ProSPr: Democratized Implementation of Alphafold Protein Distance Prediction Network

Abstract

Deep neural networks have recently enabled spectacular progress in predicting protein structures, as demonstrated by DeepMin’s winning entry with Alphalfold at the latest Critical Assessment, of Structure Prediction competition (CASP13). The best protein prediction pipeline leverages intermolecular distance predictions to assemble a final protein model, but this distance prediction network has not been published. Here, we make a trained implementation of this network available to the broader scientific community. We also benchmark its predictive power in the related task of contact prediction against the CASP13 contact prediction winner TripletRes. Access to ProSPr will enable other labs to build on best in class protein distance predictions and to engineer superior protein reconstruction methods.