Optimality of Moore neighborhoods in protein contact maps
📝 Original Info
- Title: Optimality of Moore neighborhoods in protein contact maps
- ArXiv ID: 1305.1231
- Date: 2013-05-07
- Authors: Researchers from original ArXiv paper
📝 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 may explain how protein residue networks are able to form long-range links to reduce average path length while maintaining a high level of clustering throughout the process of small-world formation, and could suggest new approaches to protein contact map prediction. Effectively, the problem of protein contact map prediction is transformed to one of maximizing the number of optimal neighborhoods. By comparison, Moore neighborhoods in protein contact maps with randomized long-range links are less optimal.💡 Deep Analysis
Deep Dive into Optimality of Moore neighborhoods in protein contact maps.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 may explain how protein residue networks are able to form long-range links to reduce average path le