Fig. 1
From: A beginner’s approach to deep learning applied to VS and MD techniques
Overview of the DEEPScreen architecture. Each prediction model included in DEEPScreen takes as input small molecule ligands in the form of SMILES representations, transforms them into 200-by-200 pixel 2D structural images, and then runs a predictive CNN model on them in order to predict whether these ligands are either active (i.e., interacting) or inactive (i.e., non-interacting) against a specific target protein [36]