In the yeast protein-protein interaction network, motif mode, a collection of motifs of special combinations of protein nodes annotated by the molecular function terms of the Gene Ontology, has revealed differences in the conservation constraints within the same topology. In this study, by employing an intelligent agent-based distributed computing method, we are able to discover motif modes in a fast and adaptive manner. Moreover, by focusing on the highly evolutionarily conserved motif modes belonging to the same biological function, we find a large downshift in the distance between nodes belonging to the same motif mode compared with the whole, suggesting that nodes with the same motif mode tend to congregate in a network. Several motif modes with a high conservation of the motif constituents were revealed, but from a new perspective, including that with a three-node motif mode engaged in the protein fate and that with three four-node motif modes involved in the genome maintenance, cellular organization, and transcription. The network motif modes discovered from this method can be linked to the wealth of biological data which require further elucidation with regard to biological functions.