  Topological analysis of large scale protein-protein interaction networks
(PINs) is important for understanding the organisational and functional
principles of individual proteins. The number of interactions that a protein
has in a PIN has been observed to be correlated with its indispensability.
Essential proteins generally have more interactions than the non-essential
ones. We show here that the lethality associated with removal of a protein from
the yeast proteome correlates with different centrality measures of the nodes
in the PIN, such as the closeness of a protein to many other proteins, or the
number of pairs of proteins which need a specific protein as an intermediary in
their communications, or the participation of a protein in different protein
clusters in the PIN. These measures are significantly better than random
selection in identifying essential proteins in a PIN. Centrality measures based
on graph spectral properties of the network, in particular the subgraph
centrality, show the best performance in identifying essential proteins in the
yeast PIN. Subgraph centrality gives important structural information about the
role of individual proteins and permits the selection of possible targets for
rational drug discovery through the identification of essential proteins in the
PIN.
