Partition coefficient

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A partition coefficient or distribution coefficient is a measure of differential solubility of a compound in two solvents. The logarithmic ratio of the concentrations of the solute in the solvent is called log P (sometimes LogP). The best known of these partition coefficients is the one based on the solvents octanol and water. The octanol-water partition coefficient ^[1] is a measure of the hydrophobicity and hydrophilicity of a substance. In the context of drug-like substances, hydrophobicity is related to absorption, bioavailability, hydrophobic drug-receptor interactions, metabolism and toxicity. In the field of hydrogeology, the octanol water partition coefficient, or K_ow, is used to predict and model the migration of dissolved hydrophobic organic compounds in soil and groundwater.

Contents 1 Application 1.1 Shake flask (or tube) method 1.2 HPLC determination 1.3 Electrochemical methods 2 Prediction 3 Limitations 4 See also 4.1 LogP calculators 5 References

[edit] Application

[edit] Shake flask (or tube) method

The classical and most reliable method of log P determination is the shake-flask method, which consists of mixing a known amount of solute in a known volume of octanol and water, then measuring the distribution of the solute in each solvent. The most common method of measuring the distribution of the solute is by UV/VIS spectroscopy. There are a number of pros and cons to this method:

Pros:

• Most accurate method
• Accurate for broadest range of solutes (neutral and charged compounds applicable)
• Chemical structure does not have to be known beforehand.

Cons:

• Time consuming (>30 minutes per sample)
• Octanol and water must be premixed and equilibrated (takes at least 24 hours to equilibrate)
• Complete solubility must be attained.
• The concentration vs. UV-Vis response must be linear over the solute's concentration range. (See Beer-Lambert law)

As an alternative to UV/VIS spectroscopy other methods can be used to measure the distribution, one of the best is to use a carrier free radiotracer. In this method (which is well suited for the study of the extraction of metals) a known amount of a radioactive material is added to one of the phases. The two phases are then brought into contact and mixed until equilibrium has been reached. Then the two phases are separated before the radioactivity in each phase is measured. If an energy dispersive detector can be used (such as a high purity germanium detector) then it is possible to use several different radioactive metals at once, with the more simple gamma ray detectors it is only possible to use one radioactive element in the sample.

If the volume of both of the phases are the same then the math is very simple.

For a hypothetical solute (S)

D or P = radioactivity of the organic phase / radioactivity of the aqueous phase

D or P = [S_{organic]/[Saqueous]}

_{In such an experiment using a carrier free radioisotope the solvent loading is very small, hence the results are different from those which are obtained when the concentration of the solute is very high. A disadvantage of the carrier free radioisotope experiment is that the solute can absorb on the surfaces of the glass (or plastic) equipment or at the interface between the two phases. To guard against this the mass balance should be calculated.}

_{It should be the case that}

_{radioactivity of the organic phase + radioactivity of the aqueous phase = initial radioactivity of the phase bearing the radiotracer}

_{For nonradioactive metals, it is possible in some cases to use ICP-MS or ICP-AES. Sadly ICP methods often suffer from many interferences which do not apply to gamma spectrscopy so hence the use of radiotracers (counted by gamma ray spectrscopy) is often more straightforward.}

_{[edit] HPLC determination}

_{A faster method of log P determination makes use of high-performance liquid chromatography. The log P of a solute can be determined by correlating its retention time with similar compounds with known log P values.}

_Pros:

• _{Fast method of determination (5-20 minutes per sample)}

_Cons:

• _{The solute's chemical structure must be known beforehand.}
• _{Since the value of log P is determined by linear regression, several compounds with similar structures must have known log P values.}
• _{Different chemical classes will have different correlation coefficients, between-class comparisons are not significant.}

_{[edit] Electrochemical methods}

_{In the recent past some experiments using polarised liquid interfaces have been used to examine the thermodynamics and kinetics of the transfer of charged species from one phase to another. Two main methods exist.}

• _{ITIES, Interfaces between two immiscible electrolyte solutions which for example has been used at Ecole Polytechnique Fédérale de Lausanne. [1]}
• _{Droplet experiments which have been used by Alan Bond, Frank Marken[2] and also by the team at the Ecole Polytechnique Fédérale de Lausanne. Here a reaction at a triple interface between a conductive solid, droplets of a redox active liquid phase and an electrolyte solution have been used to determine the energy required to transfer a charged species across the interface.}

_{[edit] Prediction}

_{QSAR algorithms calculate a log P in several different ways:}

• _{Fragment based prediction (group contribution)}

_{It has been shown that the log P of a compound can be determined by the sum of its fragments. Fragmentary log P values have been determined statistically. This method gives mixed results and is generally not trusted to have accuracy of more than ±0.1 units.}

• _{Data mining prediction}

_{A typical data mining based prediction uses e.g. support vector machines, decision trees, neural networks are usually very successful for calculating log P values when trained with compounds that have similar chemical structures and known log P values.}

• _{Molecule mining prediction}

_{Molecule mining approaches apply a similarity matrix based prediction or an automatic fragmentation scheme into molecular substructures. Furthermore there exist also approaches using maximum common subgraph searches or molecule kernels.}

_{[edit] Limitations}

_{LogP is not an accurate determinant of solubility for ionizable compounds because it only correctly describes the partition coefficient of neutral (uncharged) molecules. Taking the example of drug discovery we see how the limitations of logP can effect research. Since the majority of drugs (approximately 80%) are ionizable, logP is not an appropriate predictor of a compound's behaviour in the changing pH environments of the body. The distribution coefficient (LogD) is the correct descriptor for ionizable systems.}

_{[edit] See also}

• _{Cheminformatics}
  • _QSAR
  • _ADME
  • _{Molecule mining}

_{[edit] LogP calculators}

• _{ACD/LogP DB}
• _{Chemistry Development Kit}
• _JOELib
• _{ALOGPS Free on-line calculations and comparison of 7 logP methods}
• _{Free online logP calculations using ChemAxon's Marvin and Calculator Plugins - requires Java}
• _{an overview of on-line WWW resources for logP and other PhysProp calculations}

_{There are many logP calculators or predictors available both commerically and for free (ACD/LogP DB and CLogP among them). The use of this particular descriptor by Christopher A. Lipniski in his publication about the 'Rule of Five' has made it a commonly understood term in the medicinal chemistry world.}

_{[edit] References}

1. _{^ J. Sangster, Octanol-Water Partition Coefficients: Fundamentals and Physical Chemistry, Vol. 2 of Wiley Series in Solution Chemistry, John Wiley & Sons, Chichester, 1997.}