Scoring 3D protein-protein interaction models using deep learning
deeprank-core is the refactorized version of DeepRank GNN, the graph neural network of our DeepRank package. It allows to train graph neural networks to classify protein-protein interface with a greater flexibility for the user.
In recent years, for the purpose of drug design or protein engineering it has become increasingly of interest to predict or classify information based on the 3D protein-protein interactome.
We have previously developed DeepRank and DeepRank-GNN, deep-learning frameworks to facilitate pattern learning from protein-protein interfaces using Convolutional Neural Network (CNN) and Graph Neural Network (GNN) approaches. deeprank-core has been redesigned to be more modular and customizable, and is wrapped into a user-friendly python3 package.