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Understanding on the residue contact network using the log‐normal cluster model and the multilevel wheel diagram
Author(s) -
Sun Weitao,
He Jing
Publication year - 2010
Publication title -
biopolymers
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.556
H-Index - 125
eISSN - 1097-0282
pISSN - 0006-3525
DOI - 10.1002/bip.21494
Subject(s) - residue (chemistry) , chemistry , cluster (spacecraft) , globular protein , biological system , cluster size , chemical physics , crystallography , amino acid residue , protein structure , topology (electrical circuits) , biophysics , statistical physics , physics , combinatorics , molecular dynamics , computational chemistry , peptide sequence , computer science , mathematics , biochemistry , biology , gene , programming language
Residue clusters play essential role in stabilizing protein structures in the form of complex networks. We show that the cluster sizes in a native protein follow the log‐normal distribution for a dataset consisting of 424 proteins. To our knowledge, this is the first time of such fitting for the native structures. Based on log‐normal model, the asymptotically increasing mean cluster sizes produce a critical protein chain length of about 200 amino acids, beyond which length most globular proteins have nearly the same mean cluster sizes. This suggests that the larger proteins use a different packing mechanism than the smaller proteins. We confirmed the scale‐free property of the residue contact network for most of the protein structures in the dataset, although the violations were observed for the tightly packed proteins. Residue cluster network wheel (RCNW) is proposed to visualize the relationship between the multiple properties of the residue network such as the cluster size, the residue types and contacts, and the flexibility of the residue. We noticed that the residues with large cluster size have smaller Cα displacement measured using the normal mode analysis. © 2010 Wiley Periodicals, Inc. Biopolymers 93: 904–916, 2010.