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Modeling protein evolution

Part 1. Genetics

1.1. Genetic Variation and Evolution

Short Specialist Review

  1. David D. Pollock1,
  2. Richard A. Goldstein2

Published Online: 15 APR 2005

DOI: 10.1002/047001153X.g101311

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics

How to Cite

Pollock, D. D. and Goldstein, R. A. 2005. Modeling protein evolution. Encyclopedia of Genetics, Genomics, Proteomics and Bioinformatics. 1:1.1:9.

Author Information

  1. 1

    Louisiana State University, Baton Rouge, LA, USA

  2. 2

    National Institute for Medical Research, London, UK

Publication History

  1. Published Online: 15 APR 2005

Abstract

Modeling protein evolution has been frustratingly simplistic in the past, but new methodologies and approaches have been rapidly changing this situation. Increased computational power, improved phylogeny-based maximum likelihood and Bayesian approaches, larger data sets, and better protein structure prediction methods are jointly improving the outlook and allowing researchers to improve the biological realism of protein models. They are also allowing more detailed analysis of differences in processes among sequence positions over space and time, of selection and adaptation, coevolution, and functional divergence, and of ancestral changes in function. The future is expected to bring improved integration of models of protein evolution with protein structure prediction, with the potential to dramatically improve the accuracy and power of both.

Keywords:

  • protein evolution;
  • evolutionary dynamics;
  • protein structure;
  • maximum likelihood;
  • posterior probability;
  • Bayesian;
  • coevolution