DEPCOD: a tool to detect and visualize co-evolution of protein domains

Author:

Ji Fei12,Bonilla Gracia12,Krykbaev Rustem1,Ruvkun Gary12,Tabach Yuval3,Sadreyev Ruslan I14ORCID

Affiliation:

1. Department of Molecular Biology, Massachusetts General Hospital , Boston , MA , USA

2. Department of Genetics, Harvard Medical School , Boston , MA , USA

3. Department of Developmental Biology and Cancer Research, Faculty of Medicine, The Hebrew University of Jerusalem , Ein Kerem  9112102 ,  Israel

4. Department of Pathology, Massachusetts General Hospital and Harvard Medical School , Boston , MA , USA

Abstract

Abstract Proteins with similar phylogenetic patterns of conservation or loss across evolutionary taxa are strong candidates to work in the same cellular pathways or engage in physical or functional interactions. Our previously published tools implemented our method of normalized phylogenetic sequence profiling to detect functional associations between non-homologous proteins. However, many proteins consist of multiple protein domains subjected to different selective pressures, so using protein domain as the unit of analysis improves the detection of similar phylogenetic patterns. Here we analyze sequence conservation patterns across the whole tree of life for every protein domain from a set of widely studied organisms. The resulting new interactive webserver, DEPCOD (DEtection of Phylogenetically COrrelated Domains), performs searches with either a selected pre-defined protein domain or a user-supplied sequence as a query to detect other domains from the same organism that have similar conservation patterns. Top similarities on two evolutionary scales (the whole tree of life or eukaryotic genomes) are displayed along with known protein interactions and shared complexes, pathway enrichment among the hits, and detailed visualization of sources of detected similarities. DEPCOD reveals functional relationships between often non-homologous domains that could not be detected using whole-protein sequences. The web server is accessible at http://genetics.mgh.harvard.edu/DEPCOD.

Funder

National Institutes of Health

Melanoma Research Alliance

Israel Cancer Association

Publisher

Oxford University Press (OUP)

Subject

Genetics

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