NPCs represent one of the biggest and paradigmatic protein complexes, and could play a key role in understanding the general rules concerning protein complexes assembly and dynamics in eukaryotic cells.
We are building several models and plan to perform experiments to understand and predict the distribution of the network (power law or exponential distribution); networks of module regulation with microarray databases; identification of candidate nuclear pore complex components (nucleoporins) in the nematode Caenorhabditis elegans (23 nucleoporins currently known vs. >30 in yeast, fruit fly and human); and finally we are using an algorithm to identify ìcommunitiesî in the network at multiple resolutions.
We have applied a community detection algorithm to physical interactions among yeast proteins included in the Biogrid database (http://www.thebiogrid.org/) to obtain candidate genes for the NPC network and the connection/coherence with gene ontology (GO) terms pertaining to this biological structure. Applying chi square test and standard GO-term finder tools we are studying which other GO terms are overrepresented in the community containing NPC components. We have found that both the nuclear exosome and the associated SKI complex could have an interesting connection with NPCs. Initially, interactions with the NPC will be tested for RNAi-induced synthetic lethality, followed by experiments aiming to reveal mechanistic insight.