Application of Network Theory in Understanding and Predicting Protein Structure and Function
Authors: Galan, Jhenny F.; Gao, Jun; Pabuwal, Vagmita; Meek, Peter J.; Li, Zhijun
Source: Current Proteomics, Volume 5, Number 3, October 2008 , pp. 181-190(10)
Publisher: Bentham Science Publishers
Abstract:
Elucidating protein structure and function relationships from sequence data, and predicting protein structure and function by an automatic, high-throughput means pose important and imminent challenges for structural proteomics. In recent years, there has been growing interest in applying network concepts and theory to meet this challenge. The network approach transforms a protein structure into a network by representing each amino acid residue as a node and each residue-residue interaction with an edge connecting two residues. Through this transformation, insights into various aspects of protein structure and function are explored from the perspective of networks. Current applications of the network approach include: understanding protein stability, studying protein folding, developing scoring functions for structure discrimination, predicting protein functional sites and analyzing protein-protein and protein-DNA complexes. The network approach is computationally efficient and proves to be a useful tool in structural proteomics. This review covers the applications of the network approach in the field of structural proteomics.Keywords: Protein Structure- function relation ships; protein-DNA complexes; structural proteomics; Protein 3D structure; residue-residue interaction
Document Type: Research article
Publication date: 2008-10-01
- Current Proteomics research in the emerging field of proteomics is growing at an extremely rapid rate. The principal aim of Current Proteomics is to publish well-timed review articles in this fast-expanding area on topics relevant and significant to the development of proteomics. Current Proteomics is an essential journal for everyone involved in proteomics and related fields in both academia and industry.
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- In this Subject: Genetics
- By this author: Galan, Jhenny F. ; Gao, Jun ; Pabuwal, Vagmita ; Meek, Peter J. ; Li, Zhijun

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