Metabolites physicochemical properties

The oxidative polymerization of 5,6-dihydroxyindole (1) and related tyrosine-derived metabolites is a central, most elusive process in the biosynthesis of eumelanins, which are the characteristic pigments responsible for the dark color of human skin, hair, and eyes. Despite the intense experimental research for more than a century,36 the eumelanin structure remains uncharacterized because of the lack of defined physicochemical properties and the low solubility, which often prevents successful investigations by modem spectroscopic techniques. The starting step of the oxidative process is a one-electron oxidation of 5,6-dihydroxyindole generating the semiquinone 1-SQ (Scheme 2.7). 

An interesting vertical profile of the metabolite concentrations was observed the compounds showed a tendency to accumulate at the two-phase boundaries of air-freshwater and freshwater-saline water (the halocline). Thus, concentration maxima were observed at depths of 0 and 2 m (see Fig. 6.4.1) [6]. The observed distribution may result from either the physicochemical properties of these compounds (surface activity and hydrophobicity), or their formation at the interface due to increased biological activity. For the parent surfactants a similar but less pronounced vertical distribution pattern was observed (with maxima at 0 and 2 m of 17 and 9 xg L 1, respectively) [5],... 

Stoichiometric analysis goes beyond topological arguments and takes the specific physicochemical properties of metabolic networks into account. As noted above, based on the analysis of the nullspace of complex reaction networks, stoichiometric analysis has a long history in the chemical and biochemical sciences [59 62]. At the core of all stoichiometric approaches is the assumption of a stationary and time-invariant state of the metabolite concentrations S°. As already specified in Eq. (6), the steady-state condition... 

The use of HPLC to analyze biogenic amines and their acid metabolites is well documented. HPLC assays for classical biogenic amines such as norepinephrine (NE), epinephrine (E), dopamine (DA), and 5-hydroxytryptamine (5-HT, serotonin) and their acid metabolites are based on several physicochemical properties that include a catechol moiety (aryl 1,2-dihydroxy), basicity, easily oxidized nature, and/or native fluorescence characteristics (Anderson, 1985). Based on these characteristics, various types of detector systems can be employed to assay low concentrations of these analytes in various matrices such as plasma, urine, cerebrospinal fluid (CSE), tissue, and dialysate. 

The determination of endogenous compounds and drugs in biological matrices has always presented a formidable challenge as one has to consider various factors before attempting to develop a suitable HPLC assay. These include the physicochemical properties of the compound such as the pKa value, solubility, volatility, particular functional groups (e.g., possessing chromophores, fluorophores, or electroactive characteristics), potential metabolites, and the required sensitivity and specificity. All these aspects will determine the type of extraction processes, analytical column selection, and suitable detector systems to be used as part of the HPLC apparatus. 

As a first approximation, we consider the main subsurface transformation processes to comprise reactions leading to chemical transformation or degradation and metabolite formation in the liquid phase or the solid-liquid interface and reactions resulting in complexation of chemicals, which in turn lead to a change in their physicochemical properties. 

METEOR S biotransformation rules are generic reaction descriptors, and the versatile structural representation used in the system allows each atom or bond to have specific physicochemical properties. This approach provides more details than simple hard-coded functional group descriptors (313), but this flexibility also can give rise to an avalanche of data. METEOR manages the amount of data by predicting which metabolites are to be formed rather than all the possible outcomes (310,312,314,315). At high certainty levels, when chosen, only the more likely biotransformations are requested. At lower likelihood levels, the more common metabolites are also selected for examination. Currently, METEOR knowledge-based biotransformations are exclusively for mammalian biotransformations (phase I and phase II) (314,315). 

While the above examples focus on safety matters associated with pharmacological off-targets, it has to be emphasized that the knowledge of physicochemical properties of compounds is equally important at any phase of drug discovery. For example, poor solubility and permeability can prevent decent exposure and extensive hepatic metabolism might create inactive or toxic metabolites. 

Blasticidin (52) is an antibiotic isolated from Streptomyces griseochro-mogenes in 1955 [87]. Detailed physicochemical properties were reported in 1968, but the structure remained undefined [88]. Interest in this metabolite was renewed recently with the isolation of the homologous compounds aflastatin A and B (53, 54), metabolites of S. griseochro-... 

Once a chemical is in systemic circulation, the next concern is how rapidly it is cleared from the body. Under the assumption of steady-state exposure, the clearance rate drives the steady-state concentration in the blood and other tissues, which in turn will help determine what types of specific molecular activity can be expected. Chemicals are processed through the liver, where a variety of biotransformation reactions occur, for instance, making the chemical more water soluble or tagging it for active transport. The chemical can then be actively or passively partitioned for excretion based largely on the physicochemical properties of the parent compound and the resulting metabolites. Whole animal pharmacokinetic studies can be carried out to determine partitioning, metabolic fate, and routes and extent of excretion, but these studies are extremely laborious and expensive, and are often difficult to extrapolate to humans. To complement these studies, and in some cases to replace them, physiologically based pharmacokinetic (PBPK) models can be constructed [32, 33]. These are typically compartment-based models that are parameterized for particular... 

Figure 15.4 Structures of DDT, methoxychlor, and their major metabolites, and toxicological and key physicochemical properties. Data from [132, 135, 141, 210].

MPTP is also metabolized by other routes involving cytochromes P-450, FAD-dependent monooxygenases, and aldehyde oxidase. However, these seem to be detoxication pathways, as they divert MPTP away from uptake and metabolism in the brain. However, MPTP may inhibit its own metabolism by cytochromes P-450 and thereby reduce one means of detoxication. This example illustrates the importance of structure and physicochemical properties in toxicology. MPTP is sufficiently lipophilic to cross the blood-brain barrier and gain access to the astrocytes. The structure of the metabolite is important for uptake via the dopamine system, hence localizing the compound to a particular type of neuron. Again, uptake into mitochondria is presumably a function of structure, as a specific energy-dependent carrier is involved. 

Owing to the extraordinary diversity of the chemical structure and physicochemical properties of metabolites, there is no a single analytical platform or methodology capable to detect, quantify, and identify all metabolites in the same analysis. Two major analytical platforms are currently used for... 

Maquille et al. [121], due to the physicochemical properties (i.e., polarity and ionization state) of the investigated drugs (opiates, amphetamine, cocaine and metabolites), concluded that LLE should be selected. To automate the sample preparation procedure, this team proposed urine extraction by supported liquid-liquid extraction (SLE), a promising technique that appeared in 1997 [122], which can be easily automated in a 96-well plate format. It has been demonstrated that matrix effect is significantly minimized. 

The metabolome refers to the entire collection of metabolites, including lipids, sugars, amino acids, and nucleosides within an organism [2]. Though there is still some debate as to the exact number of metabolites, the current estimate is 6,800 human metabolites [25]. Compared to large biopolymers consisting of thousands of atoms, such as proteins and nucleic acids, the structures of many metabolites seem simple. However, this simplicity masks the unique challenge associated with analysis of the metabolome due to the distinct physicochemical properties of different classes of metabolites. For example, the isolation and analysis protocols... 

Fig. I The typical metabolomics workflow has three key steps the isolation of metabolites, detection of the metabolites, and data analysis. The isolation step is typically determined by the class of metabolite being measured because of the physicochemical properties of different metabolite classes (i.e., hydrophobic, hydrophilic), which require different enrichment protocols. Two principle methods for metabolite detection are NMR- and MS-based methods. Finally, the data analysis can be performed in a variety of ways depending on the problem...

The structure of a compartmental PK model is given by the number of compartments being used and the way the compartments are connected. For most drugs the plasma concentration-time profiles can be sufficiently described by one-, two-or three-compartment models. A one-compartment model assumes that no time is necessary for the distribution of the drug and the whole distribution occurs within this one compartment. The two-compartment model implements in addition to a central compartment a peripheral compartment which allows the description of distribution processes of the compound in, e.g. tissues with different physicochemical properties. The three-compartment model provides an additional compartment for distribution processes. The use of more than three compartments is quite rare, but there are some situations where the model can get quite difficult, e.g. if the concentration-time profile of metabolites are also considered within the model. For more information regarding compartment models, refer to Rowland and Tozer... 

In contrast to GC, liquid chromatography hyphenated with mass spectrometry (LC-MS) does not require a derivatization step before sample analysis. Separation of metabolite from sample matrix is achieved using chromatography columns with various stationary phases of different physicochemical characteristics. LC-MS is more often used than GC-MS because it is more suitable for unstable compounds, compounds difficult to derivatize, and nonvolatile compounds [6, 7]. Therefore, a wider range of metabolites with various physicochemical properties can be determined using LC-MS. Moreover, the sample pretreatment procedure is much simpler, which can have a great impact on minimization of analytical variability. 

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