I've implemented ligand binding affinity prediction using deep learning and also wrote a blog post about it. The post doesn't cover only the technical stuff, bu

I've implemented ligand binding affinity prediction using deep learning and also wrote a blog post about it. The post doesn't cover only the technical stuff, but also a little bit the history of the idea. It uses SMILES token to feed the neural network with the molecule structures. I'm using alternative representations for data augmentation, which wasn't used by similar projects before. The training is done with Keras Gaia, which was developed for this project. It simplifies the training process for different models and datasets. The SPARQL wrapper for BindingDB could be of interest for anyone who would like to fetch BindingDB data using ChEMBL queries. I also implemented a SMILES parser in JavaScript, because there wasn't any implementation available.