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Mapping proteins in the presence of paralogs using units of coevolution

BACKGROUND: We study the problem of mapping proteins between two protein families in the presence of paralogs. This problem occurs as a difficult subproblem in coevolution-based computational approaches for protein-protein interaction prediction. RESULTS: Similar to prior approaches, our method is b...

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Detalles Bibliográficos
Autores principales: El-Kebir, Mohammed, Marschall, Tobias, Wohlers, Inken, Patterson, Murray, Heringa, Jaap, Schönhuth, Alexander, Klau, Gunnar W
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3852051/
https://www.ncbi.nlm.nih.gov/pubmed/24564758
http://dx.doi.org/10.1186/1471-2105-14-S15-S18
Descripción
Sumario:BACKGROUND: We study the problem of mapping proteins between two protein families in the presence of paralogs. This problem occurs as a difficult subproblem in coevolution-based computational approaches for protein-protein interaction prediction. RESULTS: Similar to prior approaches, our method is based on the idea that coevolution implies equal rates of sequence evolution among the interacting proteins, and we provide a first attempt to quantify this notion in a formal statistical manner. We call the units that are central to this quantification scheme the units of coevolution. A unit consists of two mapped protein pairs and its score quantifies the coevolution of the pairs. This quantification allows us to provide a maximum likelihood formulation of the paralog mapping problem and to cast it into a binary quadratic programming formulation. CONCLUSION: CUPID, our software tool based on a Lagrangian relaxation of this formulation, makes it, for the first time, possible to compute state-of-the-art quality pairings in a few minutes of runtime. In summary, we suggest a novel alternative to the earlier available approaches, which is statistically sound and computationally feasible.