PMID- 23672211
OWN - NLM
STAT- MEDLINE
DCOM- 20140320
LR  - 20130618
IS  - 1520-5851 (Electronic)
IS  - 0013-936X (Linking)
VI  - 47
IP  - 12
DP  - 2013 Jun 18
TI  - General model for estimating partition coefficients to organisms and their 
      tissues using the biological compositions and polyparameter linear free energy 
      relationships.
PG  - 6630-9
LID - 10.1021/es401772m [doi]
AB  - Equilibrium partition coefficients of organic chemicals from water to an organism 
      or its tissues are typically estimated by using the total lipid content in 
      combination with the octanol-water partition coefficient (K(ow)). This estimation 
      method can cause systematic errors if (1) different lipid types have different 
      sorptive capacities, (2) nonlipid components such as proteins have a significant 
      contribution, and/or (3) K(ow) is not a suitable descriptor. As an alternative, 
      this study proposes a more general model that uses detailed organism and tissue 
      compositions (i.e., contents of storage lipid, membrane lipid, albumin, other 
      proteins, and water) and polyparameter linear free energy relationships 
      (PP-LFERs). The values calculated by the established PP-LFER-composition-based 
      model agree well with experimental in vitro partition coefficients and in vivo 
      steady-state concentration ratios from the literature with a root mean squared 
      error of 0.32-0.53 log units, without any additional fitting. This model 
      estimates a high contribution of the protein fraction to the overall tissue 
      sorptive capacity in lean tissues (e.g., muscle), in particular for H-bond donor 
      polar compounds. Direct model comparison revealed that the simple lipid-octanol 
      model still calculates many tissue-water partition coefficients within 1 log unit 
      of those calculated by the PP-LFER-composition-based model. Thus, the 
      lipid-octanol model can be used as an order-of-magnitude approximation, for 
      example, for multimedia fate modeling, but may not be suitable for more accurate 
      predictions. Storage lipid-rich phases (e.g., adipose, milk) are prone to 
      particularly large systematic errors. The new model provides useful implications 
      for validity of lipid-normalization of concentrations in organisms, 
      interpretation of biomonitoring results, and assessment of toxicity.
FAU - Endo, Satoshi
AU  - Endo S
AD  - Department of Analytical Environmental Chemistry, UFZ-Helmholtz Centre for 
      Environmental Research, Permoserstrasse 15, D-04318 Leipzig, Germany.
FAU - Brown, Trevor N
AU  - Brown TN
FAU - Goss, Kai-Uwe
AU  - Goss KU
LA  - eng
PT  - Journal Article
PT  - Research Support, Non-U.S. Gov't
DEP - 20130529
PL  - United States
TA  - Environ Sci Technol
JT  - Environmental science & technology
JID - 0213155
RN  - 0 (Organic Chemicals)
SB  - IM
MH  - Models, Theoretical
MH  - Organic Chemicals/*chemistry
EDAT- 2013/05/16 06:00
MHDA- 2014/03/22 06:00
CRDT- 2013/05/16 06:00
PHST- 2013/05/16 06:00 [entrez]
PHST- 2013/05/16 06:00 [pubmed]
PHST- 2014/03/22 06:00 [medline]
AID - 10.1021/es401772m [doi]
PST - ppublish
SO  - Environ Sci Technol. 2013 Jun 18;47(12):6630-9. doi: 10.1021/es401772m. Epub 2013 
      May 29.