Journal of Molecular Evolution

, Volume 57, Supplement 1, pp S103–S119 | Cite as

Statistical Properties of Neutral Evolution

  • Ugo BastollaEmail author
  • Markus Porto
  • H. Eduardo Roman
  • Michele Vendruscolo


Neutral evolution is the simplest model of molecular evolution and thus it is most amenable to a comprehensive theoretical investigation. In this paper, we characterize the statistical properties of neutral evolution of proteins under the requirement that the native state remains thermodynamically stable, and compare them to the ones of Kimura’s model of neutral evolution. Our study is based on the Structurally Constrained Neutral (SCN) model which we recently proposed. We show that, in the SCN model, the substitution rate decreases as longer time intervals are considered. Fluctuations from one branch of the evolutionary tree to another are strong, leading to a non-Poissonian statistics for the substitution process. Such strong fluctuations are in part due to the fact that neutral substitution rates for individual residues are strongly correlated for most residue pairs. Interestingly, structurally conserved residues, characterized by a much below average substitution rate, are also much less correlated to other residues and evolve in a much more regular way. Our results can improve methods aimed at distinguishing between neutral and adaptive substitutions as well as methods for computing the expected number of substitutions occurred since the divergence of two protein sequences. In particular, we compute the minimal sequence similarity below which no information about the evolutionary divergence of the compared sequences can be obtained.


Neutral evolution Non-Poissonian substitution process Correlations 


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Copyright information

© Springer-Verlag New York LLC 2003

Authors and Affiliations

  • Ugo Bastolla
    • 1
    Email author
  • Markus Porto
    • 2
  • H. Eduardo Roman
    • 3
  • Michele Vendruscolo
    • 4
  1. 1.Centro de Astrobiología (INTA-CSIC), 28850 Torrejon de ArdozSpain
  2. 2.Max-Planck-Institut für Physik Komplexer Systeme, Nöthnitzer Straβe 38, 01187 DresdenGermany
  3. 3.Dipartimento di Fisica and INFNUniversità di Milano, Via Celoria 16, 20133 MilanoItaly
  4. 4.Department of ChemistryUniversity of Cambridge, Lensfield Road, Cambridge CB2 1EWUnited Kingdom

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