Dataset Information

Kim2022 - BayeshERG: A deep learning model for predicting hERG channel blockers

ABSTRACT: BayeshERG is a predictor of small molecule-induced blockade of the hERG ion channel. To increase its predictive power, the authors pretrained a bayesian graph neural network with 300,000 molecules as a transfer learning exercise. The pretraining set was obtained from Du et al, 2015, and the fine tuning dataset is a collection of 14,322 molecules from public databases (8488 positives and 5834 negatives). The model was validated on external datasets and experimentally, from 12 selected compounds (>0.95 probability) one candidate showed strong hERG inhibition (IC 50 Model Type: Predictive machine learning model. Model Relevance: Prediction of hERG channel blockade probability br> Model Encoded by: Azycn (Ersilia) Metadata Submitted in BioModels by: Zainab Ashimiyu-Abdusalam Implementation of this model code by Ersilia is available here: https://github.com/ersilia-os/eos4tcc

SUBMITTER: Zainab Ashimiyu-Abdusalam