Hansen Solubility Parameter (HSP) and logP, logKow

HSP Application note #7

Hansen Solubility Parameter (HSP) and logP, logKow

2010.2.17

HSPiP Team Senior Developer, Dr. Hiroshi Yamamoto
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Hansen Solubility Parameters (HSP)

Hansen Solubility Parameters(HSP) were developed by Charles M. Hansen as a way of predicting if one material will dissolve in another and form a solution. They are based on the idea that "like dissolves like" where one molecule is defined as being 'like' another if it bonds to itself in a similar way.
Specifically, each molecule is given three Hansen parameters, each generally measured in MPa0.5:
dD:The energy from dispersion bonds between molecules
dP:The energy from dipolar intermolecular force between molecules
dH:The energy from hydrogen bonds between molecules.
These three parameters can be treated as Vector for a point in three dimensions also known as the Hansen space. The nearer two molecules HSP Vector are in this three dimensional space, the more likely they are to dissolve into each other.

What can perhaps be surprising is that one can assign HSP to so many different things. Gases like carbon dioxide, solids like carbon-60, sugar, and biological materials like human skin, depot fat, DNA, and even some proteins all have HSP. The list can be continued with drugs, polymers, plasticizers, and in fact any organic material and even many inorganic materials like salts. The only requirement for an experimental confirmation is that the material must behave differently in a sufficient number of test solvents upon contact.

Pirika JAVA Demo Applet calculate HSP. HSPLight is available here.
Please refer to e-Book of HSPiP if you want know more about HSP.
About the Power Tools that handle HSP more effectively.

LogP, logKow (Octanol/water partition ratio) is very important index in medical area, so we try to find out the relationship HSP and logP.

We show basic concept in above picture.
If the chemical is relatively easily dissolve to Octanol, HSP distance is small.

HSP Distance

To calculate the distance (Ra) between Hansen parameters in Hansen space the following formula is used:

HSP distance(Ra)={4*(dD1-dD2)2 + (dP1-dP2)2 +(dH1-dH2)2 }0.5

And made a lot of QSPR model but failed.

So, we start to examine logP more detail.

We extract only hydrocarbon data of logP from HSPiP database and plot of it.

HSPiP(Hansen Solubility Parameters in Practice)

The first edition of HSPiP that appeared in November, 2008, greatly enhanced the usefulness of the Hansen solubility parameters (HSP).

The HSP values of over 1200++ chemicals and 500 polymers are provided in convenient electronic format and have been revised and updated using the latest data sources in the second edition (March, 2009).

A third edition of the HSPiP appeared in March, 2010. There are now 10,000 compounds in the HSP file which also includes data on density, melting point, boiling point, critical parameters, Antoine constants and much more. The user is able to carry out many different sorts of optimisations of solubility, evaporation, diffusion, adhesion, create their own datasets (automatically if required) and explore the huge range of applications for HSP in coatings, paints, nanoparticles, cosmetics, pharma, organic photovoltaics and much more.

The 3rd Edition v3.1 was released on 12 December 2010. Current users can upgrade free (now v3.1.09) by downloading the latest .msi installer from http://hansen-solubility.com

The 4th Edition v4.0.x was released on 2 Jan. 2013. The Current users can upgrade with free charge.

2013.1.28 The Visual How to manual of HSPiP. You can understand what HSPiP can do.
Please check the Functional Group List whether your targets are available with HSPiP.
How to purchase HSPiP
2013..1.2 The HSPiP ver. 4 include Power Tools for HSPiP power user.

tot HSP = sqrt(dD^2 + dP^2 + dH^2) (vector length)
For plain hydrocarbon's dP and dH is almost 0, tot HSP is just dD.

With this result shows, if logP becomes large, even though dD is not change so much.
Some cyclic hydrocarbon's dD become large compare to chain type of hydrocarbon.
Larger hydrocarbon's logP become larger.

So, from fundamental reason, HSP can not estimate logP.

But when I build QSPR model I notice one thing.
In HSP concept, HSP volume play very important role and we have HSP volume column in Excel file. When I drew figure of QSPR model, I happened to plot logP vs HSP volume.

It have so beautiful correlation logP and HSP Volume.

So, we start to check other compounds.

At first, we extract halogenated compounds logP from our database and plot with HSP volume. It is completely identical with hydrocarbon line.
HSP volume become large according to F<Cl<Br<I.
But you do not need to know nature of F, Cl, Br, I to know logP.
It is governed just by Volume.
This result is very strange for us, because solubility parameter of Halogenated compounds are so different.
But for the logP, fact is that.

And we checked aromatic compounds without functional groups.
For these compounds, logP is just governed by HSP Volume.

For sulfur compounds, thiol compounds are identical with hydrocarbon's line.
thio-ether compounds make slightly upper line.
(this case, only one sulfur atom)

For only one functional group of alcohol(OH), Ether, Ketone, Aldehyde(ALD) compounds, these make upper line, but shift amount is almost same.
And the slope is identical to hydrocarbon's line.

This result is also so strange to us.
Alcohol is very easily dissolve to water and Ether is not.
So, at first, we thought alcohol line go much higher line to Ether line.
But from this result, alcohol is very easily dissolve to water but also dissolve to Octanol.
So, the ratio is identical.

And the lines are parallel, that means, one functional group of alcohol, Ether, Ketone, Aldehyde, it reduce HSP volume about 60.
Then the line become identical.

Carboxylic Acid(CA), Carbonate, Ester compounds are almost same with above theory.

we want to note one thing. Cyclic ester especially lactones goes much upper line.

Nitrogen containing compounds are also same with above theory.

Then we want to know multi functional compounds.
For Alcohol, we know one OH group reduce HSP Volume about 60.
And multi OH group case, it become almost same tendency.
You just reduce HSP Volume 60*OH number.

For ester, ether, combination of these functional groups, result is very easy to understand.

And if we determine Reduce Volume amount with using multiple Regression method,
we can get logP estimation scheme.
The result become very beautiful line.

So, we can conclude that logP is just determined by Volume and some functional group reduce Volume certain amount.
logP is not solubility related Index.

If you want to apply logP into permeability, bio-concentration or something, please think these results.

We know some exceptions.
Molecule have both COOH and amine, additivity will not work.
Some compounds that have (-OCH2CH2O)nOH, it will not work.
And more.

Anyway, our HSP solubility parameter method, we deal volume as it is.
And evaluate how materials and compounds interact.
"Like seeks like"

Try HSP if you failed to understand with only logP!!

Y-MB (implemented in HSPiP) break molecule into functional groups and predict a lot of thermo-chemical properties. I have 5689 data of logP in my database, and made estimation scheme for logP. You can calculate logP just input Smiles molecular structure and push calc. button.
Please use if you need to calculate logP beside HSP.

Smiles(Simplified Molecular Input Line Entry Syntax)

SMILES is a string obtained by printing the symbol nodes encountered in a depth-first tree traversal of a chemical graph.
"Organic subset" of B, C, N, O, P, S, F, Cl, Br, and I, brackets can be omitted.
Branches are described with parentheses, as in CCC(=O)O for propionic acid
Double and triple bonds are represented by the symbols '=' and '#'
Ring closure labels are used to indicate connectivity between non-adjacent atoms in the SMILES

Pirika JAVA Demo Applet getting Smiles. Draw2Smiles is available here.
Now we have Power Tool "Draw 2 Smiles", GUI HTML5 software on HSPiP ver. 4.

Y-MB Properties Estimation

Y-MB break Smiles into correspponding Functional Groups and Estimate various Properties. These estimation schemes are come from Pirika technologies.

Pirika JAVA Demo Applet calculate Properties. PirikaLight is available here.
Now we have Power Tool "Y-Predict", GUI HTML5 software on HSPiP ver. 4.

<p>Please Use HTML5 Browser</p>

If you want to know how to draw molecules, please refer to Power Tools applications. The full version of this estimation routine is implemented into Y-Predict Powert Tools in HSPiP ver. 4.

I put one example of prediction about hormonally active agents (endocrine disrupting chemicals) with Y-MB 3.1

If you want to know logP theory, please visit Pirka page
Newest estimation scheme of logP is implemented in HSPiP ver. 3.

2011.6.20

I rebuild JAVA program for iPad/iPhone with HTML5+CSS+JavaScript. logP calculator

Hansen Solubility Parameters(HSP) Application Notes

HSP Application note #7