kb2du-LigandScoringProtocol.txt

Name

ScaffOpt_score4

Software

LigPrep v33013
ScaffOpt

Parameters

Assumed pH 5 for ligand preparation.
-dt 'RDK5' -dt 'ErgFP' -dt 'ECFP' -dt 'FCFP' -dt '2Dpp' -binsize 0 -xmean 0.00001 -repbt 100 -hpnum 100 -of 'multi' for all 6 ScaffOpt runs.

Method

3D ligand conformations and tautomerization/ionization states were generated with LigPrep at target pH=5. In case of compounds with alternative tautomers/ionization states,
only the one with lowest LigPrep state penalty was used. CHEMBL was queried for similarity to the 3 CatS datasets ('score', 'FESet' and 'pose') and 6 assays were selected to be used by ScaffOpt algorithm as training set. These were (assay IDs): CHEMBL1048481, CHEMBL1103405, CHEMBL1103448, CHEMBL1173849, CHEMBL2318072, CHEMBL899800. ScaffOpt was executed 6 times, one for each assay. ScaffOpt is a fully-automatic machine learning algorithm that takes as input a few molecules with measured binding affinity (training set) and
scores a given screening database of compounds according to their predicted binding affinity to the receptor. The details of ScaffOpt algorithm will be described in a forth-coming
publication. For this submission no receptor information was used, only 2D structural information of the compounds. The predicted binding scores in this submission were
obtained for all 136 compounds using only assay CHEMBL2318072 as a training set at simcut level 0.0 ('simcut' is a ScaffOpt parameter that quantifies the similarity between the training set and the screening set).

Answer 1

No