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 (R2) and leave-one-out correlation coefficients (Rcv2): R2 = 0.881–0.983; Rcv2=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 (R2 = 0.911–0.974; Rcv2=0.831–0.936). A mixed pool of molecular and fragment descriptors did not lead to significant improvement of the models.

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