Literature DB >> 25438718

Topological features of rugged fitness landscapes in sequence space.

Dmitry A Kondrashov1, Fyodor A Kondrashov2.   

Abstract

The factors that determine the tempo and mode of protein evolution continue to be a central question in molecular evolution. Traditionally, studies of protein evolution focused on the rates of amino acid substitutions. More recently, with the availability of sequence data and advanced experimental techniques, the focus of attention has shifted toward the study of evolutionary trajectories and the overall layout of protein fitness landscapes. In this review we describe the effect of epistasis on the topology of evolutionary pathways that are likely to be found in fitness landscapes and develop a simple theory to connect the number of maladapted genotypes to the topology of fitness landscapes with epistatic interactions. Finally, we review recent studies that have probed the extent of epistatic interactions and have begun to chart the fitness landscapes in protein sequence space.
Copyright © 2014 Elsevier Ltd. All rights reserved.

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Year:  2014        PMID: 25438718     DOI: 10.1016/j.tig.2014.09.009

Source DB:  PubMed          Journal:  Trends Genet        ISSN: 0168-9525            Impact factor:   11.639


  33 in total

Review 1.  Changing preferences: deformation of single position amino acid fitness landscapes and evolution of proteins.

Authors:  Georgii A Bazykin
Journal:  Biol Lett       Date:  2015-10       Impact factor: 3.703

Review 2.  Epistasis in protein evolution.

Authors:  Tyler N Starr; Joseph W Thornton
Journal:  Protein Sci       Date:  2016-02-28       Impact factor: 6.725

Review 3.  Evolutionary consequences of drug resistance: shared principles across diverse targets and organisms.

Authors:  Diarmaid Hughes; Dan I Andersson
Journal:  Nat Rev Genet       Date:  2015-07-07       Impact factor: 53.242

4.  Average Fitness Differences on NK Landscapes.

Authors:  Wim Hordijk; Stuart A Kauffman; Peter F Stadler
Journal:  Theory Biosci       Date:  2019-06-18       Impact factor: 1.919

Review 5.  Prediction of antibiotic resistance: time for a new preclinical paradigm?

Authors:  Morten O A Sommer; Christian Munck; Rasmus Vendler Toft-Kehler; Dan I Andersson
Journal:  Nat Rev Microbiol       Date:  2017-07-31       Impact factor: 60.633

6.  Spiraling Complexity: A Test of the Snowball Effect in a Computational Model of RNA Folding.

Authors:  Ata Kalirad; Ricardo B R Azevedo
Journal:  Genetics       Date:  2016-12-22       Impact factor: 4.562

7.  Inferring the shape of global epistasis.

Authors:  Jakub Otwinowski; David M McCandlish; Joshua B Plotkin
Journal:  Proc Natl Acad Sci U S A       Date:  2018-07-23       Impact factor: 11.205

8.  Epistasis and the Dynamics of Reversion in Molecular Evolution.

Authors:  David M McCandlish; Premal Shah; Joshua B Plotkin
Journal:  Genetics       Date:  2016-05-18       Impact factor: 4.562

9.  Learning epistatic interactions from sequence-activity data to predict enantioselectivity.

Authors:  Julian Zaugg; Yosephine Gumulya; Alpeshkumar K Malde; Mikael Bodén
Journal:  J Comput Aided Mol Des       Date:  2017-12-12       Impact factor: 3.686

10.  Minimum epistasis interpolation for sequence-function relationships.

Authors:  Juannan Zhou; David M McCandlish
Journal:  Nat Commun       Date:  2020-04-14       Impact factor: 14.919

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