Before revision: We propose the use of local search to investigate protein residue networks ( PRN) . In a local search , clustering is inversely related to average path length. The opposite holds for a global search such as the commonly used breadth first strategy (BFS). The inverse relationship better fits the notion that amino acids get closer to each other as a protein becomes more compact. We use a greedy local search algorithm (EDS) that is Euclidean distance based and allows backtracking. While there are preferable differences between BFS and EDS paths in terms of variation in path length , search cost and link usage, there are also similarities in terms of centrality and hierarchy . EDS identifies a set of short-cut edges for each PRN . Short-cut edges are enriched with short-range links, and the short-cut network (SCN) they form spans most of a PRN's nodes, is adjacent to most of a PRN's edges and is strongly transitive.
After revision: We propose the use of local search to investigate protein residue networks ( PRN) . In a local search perspective to understand why PRNs are highly clustered when having short paths is important for protein functionality. We found that by adopting a local search cost and link usage, there are also similarities in terms of centrality and hierarchy . EDS identifies a set of short-cut edges for each PRN . Short-cut edges are enriched with short-range links, and the short-cut network (SCN) they form spans most of a PRN's nodes, is adjacent to most of a PRN's edges and is strongly transitive.