ArticleGenome research2009
The human protein coevolution network.
Article in Genome research, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed, 63 citations in OpenAlex.
- DiffPaSS-high-performance differentiable pairing of protein sequences using soft scores.Bioinformatics (Oxford, England) · 2024Article
- Pairing interacting protein sequences using masked language modeling.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Combining phylogeny and coevolution improves the inference of interaction partners among paralogous proteins.PLoS computational biology · 2023Article
- A-Prot: protein structure modeling using MSA transformer.BMC bioinformatics · 2022Article
- Overview of methods for characterization and visualization of a protein-protein interaction network in a multi-omics integration context.Frontiers in molecular biosciences · 2022Review
- PolyQ length co-evolution in neural proteins.NAR genomics and bioinformatics · 2021Article
- Coevolutionary and Phylogenetic Analysis of Mimiviral Replication Machinery Suggest the Cellular Origin of Mimiviruses.Molecular biology and evolution · 2021Article
- Discovery of Native Protein Complexes by Liquid Chromatography Followed by Quantitative Mass Spectrometry.Advances in experimental medicine and biology · 2021Article
- Inter-protein residue covariation information unravels physically interacting protein dimers.BMC bioinformatics · 2020Article
- Characterizing human genomic coevolution in locus-gene regulatory interactions.BioData mining · 2019Article
- Applying evolutionary genetics to developmental toxicology and risk assessment.Reproductive toxicology (Elmsford, N.Y.) · 2017Review
- Article
- Systems-level analysis of human aging genes shed new light on mechanisms of aging.Human molecular genetics · 2016Article
- Diversification and coevolution of the ghrelin/growth hormone secretagogue receptor system in vertebrates.Ecology and evolution · 2016Article
- Recent coselection in human populations revealed by protein-protein interaction network.Genome biology and evolution · 2014Article
- Studying tumorigenesis through network evolution and somatic mutational perturbations in the cancer interactome.Molecular biology and evolution · 2014Article
- Generation of divergent uroplakin tetraspanins and their partners during vertebrate evolution: identification of novel uroplakins.BMC evolutionary biology · 2014Article
- Practical aspects of protein co-evolution.Frontiers in cell and developmental biology · 2014Review
- Article
- Coevolution analyses illuminate the dependencies between amino acid sites in the chaperonin system GroES-L.BMC evolutionary biology · 2013Article
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Coevolution maintains interactions between phenotypic traits through the process of reciprocal natural selection. Detecting molecular coevolution can expose functional interactions between molecules in the cell, generating insights into biological processes, pathways, and the networks of interactions important for cellular function. Prediction of interaction partners from different protein families exploits the property that interacting proteins can follow similar patterns and relative rates of evolution. Current methods for detecting coevolution based on the similarity of phylogenetic trees or evolutionary distance matrices have, however, been limited by requiring coevolution over the entire evolutionary history considered and are inaccurate in the presence of paralogous copies. We present a novel method for determining coevolving protein partners by finding the largest common submatrix in a given pair of distance matrices, with the size of the largest common submatrix measuring the strength of coevolution. This approach permits us to consider matrices of different size and scale, to find lineage-specific coevolution, and to predict multiple interaction partners. We used MatrixMatchMaker to predict protein-protein interactions in the human genome. We show that proteins that are known to interact physically are more strongly coevolving than proteins that simply belong to the same biochemical pathway. The human coevolution network is highly connected, suggesting many more protein-protein interactions than are currently known from high-throughput and other experimental evidence. These most strongly coevolving proteins suggest interactions that have been maintained over long periods of evolutionary time, and that are thus likely to be of fundamental importance to cellular function.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.