Abstract
Predicting the structure of interacting protein chains is a fundamental step towards understanding protein function. Unfortunately, no computational method can produce accurate structures of protein complexes. AlphaFold2, has shown unprecedented levels of accuracy in modelling single chain protein structures. Here, we apply AlphaFold2 for the prediction of heterodimeric protein complexes. We find that the AlphaFold2 protocol together with optimized multiple sequence alignments, generate models with acceptable quality (DockQ≥0.23) for 63% of the dimers. From the predicted interfaces we create a simple function to predict the DockQ score which distinguishes acceptable from incorrect models as well as interacting from non-interacting proteins with state-of-art accuracy. We find that, using the predicted DockQ scores, we can identify 51% of all interacting pairs at 1% FPR. The protocol can be found at: https://gitlab.com/ElofssonLab/FoldDock.
Competing Interest Statement
The authors have declared no competing interest.
Footnotes
After reviews we have updated the manuscript. In short two major things have changed 1) We have introduced a pDockQ score that predicts the DockQ score for each protein-protein interactions. This improves both separation of good and bad models and interacting and non-interacting proteins. 2) We have added comparisons to (a) state of the art docking method and (b) alphafold-multimer.
