Optimality of Moore neighborhoods in protein contact maps
Susan Khor

TL;DR
This study demonstrates that Moore neighborhoods in protein contact maps are nearly optimal for maintaining network efficiency, offering insights into protein structure formation and potential new methods for contact map prediction.
Contribution
It shows that Moore neighborhoods are 97% optimal in preserving network efficiency in protein contact maps, linking neighborhood configuration to protein network properties.
Findings
Moore neighborhoods are 97% optimal in contact maps.
Optimal neighborhoods support small-world network features.
Randomized long-range links reduce neighborhood optimality.
Abstract
A protein contact map is a binary symmetric adjacency matrix capturing the distance relationship between atoms of a protein. Each cell (i, j) of a protein contact map states whether the atoms (nodes) i and j are within some Euclidean distance from each other. We examined the radius one Moore neighborhood surrounding each cell (i, j) where j > (i + 2) in complete protein contact maps by mutating them one at a time. We found that the particular configuration of a neighborhood is generally (97%) optimal in the sense that no other configuration could maintain or improve upon existing local and global efficiencies of the nodes residing in a neighborhood. Local efficiency of a node is directly related to its clustering measure. Global efficiency of a node is inversely related to its distance to other nodes in the network. This feature of the Moore neighborhood in complete protein contact maps…
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Taxonomy
TopicsProtein Structure and Dynamics · Bioinformatics and Genomic Networks · Complex Network Analysis Techniques
