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Physical & Chemical properties

Partition coefficient

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partition coefficient
Type of information:
calculation (if not (Q)SAR)
Adequacy of study:
key study
Study period:
2 (reliable with restrictions)
Rationale for reliability incl. deficiencies:
accepted calculation method
Justification for type of information:
EpiWin calculation
EpiSuite / KOWWIN v1.68

2. MODEL (incl. version number)
EpiSuite 4.1
KOWWIN v1.68

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Principles of method if other than guideline:
KOWWIN uses a "fragment constant" methodology to predict log P.  In a "fragment constant" method, a structure is divided into fragments (atom or larger functional groups) and coefficient values of each fragment or group are summed together to yield the log P estimate.   KOWWIN’s methodology is known as an Atom/Fragment Contribution (AFC) method.  Coefficients for individual fragments and groups were derived by multiple regression of 2447 reliably measured log P values.  KOWWIN’s "reductionist" fragment constant methodology (i.e. derivation via multiple regression) differs from the "constructionist" fragment constant methodology of Hansch and Leo (1979) that is available in the CLOGP Program (Daylight, 1995).  See the Meylan and Howard (1995) journal article for a more complete description of KOWWIN’s methodology.

To estimate log P, KOWWIN initially separates a molecule into distinct atom/fragments.  In general, each non-hydrogen atom (e.g. carbon, nitrogen, oxygen, sulfur, etc.) in a structure is a "core" for a fragment; the exact fragment is determined by what is connected to the atom.  Several functional groups are treated as core "atoms"; these include carbonyl (C=O), thiocarbonyl (C=S), nitro (-NO2), nitrate (ONO2), cyano (-C/N), and isothiocyanate (-N=C=S).  Connections to each core "atom" are either general or specific; specific connections take precedence over general connections.  For example, aromatic carbon, aromatic oxygen and aromatic sulfur atoms have nothing but general connections; i.e., the fragment is the same no matter what is connected to the atom.  In contrast, there are 5 aromatic nitrogen fragments: (a) in a five-member ring, (b) in a six-member ring, (c) if the nitrogen is an oxide-type {i.e. pyridine oxide}, (d) if the nitrogen has a fused ring location {i.e. indolizine}, and (e) if the nitrogen has a +5 valence {i.e. N-methyl pyridinium iodide}; since the oxide-type is most specific, it takes precedence over the other four.  The aliphatic carbon atom is another example; it does not matter what is connected to -CH3, -CH2-, or -CH< , the  fragment is the same; however, an aliphatic carbon with no hydrogens has two possible fragments: (a) if there are four single bonds with 3 or more carbon connections and (b) any other not meeting the first criteria.

It became apparent, for various types of structures, that log P estimates made from atom/fragment values alone could or needed to be improved by inclusion of  substructures larger or more complex than "atoms"; hence, correction factors were added to the AFC method.  The term "correction factor" is appropriate because their values are derived from the differences between the log P estimates from atoms alone and the measured log P values.  The correction factors have two main groupings: first, factors involving aromatic ring substituent positions and second,  miscellaneous factors.  In general, the correction factors are values for various steric interactions, hydrogen-bondings, and effects from polar functional substructures.  Individual correction factors were selected through a tedious process of correlating the differences (between log P estimates from atom/fragments alone and measured log P values) with common substructures.

Two separate regression analyses were performed.  The first regression related log P to atom/fragments of compounds that do not require correction factors (i.e., compounds estimated adequately by fragments alone).  The general regression equation has the following form:

 log P  = Σ(fini ) +  b     (Equation 1)

where Σ(fini )  is the summation of fi (the coefficient for each atom/fragment) times ni (the number of times the atom/fragment occurs in the structure) and b  is the linear equation constant.  This initial regression used 1120 compounds of the 2447 compounds in the total training dataset.

The correction factors were then derived from a multiple linear regression that correlated differences between the experimental (expl) log P and the log P estimated by Equation 1 above with the correction factor descriptors.  This regression did not utilize an additional equation constant.  The equation for the second regression is:

 lop P (expl)  -  log P (eq 1)  = Σ(cjnj )       (Equation 1)

where Σ(cjnj )  is the summation of cj (the coefficient for each correction factor) times nj  (the number of times the correction factor occurs (or is applied) in the molecule).


Regression Results

Results of the two successive multiple regressions (first for atom/fragments and second for correction factors) yield the following general equation for estimating log P of any organic compound:

log P  = Σ(fini ) + Σ(cjnj ) + 0.229     (Equation 3)

(num = 2447,   r2 = 0.982,  std dev = 0.217,  mean error = 0.159)
Type of method:
calculation method (fragments)
Partition coefficient type:
log Pow
Partition coefficient:
20 °C
Remarks on result:
other: Assumed values for modelling
Log Kow = -2.93
Executive summary:

Log Kow (version 1.68 estimate): -2.93

Description of key information

Log Kow = -2.93

Key value for chemical safety assessment

Log Kow (Log Pow):
at the temperature of:
20 °C

Additional information