Protein partition coefficient, dependence

This investigation has enhanced our understanding of the factors which contribute to the molecular weight dependence of protein partitioning. The molecular weight dependence of the protein partition coefficient results from a competition between two terms in the partition coefficient expansion, namely the crossed second virial coefficient and the differences between the polymer concentrations in the top and bottom phases. While the trend in binodal concentrations tends (in part) to favor the trends observed experimentally, the trend in the second virial coefficient tends to oppose the experimental trends. 

If we assume that Equations 28 and 29 are valid, that the solvent and solution are incompressible, and that the solvent is non-interacting, we can use Equation 14 to investigate the dependence of the partition coefficient on the nature of the interactions between the species. To obtain the protein partition coefficient, the protein chemical potentials given by Equation 14 are equated in both phases. Since the reference chemical potentids are the same in both phases, we obtain ... 

DEPENDENCE OF THE PROTEIN PARTITION COEFFICIENT POLYMER AND PROTEIN MOLECULAR WEIGHTS... 

Figure 1. Dependence of protein partition coefficient, Kp, on PEO molecular weight in a PEO-dextran-water two-phase system. In order of increasing size the proteins are (open circles) cytochrome-c, (filled circles) ovalbumin, (open diamonds) bovine serum albumin, (triangles up) lactate dehydrogenase, (triangles down) catalase, (open squares) pullulanase, (filled diamonds) phosphorylase. Data compiled from (26,27). The solid lines are drawn to guide the eye.

Dmg distribution into tissue reservoirs depends on the physicochemical properties of the dmg. Tissue reservoirs include fat, bone, and the principal body organs. Access of dmgs to these reservoirs depends on partition coefficient, charge or degree of ionization at physiological pH, and extent of protein binding. Thus, lipophilic molecules accumulate in fat reservoirs and this accumulation can alter considerably both the duration and the concentration—response curves of dmg action. Some dmgs may accumulate selectively in defined tissues, for example, the tetracycline antibiotics in bone (see Antibiotics,tetracyclines). 

In an early, quite elaborate model for the diffusion through the stratum corneum, Michaels et al. derived an equation for diffusion through a two-dimensional brick-and-mortar structure [50], In this model, stratum corneum permeability for a given compound depended only on two parameters one was the product of the partition coefficient between the protein and the donor phase /fprot/donor and the diffusion coefficient in the protein phase >Prot the other was the product of the partition coefficient between the lipid and protein phases Aip/prot and the ratio of the diffusion coefficients in the two phases... 

A model-based dependence of human tissue-blood partition coefficients of chemicals on lipophilidty and tissue composition was recently described [78], For 36 neutral chemicals, the partitioning between seven different tissues and blood in humans was modeled, considering accumulation in the membrane, protein binding, and dis-... 

Here too, species differences are reported, but this parameter is accessible to in vitro studies. Both protein-binding and passive reabsorption, factors that determine the rate of renal excretion, are related to the partition coefficients of the compounds119,12°. The half-life of various non- or poorly metabolized sulfanilamides is strongly dependent on the partition coefficient, as can be seen from Fig. 13121. ... 

Parameter Values Aside from the dependent and independent variables in the equations above, a variety of parameters must be specified. These include physiological parameters (e.g., ventilation rates, cardiac output, organ volumes and masses), physicochemical parameters (e.g., tissue partition coefficients, protein binding constants), and biochemical parameters (e.g., Km and Vmax). 

All structure-activity predictions, whether by human or computer, are based on the belief that the biological activity of a chemical is determined by its structure. At a general level, activity depends on properties such as fat-water partition coefficient, water solubility, acidity, and volatility, which are governed by the structure of a chemical and many of which can be calculated fairly well using algorithms based on structure-property relationships (see Chapter 9). At a more specific level, binding to proteins, including the active sites of enzymes, depends on features of chemical structure that may extend over most of the molecule or only over a relatively small part of it. Such features are commonly called pharmacophores or, in the case of toxins, toxico-phores or sometimes toxophores. 

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