CLogP versus CLogD
structurally related compounds and correlations with aqueous solubility (Cw phases in the HPLC, there is a good correlation between Kow and retention grade methanol; anthracene, benzene, biphenyl, bisphenol-A, bromobenzene, 1- . As such, relationships between biological activities and log P can be An automated version of this method, CLOGP,8,9 .. bisphenol. It is important to realize that LogP is defined as the partition coefficient of the neutral molecule in octanol/water. The distribution coefficient is given by logD.
Moreover, since the value of log P is determined by linear regressionseveral compounds with similar structures must have known log P values, and extrapolation from one chemical class to another—applying a regression equation derived from one chemical class to a second one—may not be reliable, since each chemical classes will have its characteristic regression parameters.
octanol water partition: Topics by changethru.info
The method does, however, require the separate determination of the pKa value s of the substance. Electrochemical[ edit ] Polarized 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. 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. For example, tens of thousands of industrially manufactured chemicals are in common use, but only a small fraction have undergone rigorous toxicological evaluation.
Hence there is a need to prioritize the remainder for testing.
QSAR equations, which in turn are based on calculated partition coefficients, can be used to provide toxicity estimates. Other prediction methods rely on other experimental measurements such as solubility. The methods also differ in accuracy and whether they can be applied to all molecules, or only ones similar to molecules already studied.
Atom-based Standard approaches of this type, using atomic contributions, have been named by those formulating them with a prefix letter: A conventional method for predicting log P through this type of method is to parameterize the distribution coefficient contributions of various atoms to the overall molecular partition coefficient, which produces a parametric model. This parametric model can be estimated using constrained least-squares estimationusing a training set of compounds with experimentally measured partition coefficients.
Partition coefficient - Wikipedia
While this method is generally the least accurate, the advantage is that it is the most general, being able to provide at least a rough estimate for a wide variety of molecules. It has been shown that the log P of a compound can be determined by the sum of its non-overlapping molecular fragments defined as one or more atoms covalently bound to each other within the molecule.
Whilst the correlation was good in many cases, there were some significant outliers, so he came to ask me, the computational chemist, to see if I might explain why the calculated logP was so different.
There were some obvious structural features that can beguile certain methods of calculating logP — yes, there is more than one method of calculating logP — and other methods might closer predict the outlier values in our case. Whilst there are a range of methods for prediction, there are three basic groups, and the vast majority of the current methods are flavours thereof: It is suited to smaller molecules, particularly those with non-complex aromaticity or those which do not contain electronic systems that are known to have unexpected contributions to logP.
This is an attempt to allow for larger electronic effects. It is fast, being a table look-up technique, and many free software use this too.
The smarter hybrid algorithms know the state of each atom and thus how much of a contribution its neighbours add. Fragment contributions are then added up, with correction factors.
The rationale here is that sometimes atomistic approaches do not adequately model the nuances of electronic or intramolecular interactions, which may be better modelled by using whole fragments. This method tends to be better for systems with complex aromaticity, and larger molecules — on the condition that the molecule contains features that are similar to those from which the modelling was conducted.
In the case of very obscure motifs in your molecules, then the model from which the prediction is made may not have a very good correlation. Property based methods… There are a whole host of methods for determining logP using properties, empirical approaches, 3-D structures e. Most of these methods are reasonably computationally intense, and are buried in the world of informatics and stats, but one is worthy or particular note: It is very fast, and so historically it was employed for large datasets, and was included in several property prediction software, such as Dragon, and ADMET Predictor Simulations Plus, Inc.