期刊
IUBMB LIFE
卷 63, 期 4, 页码 264-271出版社
WILEY-BLACKWELL
DOI: 10.1002/iub.455
关键词
protein interaction; coevolution; yeast 2 hybrid; coadaptation
资金
- Science foundation Ireland [RFP: 10/RFP/GEN2685, 07/IN.1/B913, 08/RFP/NSC1617]
- Ministerio de Ciencia e Innovacion [BFU2009-12022]
- Science Foundation Ireland (SFI) [07/IN.1/B913, 08/RFP/NSC1617] Funding Source: Science Foundation Ireland (SFI)
Proteins rarely function in isolation but they form part of complex networks of interactions with other proteins within or among cells. The importance of a particular protein for cell viability is directly dependent upon the number of interactions where it participates and the function it performs: the larger the number of interactions of a protein the greater its functional importance is for the cell. With the advent of genome sequencing and omics'' technologies it became feasible conducting large-scale searches for protein interacting partners. Unfortunately, the accuracy of such analyses has been under-whelming owing to methodological limitations and to the inherent complexity of protein interactions. In addition to these experimental approaches, many computational methods have been developed to identify protein-protein interactions by assuming that interacting proteins coevolve resulting from the coadaptation dynamics between the amino acids of their interacting faces. We review the main technological advances made in the field of interactomics and discuss the feasibility of computational methods to identify protein-protein interactions based on the estimation of coevolution. As proof-of-concept, we present a classical case study: the interactions of cell surface proteins (receptors) and their ligands. Finally, we take this discussion one step forward to include interactions between organisms and species to understand the generation of biological complexity. Development of technologies for accurate detection of protein-protein interactions may shed light on processes that go from the fine-tuning of pathways and metabolic networks to the emergence of biological complexity. (C) 2011 IUBMB IUBMB Life, 63( 4): 264-271, 2011
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