The adaptive nature of protein residue networks

Abstract

Protein residue networks PRNs are used to describe proteins. These networks are usually based on an average structure for the protein. However, proteins are dynamic entities that are affected by their surroundings. In this work, we study the effect of temperatures above and below the protein dynamical transition temperature(≈200 K), on three important network parameters gleaned from weighted PRNs for the solvated β-lactamase inhibitory protein BLIP: the betweenness centrality B, the closeness centrality C, and the clustering coefficient CC. The B and C values will be extracted for each node from PRNs at six different temperatures: 150 K, 180 K, 200 K, 220 K, 250 K, and 310 K respectively. The average value for the CC for each PRN will also be calculated at each temperature, respectively. We find that at temperatures ≤200 K, the network nodes with the most significant B and C values tend to have lower relative solvent accessibility RSA values, and to fall within the protein secondary structure elements (α helices and β sheets). At temperatures >200 K, the significant nodes in terms of B and C tend to have larger RSA values, and to fall on the connecting loops in the protein. The average CC decreases in value for the PRNs up to 200 K, and then remains basically constant above 200 K. This clearly shows that any conclusions based on static PRNs should be handled with care. The dynamic nature of proteins and its coupling to the surrounding environment should be taken into consideration when using the PRN paradigm. Proteins 2017; 85:917-923. © 2016 Wiley Periodicals, Inc.

Protein conformational switch discerned via network centrality properties

“…PSNs have been shown to have the potential for bridging graph theory concepts and mechanisms of protein systems. Such connection not only enriches the statistical analysis of networks by providing a class of practical networks with unique properties, but also assists a better (quantitative) understanding of structure–function relationships in proteins [9] , [10] , [11] , [12] , [13] , [14] , [15] , [16] , [17] , [18] , [19] , [20] , [21] , [22] .…”

Topological Analysis of SARS CoV-2 Main Protease

“…Because the Euclidean distance between the amino acids is used to construct the network we more correctly should refer to this framework as topographical more than topological. This network theoretic representation has been previously used to answer several questions related to protein structure and functioning [18,19,20,21,22]. Among the tools in use, the one of node centrality [23,24] has played a fundamental role (see for instance [22].…”