Gm. Crippen, VALIDATION OF EGSITE2, A MIXED-INTEGER PROGRAM FOR DEDUCING OBJECTIVESITE MODELS FROM EXPERIMENTAL BINDING DATA, Journal of medicinal chemistry, 40(20), 1997, pp. 3161-3172
EGSITE2 represents a substantial advance in a long series of methods f
or calculating receptor site models given only specific binding data.
Compared to our most recently reported technique, EGSITE [Schnitker et
al. J. Comput.-Aided Mel. Des. 1997, 11, 93-110] the user no longer h
as to simplify the structures of the molecules in the training set by
clustering the atoms into a few superatoms. The only remaining source
of subjectivity is the user's choice of compounds for the training set
, which can be surprisingly few in number. Then EGSITE2 automatically
produces typically several different models that explain the observed
binding without outliers. The models are remarkably simple but have su
bstantial predictive power for any sort of test compound, with an esti
mation of the uncertainty of the prediction. Validation of the method
is reported for four standard test cases: triazines and pyrimidines bi
nding to dihydrofolate reductase, steroids binding to corticosteroid-b
inding globulin and to testosterone-binding globulin, and peptides bin
ding to angiotensin-converting enzyme.