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Metabolism interactions based

Haddad, S., G. Charest-Tardif, and K. Krishnan. 2000b. Physiologically based modelling of the maximal effect of metabolic interactions on the kinetics of components of complex chemical mixtures. J. Toxicol. Environ. Health 61 PartA 209-223. [Pg.407]

Tardif et al. (1992, 1993 a, 1997) have developed a physiologically based toxicokinetic model for toluene in rats (and humans—see Section 4.1.1). They determined the conditions under which interaction between toluene and xylene(s) occurred during inhalation exposure, leading to increased blood concentrations of these solvents, and decreased levels of the hippurates in urine. Similar metabolic interactions have been observed for toluene and benzene in rats (Purcell et al., 1990) toluene inhibited benzene metabolism more effectively than the reverse. Tardif et al. (1997) also studied the exposure of rats (and humans) to mixtures of toluene, we/a-xylene and ethylbenzene, using their physiologically based pharmacokinetic model the mutual inhibition constants for their metabolism were used for simulation of the human situation. [Pg.842]

Studies in recent years have revealed a number of remarkable drug interactions with irreversible or mechanism-based inhibitors of CYP3A, many of which can be attributed to inhibition of sequential intestinal and hepatic first-pass metabolism. Mechanism-based inhibition involves the metabolism of an inhibitor to a reactive metabolite, which either forms a slowly reversible metabolic-intermediate (MI) complex with the heme moiety or inactivates the enzyme irreversibly via covalent binding to the enzyme catalyzing the last step in the bioactivation sequence. As a result, mechanism-based inhibition is both... [Pg.487]

Kanamitsu SI, Ito K, Okuda H, et al. Prediction of in vivo drug-drug interactions based on mechanism-based inhibition from in vitro data inhibition of 5-fluorouracil metabolism by (E)-5-(2-bromovinyl)uracil. Drug Metab Dispos 2000 28(4) 467 t74. [Pg.544]

Most of the reports about interactions of metals with nucleic acids and their metabolism are based on studies with bacteria and animals. Information from higher plants is rather poor. Ernst (1980) cited an increase of the number of structural chromosome aberrations after cadmium treatment of Crepis capillaris seeds. [Pg.169]

Among all the interactions-based PBTK models published to date, reversible metabolic inhibition is by far the most frequently encountered type of interaction. There are 3 types of reversible enzyme inhibition competitive, noncompetitive, and uncompetitive (Table 2.2), and examples of all are listed in Table 2.3. A large number of examples of such metabolic inhibition in humans and laboratory animals are available for specific CYP enzymes and therapeutic drugs (Dome et al. 2007b). [Pg.61]

Yu X, Johanson G, Ichihara G, Shibata E, Kamijima M, Ono Y, Takeuchi Y. 1998. Physiologically based pharmacokinetic modeling of metabolic interactions between n-hexane and toluene in humans. J Occup Health 40 293-301. [Pg.269]

Once the protein interaction pattern is translated from Cartesian coordinates into distances from the reactive center of the enzyme, and the structure of the ligand has been described with similar fingerprints, both sets of descriptors can be compared. The hydrophobic complementarity (see Fig. 12.5), the complementarity of charges, and H-bonds for the protein and the substrates, are all computed using Carbo similarity [20] indices. The prediction of the site of metabolism is based on... [Pg.282]

While rate equations can be solved and metabolic rates can be estimated and determined easily in vitro because of the control of variables (specifically, substrate concentration), the situation is much more difficult in vivo. Here the advent of physiologically based pharmacokinetic (PBPK) models has offered a powerful tool for examining metabolic interactions that occur following exposure to chemical mixtures (see Chapter 3). [Pg.616]

The majority of protein-protein interaction analysis tools rely on information obtained from repositories such as BIND [156], DIP [157], MINT [158], and GRID [159]. Interaction data from public databases can be accessed directly to retrieve experimental information. Alternatively, protein-interaction data can be accessed via predictive tools such as STRING and InterWeaver. Identifying protein-protein interactions can provide clues beyond a functional role or subcellular location. It is possible to predict a protein s metabolic importance based on the density of edges connecting nodes, because it has been shown that nodes with a high density of connections are more hkely to contain essential genes [160]. [Pg.64]

There are important new applications of the aza-crown macrocycles for medicinal purposes. The perturbation of metabolic processes based on biological metal ion-ligand coordination can produce a disease or even death. Conversely, undesirable biological processes can be prevented by using certain metal ion-ligand interactions. For example, the weak complexing ability of chlorine to the central platinum ion of ds-platin (61) allows cw-platin to have antitumor activity (Haiduc and Silvestru, 1989). When applied in a biological... [Pg.16]

Depending on the bacteria and soil conditions which can be described appropriately as an extremely heterogeneous system, these transformations may be assimilatory or dissimilatory metabolic functions. Based on the recent field surveys and laboratory studies, the bacterial-environmental interactions, with reference to the cycles of sulfur and other elements, in corrosion on buried pipes are shown as Figure 1. This Figure demonstrates that microbiologically influenced corrosion (MIC) results from the activities of a microbial community. [Pg.365]

Quinine is metaboiized in the liver to the 2 -hydroxy derivative, followed by additional hydroxylation on the quinuciidine ring, with the 2,2 -dihydroxy derivative as the major metabolite. This metabolite has low activity and is rapidly excreted. The metabolizing enzyme of quinine is CYP3A4. With the increased use of quinine and its use in combination with other drugs, the potential for drug interactions based on the many known substrates for CYP3A4 (see Chapter 10) is of concern (36). [Pg.1684]

Fahmi OA, Maurer TS, Kish M, Cardenas E, Boldt S and Nettleton D (2008) A combined model for predicting CYP3A4 clinical net drug-drug interaction based on CYP3A4 inhibition, inactivation, and induction determined in vitro (Drug Metab Dispos (2008) 36 (1698-1708). Drug Metabolism and Disposition 36(9) 1975. [Pg.134]

Antia U, Tingle MD, Russell BR. Metabolic interactions with piperazine-based party pill drugs. J Pharm Pharmacol 2009 61(7) 877-82. [Pg.68]


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Interactions, metabolic

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