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HSP Application note #10

Hansen Solubility Parameters (HSP) and Endocrine Disruptor

2010.2.22

HSPiP Team Senior Developer, Dr. Hiroshi Yamamoto

 

Endocrine disruptors are exogenous substances that act like hormones in the endocrine system and disrupt the physiologic function of endogenous hormones. They are sometimes also referred to as hormonally active agents or endocrine disrupting chemicals/compounds (EDC). Studies have linked endocrine disruptors to adverse biological effects in animals, giving rise to concerns that low-level exposure might cause similar effects in human beings. (WikiPedia)

DDT

I compiled Endocrine Disruptor compounds and logBCF(bio concentration factor), logP, logS data.

name Code LogBCF logP logS
alachlor 20878 1.1206 3.52 -1.62
aldrin 20487 3.7404 6.5 -5.77
atrazine 10806 0.9 2.61 -2.46
benzophenone 7761 1.0792 3.18 -2.12
butyl benzyl phthalate 6450 1.2129 4.73 -3.57
bisphenol A 7765 1.6415 3.32 -1.82
carbaryl 20504 0.9542 2.36 -1.96
trans-, cis-chlordane 20489 4.2911 6.16 -5.25
cypermethrin 20985 2.62 6.6 -6.40
p,p' -DDT 12873 4.2923 6.91 -6.26
p,p'-DDE 20491 4.08 6.51 -5.40
di-n-butyl phthalate 5449 2.2227 4.5 -2.95
2,4-dichlorophenol 8867 1.5302 3.06 -0.55
dieldrin 20638 3.9516 5.4 -4.71
diethylhexyl phthalate 5540 2.7694 7.6 -4.57
endrin 20641 3.8739 5.2 -4.60
fenvalerate 20982 2.8463 6.2 -5.62
HCB 9058 4.331 5.73 -6.30
hexachlorocyclohexane, BHC 20741 2.57 -3.10
heptachlor 20492 3.9428 6.1 -4.74
kelthane 20683 3.7853 5.02 -4.10
malathion 16548 1.5212 2.36 -1.84
4-nitrotoluene 7576 0.9031 2.37 -1.49
octachlorostyrene 20919 3.9085
PCDDs 20524 4.9868 6.8 -7.70
PCDFs 20981 3.608 6.53 -7.16
pentachlorphenol 9142 2.6628 5.12 -2.85
nonylphenol 7767 2.1903 -3.20
simazine 20697 0.5647 2.18 -3.21
trifluralin 20527 3.3579 5.34 -4.74

Largest logS is -0.55, so all compounds are relatively hydrophobic compounds.
But I can not categorize compounds with logBCF, logP, logS.

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.

So, I calculated HSP for each molecules with HSPiP, and start analyze with SOM (Self Organization Map) neural network.

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.

 

ID LogBCF dD dP dH sqrt(Volume)
20878 1.1206 18.6 8.3 5.7 15.5
20487 3.7404 19.7 9.4 0.8 14.9
10806 0.9 18.4 8.6 12.8 13.4
7761 1.0792 20.4 7.5 4.6 12.8
6450 1.2129 18.5 8.2 3.9 16.7
7765 1.6415 19.0 5.9 12.1 14.5
20504 0.9542 19.6 9.6 7.6 12.9
20489 4.2911 19.4 12.7 1.4 15.4
20985 2.62 19.1 7.1 5.2 18.1
12873 4.2923 20.1 3.9 2.9 15.8
20491 4.08 20.5 6.6 3.2 15.1
5449 2.2227 17.3 8.1 3.7 16.3
8867 1.5302 19.9 8.1 12.0 10.9
20638 3.9516 20.0 11.0 1.2 15.0
5540 2.7694 16.8 5.6 3.4 19.9
20641 3.8739 20.0 11.0 1.2 15.0
20982 2.8463 19.4 6.2 5.3 18.7
9058 4.331 21.2 4.5 3.1 12.5
20741 2.57 18.3 15.9 4.1 14.1
20492 3.9428 19.4 11.5 1.1 14.8
20683 3.7853 20.5 4.4 7.8 15.8
16548 1.5212 15.2 8.6 9.3 16.4
7576 0.9031 19.4 7.2 4.1 11.0
20919 3.9085 20.9 5.7 2.3 14.3
20524 4.9868 20.7 5.1 4.9 14.1
20981 3.608 21.5 5.0 3.8 13.7
9142 2.6628 20.8 4.9 9.4 12.1
7767 2.1903 17.2 3.8 6.7 15.6
20697 0.5647 18.7 9.2 13.9 12.8
20527 3.3579 18.0 5.8 3.3 16.2

SOM: Self Organization Map Neural Network 

The 2D Map of "Smilar vector map to similar 2D position".

If we split dH to dHdo, dHac then HSP vector become 4 dimensions.
That is the very bad news for user. Because the Sphere and GUI can not expand to 4 dimensions.
So we start to develop SOM program to check vector similarity.

Pirika JAVA Demo Applet calculate SOM. SOMDemo is available here.

 

Input vector for SOM is [dD, dP, dH, sqrt(Volume)].
And SOM arrange similar vectors to near position.
I think there are 6 categories for these compounds.

Code no name
dD
dP
dH
sqrt(V) Cl LogBCF
5449 12 di-n-butyl phthalate
17.3
8.1
3.7
16.3 0 2.22
20985 9 cypermethrin
19.1
7.1
5.2
18.1 2 2.62
6450 5 butyl benzyl phthalate
18.5
8.2
3.9
16.7 0 1.21
20527 30 trifluralin
18.0
5.8
3.3
16.2 0 3.36
20982 17 fenvalerate
19.4
6.2
5.3
18.7 1 2.85
Average
18.4
7.1
4.3
17.2 2.45
20491 11 p,p'-DDE
20.5
6.6
3.2
15.1 4 4.08
20919 24 octachlorostyrene
20.9
5.7
2.3
14.3 8 3.91
20981 26 PCDFs
21.5
5.0
3.8
13.7 4 3.61
9058 18 HCB
21.2
4.5
3.1
12.5 6 4.33
12873 10 p,p' -DDT
20.1
3.9
2.9
15.8 5 4.29
Average
20.8
5.2
3.0
14.3 4.04
20487 2 aldrin
19.7
9.4
0.8
14.9 6 3.74
20489 8 trans-, cis-chlordane
19.4
12.7
1.4
15.4 8 4.29
20492 20 heptachlor
19.4
11.5
1.1
14.8 7 3.94
20638 14 dieldrin
20.0
11.0
1.2
15.0 6 3.95
20641 16 endrin
20.0
11.0
1.2
15.0 6 3.87
Average
19.7
11.1
1.2
15.0 3.96
20683 21 kelthane
20.5
4.4
7.8
15.8 5 3.79
20524 25 PCDDs
20.7
5.1
4.9
14.1 4 4.99
7767 28 nonylphenol
17.2
3.8
6.7
15.6 0 2.19
20878 1 alachlor
18.6
8.3
5.7
15.5 1 1.12
Average
19.2
5.4
6.3
15.3 3.02
7761 4 benzophenone
20.4
7.5
4.6
12.8 0 1.08
20504 7 carbaryl
19.6
9.6
7.6
12.9 0 0.95
7576 23 4-nitrotoluene
19.4
7.2
4.1
11.0 0 0.90
Average
19.8
8.1
5.4
12.2 0.98
7765 6 bisphenol A
19.0
5.9
12.1
14.5 0 1.64
8867 13 2,4-dichlorophenol
19.9
8.1
12.0
10.9 2 1.53
16548 22 malathion
15.2
8.6
9.3
16.4 0 1.52
10806 3 atrazine
18.4
8.6
12.8
13.4 1 0.90
20697 29 simazine
18.7
9.2
13.9
12.8 1 0.56
Average
18.2
8.1
12.0
13.6 1.23
9142 27 pentachlorphenol
20.8
4.9
9.4
12.1 5 2.66
20741 19 hexachlorocyclohexane, BHC
18.3
15.9
4.1
14.1 6 2.57
5540 15 diethylhexyl phthalate
16.8
5.6
3.4
19.9 0 2.77

Green and yellow compounds are very similar. they have very large dD and small dH. The difference is dP.
Both compounds have a lot of chlorine atoms and logBCF is around 4.
With SOM calculation, I did not input Cl# nor logBCF, but SOM categorize very cleverly.
Blue compounds have very large dH.
Pink compounds’ HSP is very similar to Orange compounds’ HSP, but molecular size is small.
And logBCF is small.
Purple compounds may go other categories.
25 to green.
28 to Orange.
21 and 27 make new category.
1 become exception.

I do not know how Endocrine disruptor works, but if HSP is differ, solubility nature is differ.
So, human may have at least these 5 types endocrines that HSP is near to above categories.

21488   ESFENVALERATE 19.4 6.2 5.3 18.7 1 18.7
20764   heptachlor epoxide 19.7 13.1 1.5 14.9 7 14.9
20508   2,4-dichlorophenoxyacetic acid 19.8 8.6 10.7 12.3 2 12.3

If I want to categorize new molecules, I need just to calculate HSP using HSPiP.
And from that results, I know new compounds go where.

logP can do so little for this study.

Where do you think Benzo[a]pyrene goes?

11548 Benzo[a]pyrene 22.8 4.8 1.8 14.28285686 0 14.3

2011.4.25

Drag=Rotate, Drag+Shift=Larger/Smaller, Drag+Alt or Command(Window key)=Translate. This example, I did not use molecular volume.

If you are using HTML5 enable browser such as Chrome, Safari or FireFox (IE9 is out of support), you will see the Canvas. If you pick solvent, solvent name will appear.

In HSPiP, we have 10000 compounds in database.
So I search the green labeled range compounds.
dD= 20 - 22
dP= 4 - 6
dH= 2 -4

There are 66 compounds in DB.
Most of all are poly chlorine compounds.

But these compounds are also belong to green label range.
Are there EDC??

From the point of REACH Regulation, we’d better set these colored HSP area are grey zone.In reagent maker catalog or in ChenSpider like open database, if they are list HSP values, it will be very convenient for user to think about EDC.

If you have the Smiles structure of molecules, you can easily calculate HSE(Health, Safety, Health) properties with HSPiP.

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.

 

I checked perfomance of HSPiP V.3.1.X for these compounds.

Only one compound (HCode=21051) is out of line.

HCode 21051
logP=3.18
HCode 20877
logP=5.94
HCode 20927
logP=6.31

HCode 20928
logP=6.23
HCode 20929
logP=6.63
HCode 20931
logP=6.67

But other similar compounds logP is around 6, so maybe database value is not correct.

I don't know the version, other software SciQSAR or ScilogP prediction is not so good.

 

 

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.

 

Other topic of Bio Medical

GC data of class 1, class 2 solvents in Q3C:
HSP and Tamiflu Solubility parameter of Tamiflu or other H1N1 antiviral compounds
HSP for Rabbit: How to design eau de Cologne for rabbit. what LD50(skin, rabbit) means.
HSP and logP: logP, logKow, it is just HSP volume.
HSP and Carcinogenicity: SOM(self organization map) analysis of Poly-chlorinated compounds
HSP and Endocrine Disruptor: categorize by SOM.
HSP and AntimicroBial. Sulfa Drugs and other kind of Drugs.
Gall stone solubilizer: How to dissolve Cholesterol base Gall Stone.
Caco-2 cell monolayer apparent Permeability:SOM analysis