30% Increase of the hERG Inhibition Module Training Library
- You can now predict hERG inhibition for drug-like compounds with greater confidence. The internal self-training library of the hERG Inhibition module (GALAS predictor) has been expanded from ~6700 compounds to ~9400 compounds.
- The new data represents novel congeneric series from recent lead optimization studies expanding the applicability domain of the algorithm for many new classes of drug-like compounds
Quantitative Prediction of hERG Inhibition Using Physicochemical Property Values
- When you use the physicochemical predictor, you can now quantitatively predict hERG inhibition, previously the prediction was probabilistic.
- The predicted value is an estimate of the half-inhibitory constant (IC50) in µM
- The heatmap helps you visualize hERG inhibition propensity in terms of estimated pIC50 values
Import Training Libraries in All Major File Types
- You can now import training libraries into ADME Suite using the following file types, in addition to SDF:
- Tab-delimited text (*.TXT)
- Comma-separated value (*.CSV)
Ease of Use Improvements
- We have streamlined “Context Help” to reduce the overlap between configurable extended tooltips and standard hints