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Towards the prediction of protein interaction partners using physical docking
Authors:Mark Nicholas Wass  Carles Pons  Florencio Pazos  Alfonso Valencia
Affiliation:1. Structural Biology and Biocomputing Programme, Spanish National Cancer Research Centre (CNIO), , Madrid, Spain;2. Structural Bioinformatics Group, Centre for Bioinformatics, Imperial College London, , London, UK;3. Life Sciences Department, Barcelona Supercomputing Center, , Barcelona, Spain;4. Computational Bioinformatics, National Institute of Bioinformatics (INB), , Barcelona, Spain;5. Computational Systems Biology Group, National Centre for Biotechnology (CNB‐CSIC), , Madrid, Spain
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.
Keywords:interactome  protein docking  protein–  protein interaction
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