Gene/Protein Disease Symptom Drug Enzyme Compound
Pivot Concepts: Gene/Protein Disease Symptom Drug Enzyme Compound   Target Concepts: Gene/Protein Disease Symptom Drug Enzyme Compound

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Query: EC:3.6.3.44 (P-glycoprotein)
13,344 document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)

Tipranavir is a nonpeptidic protease inhibitor that has activity against human immunodeficiency virus strains resistant to multiple protease inhibitors. Tipranavir 500 mg is coadministered with ritonavir 200 mg. Tipranavir is metabolized by cytochrome P450 (CYP) 3A and, when combined with ritonavir in vitro, causes inhibition of CYP1A2, CYP2C9, CYP2C19, CYP2D6, and CYP3A in addition to induction of glucuronidase and the drug transporter P-glycoprotein. As a result, drug-drug interactions between tipranavir-ritonavir and other coadministered drugs are a concern. In addition to interactions with other antiretrovirals, tipranavir-ritonavir interactions with antifungals, antimycobacterials, oral contraceptives, statins, and antidiarrheals have been specifically evaluated. For other drugs such as antiarrhythmics, antihistamines, ergot derivatives, selective serotonin receptor agonists (or triptans), gastrointestinal motility agents, erectile dysfunction agents, and calcium channel blockers, interactions can be predicted based on studies with other ritonavir-boosted protease inhibitors and what is known about tipranavir-ritonavir CYP and P-glycoprotein utilization. The highly complex nature of drug interactions dictates that cautious prescribing should occur with narrow-therapeutic-index drugs that have not been specifically studied. Thus, the known interaction potential of tipranavir-ritonavir is reported, and in vitro and in vivo data are provided to assist clinicians in predicting interactions not yet studied. As more clinical interaction data are generated, better insight will be gained into the specific mechanisms of interactions with tipranavir-ritonavir.
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PMID:Mechanisms of pharmacokinetic and pharmacodynamic drug interactions associated with ritonavir-enhanced tipranavir. 1754 71

Computational methods for predicting compounds of specific pharmacodynamic and ADMET (absorption, distribution, metabolism, excretion and toxicity) property are useful for facilitating drug discovery and evaluation. Recently, machine learning methods such as neural networks and support vector machines have been explored for predicting inhibitors, antagonists, blockers, agonists, activators and substrates of proteins related to specific therapeutic and ADMET property. These methods are particularly useful for compounds of diverse structures to complement QSAR methods, and for cases of unavailable receptor 3D structure to complement structure-based methods. A number of studies have demonstrated the potential of these methods for predicting such compounds as substrates of P-glycoprotein and cytochrome P450 CYP isoenzymes, inhibitors of protein kinases and CYP isoenzymes, and agonists of serotonin receptor and estrogen receptor. This article is intended to review the strategies, current progresses and underlying difficulties in using machine learning methods for predicting these protein binders and as potential virtual screening tools. Algorithms for proper representation of the structural and physicochemical properties of compounds are also evaluated.
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PMID:Machine learning approaches for predicting compounds that interact with therapeutic and ADMET related proteins. 1778 89

Studies of gene function and molecular mechanisms in Plasmodium falciparum are hampered by difficulties in characterizing and measuring phenotypic differences between individual parasites. We screened seven parasite lines for differences in responses to 1,279 bioactive chemicals. Hundreds of compounds were active in inhibiting parasite growth; 607 differential chemical phenotypes, defined as pairwise IC(50) differences of fivefold or more between parasite lines, were cataloged. We mapped major determinants for three differential chemical phenotypes between the parents of a genetic cross, and we identified target genes by fine mapping and testing the responses of parasites in which candidate genes were genetically replaced with mutant alleles. Differential sensitivity to dihydroergotamine methanesulfonate (1), a serotonin receptor antagonist, was mapped to a gene encoding the homolog of human P-glycoprotein (PfPgh-1). This study identifies new leads for antimalarial drugs and demonstrates the utility of a high-throughput chemical genomic strategy for studying malaria traits.
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PMID:Genetic mapping of targets mediating differential chemical phenotypes in Plasmodium falciparum. 1973 10

Although effective treatment for mood and anxiety disorders have been available for more than 40 years, 30-50% of depressed patients and 25% of patients with anxiety disorder do not respond sufficiently to first-line treatment with antidepressants. Genetic factors are supposed to play a major role in both variation of treatment response and incidence of adverse effects to medication. So far, candidate genes of pharmacokinetic and pharmacodynamic pathways of antidepressants have been investigated, and associations between several candidate genes and response to antidepressants are reported. Two functional polymorphisms of the serotonin transporter gene, 5-HTTLPR and STin2 have been investigated in a large number of pharmacogenetic studies of depression; other candidate genes include serotonin receptor genes, brain-derived neurotrophic factor, P-glycoprotein (located in the blood-brain barrier), G-proteins, TPH1 and TPH2, MAOA, the noradrenaline transporter gene, FKBP5, or cytochrome P450 (CYP450) genes. CYP450 genes play a major role in the metabolism of a substantial part of psychotropics, including antidepressants, and the first estimates of dosage adjustments for antidepressants have been provided based on metabolizer status. Genome-wide association studies that use large numbers of single-nucleotide polymorphisms to screen the entire genome for alleles that influence a trait are now feasible, and the results of the first genome-wide association studies of antidepressant treatment outcome will soon be available. The current review not only updates pharmacogenetic research in depression but also focuses on antidepressant treatment response in anxiety disorders.
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PMID:The role of pharmacogenetics in the treatment of depression and anxiety disorders. 1973 81

Though the 5-HT₆ serotonin receptor is an important target giving both agonists and antagonists similar therapeutic potency in the treatment of topic CNS-diseases, no 5-HT₆R ligand has reached the pharmaceutical market yet due to the too narrow chemical space of the known 5-HT₆R agents and insufficient "drugability." Recently, a new group of non-indole and non-sulfone hydantoin-triazine 5-HT₆R ligands was found, where 3-((4-amino-6-(4-methylpiperazin-1-yl)-1,3,5-triazin-2-yl)methyl)-5-methyl-5-(naphthalen-2-yl)imidazolidine-2,4-dione (KMP-10) was the most active member. This study is focused on wider pharmacological and "druglikeness" characteristics for KMP-10. A computer-aided insight into molecular interactions with 5-HT₆R has been performed. "Druglikeness" was examined using an eight-test panel in vitro, i.e., a parallel artificial membrane permeability assay (PAMPA), and Caco-2 permeability-, P-glycoprotein (Pgp) affinity-, plasma protein binding-, metabolic stability- and drug-drug interaction-assays, as well as mutagenicity- and HepG2-hepatotoxicity risk tests. Behavioral studies in vivo, i.e., elevated plus-maze (EPM) and novel object recognition (NOR) tests, were performed. Extended studies on the influence of KMP-10 on rats' metabolism, including biochemical tests, were conducted in vivo. Results indicated significant anxiolytic and precognitive properties, as well as some anti-obesity properties in vivo, and it was found to satisfy the "druglikeness" profile in vitro for KMP-10. The compound seems to be a good lead-structure and candidate for wider pharmacological studies in search for new CNS-drugs acting via 5-HT₆R.
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PMID:Are the Hydantoin-1,3,5-triazine 5-HT₆R Ligands a Hope to a Find New Procognitive and Anti-Obesity Drug? Considerations Based on Primary In Vivo Assays and ADME-Tox Profile In Vitro. 3181 28

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