[HTML][HTML] Improved prediction of protein-protein interactions using AlphaFold2

P Bryant, G Pozzati, A Elofsson - Nature communications, 2022 - nature.com
Nature communications, 2022nature.com
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 optimised multiple sequence alignments, generate models with acceptable quality …
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 optimised 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.
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