LogD-Distribution coefficient
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[edit] LogD
The distribution coefficient (symbolised as K or D, and commonly used in its logarithmic form logD) is a measure of the distribution of a solute between two phases for example, an organic solvent and water (the most commonly used system being octanol-water). In simple terms it describes the pH dependent hydrophobicity of compounds. It is related to logP (the partition coefficient), which describes the hydrophobicity of neutral compounds only.
[edit] Applications
An understanding of the hydrophobicity (or lipophilicity) of a compound is important for a wide range of industries.
Environmental-the hydrophobicity of a compound can give scientists an indication of how easily a compound might be taken up in groundwater to pollute waterways, and its toxicity to animals and aquatic life. LogD may be measured or predicted for compounds currently causing problems or with foresight to gauge the structural modifications necessary to make a compound environmentally friendly in the research phase.
Pharmaceutical-one of the most significant challenges in drug discovery is to make an active compound into an effective drug. In early discovery much effort is put into selecting compounds that are drugable. Hydrophobicity is important because it helps to determine the pharmacodynamic (PD), pharmacokinetic (PK) and, adsorption, distribution, metabolism and excretion (ADME) parameters. A compound that is too hydrophilic may be excreted too quickly to be effective. On the other hand a compound that is too hydrophobic may not cross biological membranes, or may be sequestered by fatty tissue and become toxic.
Agrochemical-this application somewhat combines the concerns of the two industries already discussed. On one hand agrochemists must produce insecticides and herbicides that will reach and act upon the intended target. On the other hand the environmental impact of any by-products must be kept to a minimum.
Many other industries also use logD for example in formulation of make-up or medications, paints and dyes and many other chemical processes.
[edit] Prediction
LogD can be calculated many different ways. One example is the fragment-based approach of the calculator ACD/LogD. Neural net predictors are also available.
