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Computational Methods for the Prediction of Protein-Protein Interactions

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Abstract:

Protein-protein interactions (PPIs) are key components of most cellular processes, so identification of PPIs is at the heart of functional genomics. A number of experimental techniques have been developed to discover the PPI networks of several organisms. However, the accuracy and coverage of these techniques have proven to be limited. Therefore, it is important to develop computational methods to assist in the design and validation of experimental studies and for the prediction of interaction partners. Here, we provide a critical overview of existing computational methods including genomic context method, structure-based method, domain-based method and sequence-based method. While an exhaustive list of methods is not presented, we analyze the relative strengths and weaknesses for each of the methods discussed, as well as a broader perspective on computational techniques for determining PPIs. In addition to algorithms for interaction prediction, description of many useful databases pertaining to PPIs is also provided.





Keywords: Protein-protein interactions; computational techniques; genome context; protein domain; protein interaction databases; protein sequence; protein structure

Document Type: Research Article

DOI: http://dx.doi.org/10.2174/092986610791760405

Publication date: September 1, 2010

More about this publication?
  • Protein & Peptide Letters publishes short papers in all important aspects of protein and peptide research, including structural studies, recombinant expression, function, synthesis, enzymology, immunology, molecular modeling, drug design etc. Manuscripts must have a significant element of novelty, timeliness and urgency that merit rapid publication. Reports of crystallisation, and preliminary structure determinations of biologically important proteins are acceptable. Purely theoretical papers are also acceptable provided they provide new insight into the principles of protein/peptide structure and function.
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