TY - JOUR
T1 - Comparative Study of Elastic Network Model and Protein Contact Network for Protein Complexes
T2 - The Hemoglobin Case
AU - Hu, Guang
AU - Di Paola, Luisa
AU - Liang, Zhongjie
AU - Giuliani, Alessandro
PY - 2017/1/1
Y1 - 2017/1/1
N2 - The overall topology and interfacial interactions play key roles in understanding structural and functional principles of protein complexes. Elastic Network Model (ENM) and Protein Contact Network (PCN) are two widely used methods for high throughput investigation of structures and interactions within protein complexes. In this work, the comparative analysis of ENM and PCN relative to hemoglobin (Hb) was taken as case study. We examine four types of structural and dynamical paradigms, namely, conformational change between different states of Hbs, modular analysis, allosteric mechanisms studies, and interface characterization of an Hb. The comparative study shows that ENM has an advantage in studying dynamical properties and protein-protein interfaces, while PCN is better for describing protein structures quantitatively both from local and from global levels. We suggest that the integration of ENM and PCN would give a potential but powerful tool in structural systems biology.
AB - The overall topology and interfacial interactions play key roles in understanding structural and functional principles of protein complexes. Elastic Network Model (ENM) and Protein Contact Network (PCN) are two widely used methods for high throughput investigation of structures and interactions within protein complexes. In this work, the comparative analysis of ENM and PCN relative to hemoglobin (Hb) was taken as case study. We examine four types of structural and dynamical paradigms, namely, conformational change between different states of Hbs, modular analysis, allosteric mechanisms studies, and interface characterization of an Hb. The comparative study shows that ENM has an advantage in studying dynamical properties and protein-protein interfaces, while PCN is better for describing protein structures quantitatively both from local and from global levels. We suggest that the integration of ENM and PCN would give a potential but powerful tool in structural systems biology.
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U2 - 10.1155/2017/2483264
DO - 10.1155/2017/2483264
M3 - Review article
C2 - 28243596
AN - SCOPUS:85012191671
SN - 2314-6133
VL - 2017
JO - BioMed Research International
JF - BioMed Research International
M1 - 2483264
ER -