Those of you who follow this blog will know that I have a long standing interest in alkane/water partition coefficient and I’d like to tell you a bit about the ClogPalk model for predicting these from molecular structure that we published during my time in Brasil. Some years ago we explored prediction of ΔlogP (logPoct - logPalk) from calculated molecular electrostatic potentials and this can be thought of as treating the alkane/water partition coefficient as a perturbation of the octanol/water partition coefficient. One disadvantage of this approach is that it requires access to logPoct and I was keen to explore other avenues. The correlation of logPalk with computed molecular surface area (MSA) is excellent for saturated hydrocarbons and I wondered if this class of compound might represent a suitable reference state for another type of perturbation model. Have a look at Fig 1 which shows plots of logPalk against MSA for saturated hydrocarbons (green), aliphatic alcohols (red) and aliphatic diols (blue). You can see how adding a single hydroxyl group to a saturated hydrocarbon shifts logPalk down by about 4.5 units and adding two hydroxyl groups shifts logPalk further still.
The perturbations are defined substructurally using SMARTS notation. Specifically, each perturbation term consists of a SMARTS definition for the relevant functional group and a decrement term (e.g. 4.5 units for alcohol hydroxyl). The model also allows functional groups to interact with each other. For example, an intramolecular hydrogen bond ‘absorbs’ some of a molecule’s polarity and manifests itself as an unexpectedly high logPalk value. Take a look at this article if you’re interested in this sort of thing. The interaction terms can be thought of as perturbations of perturbations. The ClogPalk model is shown in Fig 2.
The performance of the model against external test data is shown in Figure 3. There do appear to be some issues with some of the data and measured values of logPalk were found to differ by two or more units for some compounds (Atropine, Propanolol, Papavarine). Also there are concerns about the self-consistency of the measurements for Cortexolone, Cortisone and Hydrocortisone. Specifically, the logPalk of Cortexolone (-1.00) is actually lower than that for its keto analogue Cortisone (-0.55).
The software was built using OpenEye programming toolkits (OEChem and Spicoli) and you’ll find the source code and makefiles in the supplementary information with all the data used to parameterize and test the models. It’s not completely open source because you’ll need a license from OpenEye to actually run the software. However, the documentation for the toolkits is freely available online and you may be even able to get an evaluation license to see how things work. You’ll also find the source code for SSProFilter in the supplemental material and this is an improved (it also profiles) version of the Filter program that I put together with the Daylight toolkit back in 1996. Very useful for designing screening libraries and you might want to take a look at this post on SMARTS from a couple of years ago.
There's some general discussion in the article that is not specific to the ClogPalk model and I'll mention it briefly since I think this is relevant to molecular design. Those of you who believe that the octanol/water partition coefficient is somehow fundamental might like to trace how we ended up with this particular partitioning system. We also address the question of whether logP or logD is the more appropriate measure of lipophilicity measure and some ligand efficiency stuff from an earlier post makes its journal debut.
That’s about all I wanted to say for now and I’ll finish by noting that the manuscript was originally submitted to another journal but that's going to be the subject of a post all of its very own...
Toulmin, Wood, Kenny (2008) Toward prediction of alkane/water partition coefficients. J Med Chem 51:3720-3730 DOIKenny, Montanari, Prokopczyk (2013)ClogPalk: A method for predicting alkane/water partition coefficient. JCAMD 27:389-402 DOI