| Measuring
the degree to which a drug or other substance
becomes available to the target tissue after
administration is crucial in drug discovery.
This model predicts the total oral dose
of a drug that reaches the plasma upon absorption
in the gut and first pass metabolism.
In the Strand Bioavailability
model, developed by Strand Genomics, several
machine-learning methods including neural
networks, decision trees and support vector
machines were employed to identify a small
set from 1054 molecular descriptors that
correlated with this pharmacokinetic parameter.
The input to the
predictors is the 2-D structure of a molecule,
which is used to compute the descriptors
that are utilized by the models. Structures
may be imported as either SMILES, MOL, SYBYL MOL2, or SD
files.
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