QSAR modeling of blood:air and tissue:air partition coefficients using theoretical descriptors.
Human blood:air, human and rat tissue (fat, brain, liver, muscle, and kidney):air partition coefficients of a diverse set of organic compounds were correlated and predicted using structural descriptors by employing CODESSA-PRO and ISIDA programs. Four and five descriptor regression models developed using CODESSA-PRO were validated on three different test sets. Overall, these models have reasonable values of correlation coefficients (R(2)) and leave-one-out correlation coefficients (R(cv)(2)): R(2) = 0.881-0.983; R(cv)(2) = 0.826-0.962. Calculations with ISIDA resulted in models based on atom/bond sequences involving two to three atoms with statistical parameters that were similar to those of models obtained with CODESSA-PRO (R(2) = 0.911-0.974; R(cv)(2) = 0.831-0.936). A mixed pool of molecular and fragment descriptors did not lead to significant improvement of the models.
Katritzky
Alan R
AR
Center for Heterocyclic Compounds, Department of Chemistry, University of Florida, Gainesville, 32611, USA. katritzky@chem.ufl.edu
Kuanar
Minati
M
Fara
Dan C
DC
Karelson
Mati
M
Acree
William E
WE
Solov'ev
Vitaly P
VP
Varnek
Alexandre
A
D000273:Adipose Tissue; D000388:Air; D000818:Animals; D001769:Blood; D001921:Brain; D006801:Humans; D007668:Kidney; D008099:Liver; D008956:Models, Chemical; D009132:Muscles; D021281:Quantitative Structure-Activity Relationship; D051381:Rats; D012984:Software