Beyond Mutation Matrices: Physical-Chemistry Based Evolutionary Models

Jeffrey M. Koshi[1] (jkoshi@umich.edu)
David P. Mindell[2] (mindell@umich.edu)
Richard A. Goldstein[3] (richardg@umich.edu)

[1] Biophysics Research Division, University of Michigan
Ann Arbor, MI, 48109-1055, USA
[2] Department of Biology and Museum of Zoology, University of Michigan
Ann Arbor, MI, 48109-1055, USA
[3] Department of Chemistry and Biophysics Research Division, University of Michigan
Ann Arbor, MI, 48109-1079, USA


Abstract

We describe a model for characterizing site mutations in evolving proteins. By representing the fitness of each of the amino acids as a function of the physical-chemical properties of that amino acid, and constructing mutation matrices based on Boltzmann statistics and Metropolis kinetics, we are able to greatly reduce the number of adjustable parameters. This allows us to include site heterogeneity in the model, as well as to optimize the model for specific protein types. We demonstrate the applicability of the model by investigating the phylogenetic relationship between various subtypes of HIV-1.

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Japanese Society for Bioinformatics