Abstract
Homology identification is the first step for many genomic studies. Current methods, based on sequence comparison, can result in a substantial number of mis-assignments due to the similarity of homologous domains in otherwise unrelated sequences. Here we propose methods to detect homologs through explicit comparison of protein domain content. We developed several schemes for scoring the homology of a pair of protein sequences based on methods used in the field of information retrieval. We evaluate the proposed methods and methods used in the literature using a benchmark of fifteen sequence families of known evolutionary history. The results of these studies demonstrate the effectiveness of comparing domain architectures using these similarity measures. We also demonstrate the importance of both weighting promiscuous domains and of compensating for the statistical effect of having a large number of domains in a protein. Using logistic regression, we demonstrate the benefit of combining similarity measures based on domain content with sequence similarity measures.
Highlights
The need for accurate multi-domain homology identification is urgent
We focused on vertebrate data because the multi-domain families that challenge traditional homology identification methods tend to be larger and more complex in vertebrates (Aravind et al, 2001; Chothia et al, 2003; Patthy, 2003; Li et al, 2001; International Human Genome Sequencing Consortium, 2001; Venter et al, 2001; Wuchty, 2001; Ye and Godzik, 2004; Wuchty and Almaas, 2005)
We evaluate the weighted similarity measures, followed by a comparison of similarity and distance approaches to domain architecture comparison
Summary
The need for accurate multi-domain homology identification is urgent. Multi-domain proteins represent a substantial fraction of the proteome: about 27% of proteins in bacteria and 39% of proteins in metazoa are multi-domain proteins (Tordai et al, 2005). These are proteins of particular functional importance. Complex multi-domain families are involved in cell-cell signaling, cellular adhesion, and cellular migration, functions crucial to the evolution of multicellularity (BenShlomo et al, 2003; Miyata and Suga, 2001). Since cancer typically arises from failures in signaling or apoptosis, most oncogenes are multi-domain
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