The Effect of Edge Definition of Complex Networks on Protein Structure Identification
Author(s) -
Jing Sun,
Runyu Jing,
Di Wu,
Tuanfei Zhu,
Menglong Li,
Yizhou Li
Publication year - 2013
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2013/365410
Subject(s) - computer science , domain (mathematical analysis) , protein structure , computational biology , path (computing) , complex network , identification (biology) , mathematics , biology , combinatorics , biochemistry , botany , mathematical analysis , programming language
The main objective of this study is to explore the contribution of complex network together with its different definitions of vertexes and edges to describe the structure of proteins. Protein folds into a specific conformation for its function depending on interactions between residues. Consequently, in many studies, a protein structure was treated as a complex system comprised of individual components residues, and edges were interactions between residues. What is the proper time for representing a protein structure as a network? To confirm the effect of different definitions of vertexes and edges in constructing the amino acid interaction networks, protein domains and the structural unit of proteins were described using this method. The identification performance of 2847 proteins with domain/domains proved that the structure of proteins was described well when R C α was around 5.0–7.5 Å, and the optimal cutoff value for constructing the protein structure networks was 5.0 Å (C α -C α distances) while the ideal community division method was community structure detection based on edge betweenness in this study.
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