Predicting Drug Mechanics by Deep Learning on Gene and Cell Activities

The identification of protein target and mechanism of disease are fundamentally important in drug discovery. A pipeline for predicting mechanism of action (MoA) for drug molecules based on gene expression and cell viability data is developed and demonstrated on experimental data. A deep learning network learns the known MoAs over thousands of gene expression and cell viability training data and is shown to predict the unknown MoAs over test data with high efficacy.