Before revision:  With a few lines of code, DeepPurpose generates drug candidates based on aggregating five pretrained state-of-the-art models while offering flexibility for users to train their own models with 15 drug / target encodings and 50+ novel architectures.
After revision:  With a few lines of code, DeepPurpose generates drug candidates based on five pre-trained DL models with only a few lines of codes. Further, computer scientists can use DeepPurpose to train customized DTI prediction models with 15 drug / target encodings and 50+ novel architectures.