Scaling properties of evolutionary paths in a biophysical model of protein adaptation

Michael Manhart, Alexandre Morozov

Research output: Contribution to journalArticle

Abstract

The enormous size and complexity of genotypic sequence space frequently requires consideration of coarse-grained sequences in empirical models. We develop scaling relations to quantify the effect of this coarse-graining on properties of fitness landscapes and evolutionary paths. We first consider evolution on a simple Mount Fuji fitness landscape, focusing on how the length and predictability of evolutionary paths scale with the coarse-grained sequence length and alphabet. We obtain simple scaling relations for both the weak- and strong-selection limits, with a non-trivial crossover regime at intermediate selection strengths. We apply these results to evolution on a biophysical fitness landscape that describes how proteins evolve new binding interactions while maintaining their folding stability. We combine the scaling relations with numerical calculations for coarse-grained protein sequences to obtain quantitative properties of the model for realistic binding interfaces and a full amino acid alphabet.

Original languageEnglish (US)
Article number045001
JournalPhysical Biology
Volume12
Issue number4
DOIs
StatePublished - Jul 1 2015

Fingerprint

Proteins
Amino Acids

All Science Journal Classification (ASJC) codes

  • Molecular Biology
  • Biophysics
  • Structural Biology
  • Cell Biology

Keywords

  • evolutionary paths
  • fitness landscapes
  • protein evolution
  • random walks
  • scaling

Cite this

@article{5aacb4c7119b4161ae93e60375ee7deb,
title = "Scaling properties of evolutionary paths in a biophysical model of protein adaptation",
abstract = "The enormous size and complexity of genotypic sequence space frequently requires consideration of coarse-grained sequences in empirical models. We develop scaling relations to quantify the effect of this coarse-graining on properties of fitness landscapes and evolutionary paths. We first consider evolution on a simple Mount Fuji fitness landscape, focusing on how the length and predictability of evolutionary paths scale with the coarse-grained sequence length and alphabet. We obtain simple scaling relations for both the weak- and strong-selection limits, with a non-trivial crossover regime at intermediate selection strengths. We apply these results to evolution on a biophysical fitness landscape that describes how proteins evolve new binding interactions while maintaining their folding stability. We combine the scaling relations with numerical calculations for coarse-grained protein sequences to obtain quantitative properties of the model for realistic binding interfaces and a full amino acid alphabet.",
keywords = "evolutionary paths, fitness landscapes, protein evolution, random walks, scaling",
author = "Michael Manhart and Alexandre Morozov",
year = "2015",
month = "7",
day = "1",
doi = "https://doi.org/10.1088/1478-3975/12/4/045001",
language = "English (US)",
volume = "12",
journal = "Physical Biology",
issn = "1478-3967",
publisher = "IOP Publishing Ltd.",
number = "4",

}

Scaling properties of evolutionary paths in a biophysical model of protein adaptation. / Manhart, Michael; Morozov, Alexandre.

In: Physical Biology, Vol. 12, No. 4, 045001, 01.07.2015.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Scaling properties of evolutionary paths in a biophysical model of protein adaptation

AU - Manhart, Michael

AU - Morozov, Alexandre

PY - 2015/7/1

Y1 - 2015/7/1

N2 - The enormous size and complexity of genotypic sequence space frequently requires consideration of coarse-grained sequences in empirical models. We develop scaling relations to quantify the effect of this coarse-graining on properties of fitness landscapes and evolutionary paths. We first consider evolution on a simple Mount Fuji fitness landscape, focusing on how the length and predictability of evolutionary paths scale with the coarse-grained sequence length and alphabet. We obtain simple scaling relations for both the weak- and strong-selection limits, with a non-trivial crossover regime at intermediate selection strengths. We apply these results to evolution on a biophysical fitness landscape that describes how proteins evolve new binding interactions while maintaining their folding stability. We combine the scaling relations with numerical calculations for coarse-grained protein sequences to obtain quantitative properties of the model for realistic binding interfaces and a full amino acid alphabet.

AB - The enormous size and complexity of genotypic sequence space frequently requires consideration of coarse-grained sequences in empirical models. We develop scaling relations to quantify the effect of this coarse-graining on properties of fitness landscapes and evolutionary paths. We first consider evolution on a simple Mount Fuji fitness landscape, focusing on how the length and predictability of evolutionary paths scale with the coarse-grained sequence length and alphabet. We obtain simple scaling relations for both the weak- and strong-selection limits, with a non-trivial crossover regime at intermediate selection strengths. We apply these results to evolution on a biophysical fitness landscape that describes how proteins evolve new binding interactions while maintaining their folding stability. We combine the scaling relations with numerical calculations for coarse-grained protein sequences to obtain quantitative properties of the model for realistic binding interfaces and a full amino acid alphabet.

KW - evolutionary paths

KW - fitness landscapes

KW - protein evolution

KW - random walks

KW - scaling

UR - http://www.scopus.com/inward/record.url?scp=84937548528&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84937548528&partnerID=8YFLogxK

U2 - https://doi.org/10.1088/1478-3975/12/4/045001

DO - https://doi.org/10.1088/1478-3975/12/4/045001

M3 - Article

C2 - 26020812

VL - 12

JO - Physical Biology

JF - Physical Biology

SN - 1478-3967

IS - 4

M1 - 045001

ER -