Metabolic pathways prediction

In the above-mentioned examples, the prediction of CYP-mediated compound interactions is a starting point in any metabolic pathway prediction or enzyme inactivation. This chapter presents an evolution of a standard method [1], widely used in pharmaceutical research in the early-ADMET (absorption, distribution, metabolism, excretion and toxicity) field, which provides information on the biotransformations produced by CYP-mediated substrate interactions. The methodology can be applied automatically to all the cytochromes whose 3 D structure can be modeled or is known, including plants as well as phase II enzymes. It can be used by chemists to detect molecular positions that should be protected to avoid metabolic degradation, or to check the suitability of a new scaffold or prodrug. The fully automated procedure is also a valuable new tool in early-ADMET where metabolite- or mechanism based inhibition (MBI) must be evaluated as early as possible. 

Moriya, Y., Shigemizu, D., Hattori, M., Tokimatsu, T. et al (2010) PathPred an enzyme-catalyzed metabolic pathway prediction server. Nucleic Acids Res.,... 

Wanjie, S.W., Welti, R., Moreau, R.A. and Chapman, K.D. (2005) Identification and quantification of glycerohpids in cotton fibers Reconciliation with metabolic pathway predictions from DNA databases. Lipids 40, 773-785. 

MetabolExperF Rule-based Metabolite prediction software Predicts the most common metabolic pathways in animals, plants or through photodegradation. Results are presented in metabolic tree format. Graphical interface for editing and adding rules www.compudrug.com... 

A new tool for computational ADME/Tox called MetaDrug includes a manually annotated Oracle database of human drug metabolism information including xenobiotic reactions, enzyme substrates, and enzyme inhibitors with kinetic data. The MetaDrug database has been used to predict some of the major metabolic pathways and identify the involvement of P450s [78]. This database has enabled the generation of over 80 key metabolic... 

PBPK models have also been used to explain the rate of excretion of inhaled trichloroethylene and its major metabolites (Bogen 1988 Fisher et al. 1989, 1990, 1991 Ikeda et al. 1972 Ramsey and Anderson 1984 Sato et al. 1977). One model was based on the results of trichloroethylene inhalation studies using volunteers who inhaled 100 ppm trichloroethylene for 4 horns (Sato et al. 1977). The model used first-order kinetics to describe the major metabolic pathways for trichloroethylene in vessel-rich tissues (brain, liver, kidney), low perfused muscle tissue, and poorly perfused fat tissue and assumed that the compartments were at equilibrium. A value of 104 L/hour for whole-body metabolic clearance of trichloroethylene was predicted. Another PBPK model was developed to fit human metabolism data to urinary metabolites measured in chronically exposed workers (Bogen 1988). This model assumed that pulmonary uptake is continuous, so that the alveolar concentration is in equilibrium with that in the blood and all tissue compartments, and was an expansion of a model developed to predict the behavior of styrene (another volatile organic compound) in four tissue groups (Ramsey and Andersen 1984). 

Sato et al. (1991) expanded their earlier PBPK model to account for differences in body weight, body fat content, and sex and applied it to predicting the effect of these factors on trichloroethylene metabolism and excretion. Their model consisted of seven compartments (lung, vessel rich tissue, vessel poor tissue, muscle, fat tissue, gastrointestinal system, and hepatic system) and made various assumptions about the metabolic pathways considered. First-order Michaelis-Menten kinetics were assumed for simplicity, and the first metabolic product was assumed to be chloral hydrate, which was then converted to TCA and trichloroethanol. Further assumptions were that metabolism was limited to the hepatic compartment and that tissue and organ volumes were related to body weight. The metabolic parameters, (the scaling constant for the maximum rate of metabolism) and (the Michaelis constant), were those determined for trichloroethylene in a study by Koizumi (1989) and are presented in Table 2-3. 

One approach to formulating potential differences in ethnic response is to examine the metabolic pathways of the common antipsychotics and determine whether the known ethnic variations in metabolizing enzymes or other effects on absorption, distribution, and excretion can be applied a priori to predict potential clinical effects. In this section we will consider some of the commonly prescribed SGAs, and only briefly touch on the FGAs. 

Antoniewicz, M.R., Stephanopoulos, G., and Kelleher, J.K., Evaluation of regression models in metabolic physiology Predicting fluxes from isotopic data without knowledge of the pathway, Metabolomics 2,41, 2006. 

Darvas F. Predicting metabolic pathways by logic programming. J Mol Graph 1988 6 80-86. 

Recent work in our laboratories has confirmed the existence of a similar pathway in the oxidation of vindoline in mammals (777). The availability of compounds such as 59 as analytical standards, along with published mass spectral and NMR spectral properties of this compound, served to facilitate identification of metabolites formed in mammalian liver microsome incubations. Two compounds are produced during incubations with mouse liver microsome preparations 17-deacetylvindoline, and the dihydrovindoline ether dimer 59. Both compounds were isolated and completely characterized by spectral comparison to authentic standards. This work emphasizes the prospective value of microbial and enzymatic transformation studies in predicting pathways of metabolism in mammalian systems. This work would also suggest the involvement of cytochrome P-450 enzyme system(s) in the oxidation process. Whether the first steps involve direct introduction of molecular oxygen at position 3 of vindoline or an initial abstraction of electrons, as in Scheme 15, remains unknown. The establishment of a metabolic pathway in mammals, identical to those found in Strep-tomycetes, with copper oxidases and peroxidases again confirms the prospective value of the microbial models of mammalian metabolism concept. 

Orthology prediction using only the relative levels of similarity of genes can be useful for quantitative estimates of certain genomic features such as the number of shared genes or the number of conserved gene pairs, rather than filling in their specific function, e.g., to predict the existence of a metabolic pathway. 

Evidence further suggests that male rats eliminate disulfoton at a faster rate than females. This difference may be due to differences in absorption, metabolism, retention, excretion, or a combination of factors. The metabolic pathways of disulfoton are relatively well understood based on data from animal studies (Bull 1965 Lee et al. 1985 March et al. 1957 Puhl and Fredrickson 1975). Similar metabolites have been detected in the urine and tissues from humans exposed to disulfoton (Brokopp et al. 1981 Yashiki et al. 1990). One study suggests that a greater percentage of disulfoton sulfoxide is oxidized to demeton S-sulfoxide, rather than disulfoton sulfone to form demeton S-sulfone (Bull 1965). Additional studies in animals, designed to measure the rate and extent of absorption, distribution, and excretion of disulfoton after inhalation or dermal exposure would be useful for predicting the toxicokinetics of disulfoton in humans at an occupational or hazardous waste site. 

When working with non-radiolabeled drugs the major challenge is to find metabolites in the biological matrices. Because the enzymes responsible for metabolism are quite well characterized metabolic changes can partially be predicted. For example hydroxylation of the parent drug is in many cases the principal metabolic pathway. From a mass spectrometric point of view it results in an increase of 16 units in the mass spectrum. In the full-scan mode an extracted ion current profile can be used to screen for potential metabolites. In a second step a product ion spectrum is recorded for structural interpretation. Ideally, one would like to obtain relative molecular mass information and the corresponding product ion spectrum in the same LC-MS run. This information can be obtained by data dependant acquisition (DDA), as illustrated in Fig. 1.39. 

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