Abstract
Molecular function in cellular processes is governed by protein-Protein interactions (PPIs) within biological networks. Selective yet specific association of these protein partners contributes to diverse functionality such as catalysis, regulation, assembly, immunity, and inhibition in a cell. Therefore, understanding the principles of protein-Protein association has been of immense interest for several decades. We provide an overview of the experimental methods used to determine PPIs and the key databases archiving this information. Structural and functional information of existing protein complexes confers knowledge on the principles of PPI, based on which a classification scheme for PPIs is then introduced. Obtaining high-quality non-redundant datasets of protein complexes for interaction characterisation is an essential step towards deciphering their underlying binding principles. Analysis of physicochemical features and their documentation has enhanced our understanding of the molecular basis of protein-Protein association. We describe the diverse datasets created/collected by various groups and their key findings inferring distinguishing features. The currently available interface databases and prediction servers have also been compiled.
| Language | English |
|---|---|
| Pages | 779-789 |
| Number of pages | 11 |
| Journal | Protein and peptide letters |
| Volume | 21 |
| Issue number | 8 |
| Publication status | Published - 2014 |
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Protein-protein interactions and prediction : A comprehensive overview. / Sowmya, Gopichandran; Ranganathan, Shoba.
In: Protein and peptide letters, Vol. 21, No. 8, 2014, p. 779-789.Research output: Contribution to journal › Article › Research › peer-review
TY - JOUR
T1 - Protein-protein interactions and prediction
T2 - Protein and peptide letters
AU - Sowmya, Gopichandran
AU - Ranganathan, Shoba
PY - 2014
Y1 - 2014
N2 - Molecular function in cellular processes is governed by protein-Protein interactions (PPIs) within biological networks. Selective yet specific association of these protein partners contributes to diverse functionality such as catalysis, regulation, assembly, immunity, and inhibition in a cell. Therefore, understanding the principles of protein-Protein association has been of immense interest for several decades. We provide an overview of the experimental methods used to determine PPIs and the key databases archiving this information. Structural and functional information of existing protein complexes confers knowledge on the principles of PPI, based on which a classification scheme for PPIs is then introduced. Obtaining high-quality non-redundant datasets of protein complexes for interaction characterisation is an essential step towards deciphering their underlying binding principles. Analysis of physicochemical features and their documentation has enhanced our understanding of the molecular basis of protein-Protein association. We describe the diverse datasets created/collected by various groups and their key findings inferring distinguishing features. The currently available interface databases and prediction servers have also been compiled.
AB - Molecular function in cellular processes is governed by protein-Protein interactions (PPIs) within biological networks. Selective yet specific association of these protein partners contributes to diverse functionality such as catalysis, regulation, assembly, immunity, and inhibition in a cell. Therefore, understanding the principles of protein-Protein association has been of immense interest for several decades. We provide an overview of the experimental methods used to determine PPIs and the key databases archiving this information. Structural and functional information of existing protein complexes confers knowledge on the principles of PPI, based on which a classification scheme for PPIs is then introduced. Obtaining high-quality non-redundant datasets of protein complexes for interaction characterisation is an essential step towards deciphering their underlying binding principles. Analysis of physicochemical features and their documentation has enhanced our understanding of the molecular basis of protein-Protein association. We describe the diverse datasets created/collected by various groups and their key findings inferring distinguishing features. The currently available interface databases and prediction servers have also been compiled.
UR - http://www.scopus.com/inward/record.url?scp=84903701114&partnerID=8YFLogxK
M3 - Article
VL - 21
SP - 779
EP - 789
JO - Protein and peptide letters
JF - Protein and peptide letters
SN - 0929-8665
IS - 8
ER -