posted on 2016-09-26, 17:22authored byPaul Czodrowski, Wolf-Guido Bolick
The prediction of molecular targets
is highly beneficial during
the drug discovery process, be it for off-target elucidation or deconvolution
of phenotypic screens. Here, we present OCEAN, a target prediction
tool exclusively utilizing publically available ChEMBL data. OCEAN
uses a heuristics approach based on a validation set containing almost
1000 drug ← → target relationships. New ChEMBL data
(ChEMBL20 as well as ChEMBL21) released after the validation was used
for a prospective OCEAN performance check. The success rates of OCEAN
to predict correctly the targets within the TOP10 ranks are 77% for
recently marketed drugs and 62% for all new ChEMBL20 compounds and
51% for all new ChEMBL21 compounds. OCEAN is also capable of identifying
polypharmacological compounds; the success rate for molecules simultaneously
hitting at least two targets is 64% to be correctly predicted within
the TOP10 ranks. The source code of OCEAN can be found at http://www.github.com/rdkit/OCEAN