Towards the prediction of protein interaction partners using physical docking
Citations Over TimeTop 10% of 2011 papers
Abstract
Deciphering the whole network of protein interactions for a given proteome ('interactome') is the goal of many experimental and computational efforts in Systems Biology. Separately the prediction of the structure of protein complexes by docking methods is a well-established scientific area. To date, docking programs have not been used to predict interaction partners. We provide a proof of principle for such an approach. Using a set of protein complexes representing known interactors in their unbound form, we show that a standard docking program can distinguish the true interactors from a background of 922 non-redundant potential interactors. We additionally show that true interactions can be distinguished from non-likely interacting proteins within the same structural family. Our approach may be put in the context of the proposed 'funnel-energy model'; the docking algorithm may not find the native complex, but it distinguishes binding partners because of the higher probability of favourable models compared with a collection of non-binders. The potential exists to develop this proof of principle into new approaches for predicting interaction partners and reconstructing biological networks.
Related Papers
- → In silico prediction of protein-protein interactions in human macrophages(2014)10,952 cited
- → Plant Protein Interactomes(2013)127 cited
- → A Second-generation Protein–Protein Interaction Network of Helicobacter pylori(2014)64 cited
- → Two‐Hybrid Systems to Measure Protein–Protein Interactions(2018)2 cited
- → Defining Viral Protein Interactomes Using the Yeast Two-Hybrid Assay(2005)1 cited