not require any pharmacological or biochemical information about the drugs, their targets or their mechanisms of action. Because the models we use are abstract, our approach can deal with adverse interactions, synergistic/antagonistic/suppressing interactions, or any other type of drug interaction. We show that our method is able to accurately predict interactions, both in exhaustive pairwise interaction data between small sets of drugs, and in large-scale databases. We also demonstrate that our algorithm can be used efficiently to discover interactions of new drugs as part of the drug discovery process.     

The clinical application of chronobiology to oncology

The introduction to medical practice of chemical agents for fighting human cancer some 30 years ago brought hope to a field of medicine previously shrouded in despair and impeded by superstition. Gradually more and better agents have become available to the physician and to the patient suffering from cancer. The physician-scientist has, in turn, learned a great deal about normal and abnormal cellular biology by using these drugs as probes. The observations that certain tissues and certain tumors share patterns of drug toxicity have led to a broadening of biologic understanding and to the use of combinations of drugs with shared antitumor activity and unshared toxicities. This empiric art of cancer chemotherapy has resulted in great progress in the treatment of a large number of advanced cancers. As important, however, is that this experience has resulted in knowledge which is leading to the development of rationally designed therapeutic regimens; to drug analogues seeking greater therapeutic-toxic ratios; to the development of methods for chemically interfering with toxic drug effects while allowing or enhancing antitumor effect; and to work defining effects of drug timing. Drug timing research considers drug dosage in respect to the timing of a drug relative to the timing of other drugs (drug-time-drug interactions) or to other doses of that same drug (drug-drug interval); the order of drugs (drug-drug sequence); and the timing of drugs relative to an internal organismic time structure (time-drug interactions). Data in this brief review clearly show that drug timing needs to be considered when designing rational chemotherapy for a living organism suffering from a cancer. The beautiful spatiotemporal complexity of life is not to be ignored or avoided, but should be considered as a golden opportunity to use what few imprecise chemical weapons we have a little more effectively.