Prediction of Hydrophobic Core Residues Based on Network Analysis

In recent years, protein folding kinetics studies performed the hydrophobic core residues play a key role not only in stabilizing the native state, but also in driving the folding reaction itself. In this work, the protein structure is modeled as an undirected network with the amino acids the vertexes and the contacts between them the edges. We find that the core residues have mainly high degree and low clustering coefficient compared with the surface residues. The four different centrality measurements have been proposed to predict hydrophobic core residues from four well-characterized proteins. We show that the four network-based centrality measurements (degree, clustering coefficient, closeness centrality, betweenness) accurately detect the hydrophobic core residues and there is strong functional relationship between any two different network-based centrality measurements. Additionally, we plot four network centrality measurements versus the Conseq value, the results show that all hydrophobic core residues have high conseq values and this means that the hydrophobic core residues are conserved in proteins.