Abstract
The vast majority of proteins do not form functional interactions in physiological conditions. We have considered several sets of protein pairs from S. cerevisiae with no functional interaction reported, denoted as non-interacting pairs, and compared their 3D structures to available experimental complexes. We identified some non-interacting pairs with significant structural similarity with experimental complexes, indicating that, even though they do not form functional interactions, they have compatible structures. We estimate that up to 8.7% of non-interacting protein pairs could have compatible structures. This number of interactions exceeds the number of functional interactions (around 0.2% of the total interactions) by a factor 40. Network analysis suggests that the interactions formed by non-interacting pairs with compatible structures could be particularly hazardous to the protein-protein interaction network. From a structural point of view, these interactions display no aberrant structural characteristics, and are even predicted as relatively stable and enriched in potential physical interactors, suggesting a major role of regulation to prevent them.
Highlights
The vast majority of proteins do not form functional interactions in physiological conditions
What is the weight of intrinsic structural properties versus regulation of protein fate in the existence or absence of protein-protein interactions in vivo? To answer this question, we focused on non-interacting proteins, i.e., protein pairs for which no functional interaction is reported, and their 3D structures, and we quantified how frequently they can be mistaken for interacting proteins, by comparison with experimental structures
We compare the 3D structures of non-interacting protein pairs of S. cerevisiae to a set of experimental dimers from the PDB30
Summary
The vast majority of proteins do not form functional interactions in physiological conditions. We identified some non-interacting pairs with significant structural similarity with experimental complexes, indicating that, even though they do not form functional interactions, they have compatible structures. Network analysis suggests that the interactions formed by non-interacting pairs with compatible structures could be hazardous to the protein-protein interaction network. Aloy and Russell[11,12] reported the first homology-based method They used homologous complexes to predict the interaction between candidate proteins and to derive statistical potentials to score the predicted interaction models. These scores measured the preservation of interface atomic contacts seen in experimental complexes, allowing the distinction between interacting pairs (preserving the contacts) and others. Multiple threading techniques were proposed to exploit distant homology relationships[15,16,17,25]; in this case, models are scored by the threading potential, alone or combined with external information such as co-localization and functional annotations[15,25]
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