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ABSTRACT: ABSTRACT: After our work was published, we found that some of the terms in the equations were incorrect and that there were some typographical errors in the abbreviations. In the section 'Single adjusting compartment' in Materials and Methods, VS should be VSAC. In the last paragraph of Results, QSAC should be QSAC. The correct equations are included in this article. These corrections will not affect the results of this study.
Theoretical Biology and Medical Modelling 12/2009; 6(1):29. · 1.86 Impact Factor
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ABSTRACT: Recently it has been reported that some drugs that produce reactive intermediates may cause clinical adverse effects following covalent binding to biomacromolecules. For example, Schiff base production mediated by aldehyde is a possible mechanism of drug-protein adducts. However, because thiols do not trap aliphatic aldehydes via hemiacetal or hemiaminal, the glutathione-trapping method cannot be used to determine the covalent bindings of the Schiff base.
We established a quantitative method to determine covalent binding mediated by aldehydes via hemiaminal or hemiacetal using non-radiolabeled compound and [(14)C]semicarbazide as a hard-trap agent with unique post-incubation.
The trapped aldehyde obtained from the post-incubation was almost equivalent to the covalent binding of the radiolabeled tool compound. Our novel method showed its usefulness in quantitative detection of aldehyde's covalent binding ability by several reagents with alicyclic amine and launched drugs as control.
The post-incubation method is useful for screening newly synthesized compounds to quantitatively assess the bioactivation of aldehydes descending from alicyclic amines.
Journal of pharmacological and toxicological methods 11/2009; 61(1):44-51. · 2.32 Impact Factor
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ABSTRACT: There are various methods for predicting human pharmacokinetics. Among these, a whole body physiologically-based pharmacokinetic (WBPBPK) model is useful because it gives a mechanistic description. However, WBPBPK models cannot predict human pharmacokinetics with enough precision. This study was conducted to elucidate the primary reason for poor predictions by WBPBPK models, and to enable better predictions to be made without reliance on complex concepts.
The primary reasons for poor predictions of human pharmacokinetics were investigated using a generic WBPBPK model that incorporated a single adjusting compartment (SAC), a virtual organ compartment with physiological parameters that can be adjusted arbitrarily. The blood flow rate, organ volume, and the steady state tissue-plasma partition coefficient of a SAC were calculated to fit simulated to observed pharmacokinetics in the rat. The adjusted SAC parameters were fixed and scaled up to the human using a newly developed equation. Using the scaled-up SAC parameters, human pharmacokinetics were simulated and each pharmacokinetic parameter was calculated. These simulated parameters were compared to the observed data. Simulations were performed to confirm the relationship between the precision of prediction and the number of tissue compartments, including a SAC.
Increasing the number of tissue compartments led to an improvement of the average-fold error (AFE) of total body clearances (CL tot) and half-lives (T 1/2) calculated from the simulated human blood concentrations of 14 drugs. The presence of a SAC also improved the AFE values of a ten-organ model from 6.74 to 1.56 in CL tot, and from 4.74 to 1.48 in T 1/2. Moreover, the within-2-fold errors were improved in all models; incorporating a SAC gave results from 0 to 79% in CL tot, and from 14 to 93% in T 1/2 of the ten-organ model.
By using a SAC in this study, we were able to show that poor prediction resulted mainly from such physiological factors as organ blood flow rate and organ volume, which were not satisfactorily accounted for in previous WBPBPK models. The SAC also improved precision in the prediction of human pharmacokinetics. This finding showed that the methodology of our study may be useful for functionally reinforcing a WBPBPK model.
Theoretical Biology and Medical Modelling 09/2008; 5:19. · 1.86 Impact Factor
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ABSTRACT: We describe the design, synthesis, and physicochemical and biological properties of a novel series of 7-heterocycle-6-trifluoromethyl-3-oxoquinoxaline-2-carboxylic acids bearing a substituted phenyl group joined through a urethane or urea linkage to the heterocycle at the 7 position. Introduction of the trifluoromethyl group at the 6 position conferred good biological activity, including neuroprotective effects, as well as good physicochemical properties. In terms of alpha-amino-3-hydroxy-5-methylisoxazole propionate receptor (AMPA-R) affinity, a urea linkage was equivalent to a urethane linkage and a pyrrole ring at the 7 position reduced affinity in comparison with an imidazole ring. Among this series, compound 14h (KRP-199), which has a 4-carboxyphenyl group joined through a urethane linkage to a 7-imidazolyl heterocycle, was found to possess high potency and selectivity for the AMPA-R in vitro and to exhibit good neuroprotective effects in vivo. Furthermore, the compound showed good physicochemical properties, including stability to light and good solubility in aqueous solutions.
Bioorganic & Medicinal Chemistry 03/2006; 14(3):776-92. · 2.92 Impact Factor
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ABSTRACT: We describe the synthesis, physicochemical, and biological properties of a novel series of 7-imidazolyl-6-trifluoromethyl quinoxalinecarboxylic acids with a substituted phenyl group attached through a urethane linkage at the C-7 position. We found that the introduction of trifluoromethyl group at the C-6 position brought about good biological activity and physicochemical properties. Among them, compound 9k (KRP-199), which has a 4-carboxyphenyl group, was found to possess high potency and selectivity for the AMPA-R in vitro and to exhibit good neuroprotective effects in vivo. Furthermore, the compound showed good physicochemical properties such as stability to light and good solubility in aqueous solutions.
Bioorganic & Medicinal Chemistry Letters 11/2004; 14(20):5107-11. · 2.55 Impact Factor
