  Identifying reliable domain-domain interactions (DDIs) will increase our
ability to predict novel protein-protein interactions (PPIs), to unravel
interactions in protein complexes, and thus gain more information about the
function and behavior of genes. One of the challenges of identifying reliable
DDIs is domain promiscuity. Promiscuous domains are domains that can occur in
many domain architectures and are therefore found in many proteins. This
becomes a problem for a method where the score of a domain-pair is the ratio
between observed and expected frequencies because the PPI network is sparse. As
such, many protein-pairs will be non-interacting and domain-pairs with
promiscuous domains will be penalized. This domain promiscuity challenge to the
problem of inferring reliable DDIs from PPIs has been recognized, and a number
of work-arounds have been proposed. In this paper, we report an application of
Formal Concept Analysis (FCA) to this problem. We find that the relationship
between formal concepts provide a natural way for rare domains to elevate the
rank of promiscuous domains, and enrich highly ranked domain-pairs with
reliable DDIs. This piggy-backing of promiscuous domains onto rare domains is
possible due to the domain architecture of proteins which mixes promiscuous
with rare domains.
