Literature DB >> 24952216

Merging molecular mechanism and evolution: theory and computation at the interface of biophysics and evolutionary population genetics.

Adrian W R Serohijos1, Eugene I Shakhnovich2.   

Abstract

The variation among sequences and structures in nature is both determined by physical laws and by evolutionary history. However, these two factors are traditionally investigated by disciplines with different emphasis and philosophy-molecular biophysics on one hand and evolutionary population genetics in another. Here, we review recent theoretical and computational approaches that address the crucial need to integrate these two disciplines. We first articulate the elements of these approaches. Then, we survey their contribution to our mechanistic understanding of molecular evolution, the polymorphisms in coding region, the distribution of fitness effects (DFE) of mutations, the observed folding stability of proteins in nature, and the distribution of protein folds in genomes.
Copyright © 2014 Elsevier Ltd. All rights reserved.

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Year:  2014        PMID: 24952216      PMCID: PMC4292934          DOI: 10.1016/j.sbi.2014.05.005

Source DB:  PubMed          Journal:  Curr Opin Struct Biol        ISSN: 0959-440X            Impact factor:   6.809


  78 in total

1.  Protein model discrimination using mutational sensitivity derived from deep sequencing.

Authors:  Bharat V Adkar; Arti Tripathi; Anusmita Sahoo; Kanika Bajaj; Devrishi Goswami; Purbani Chakrabarti; Mohit K Swarnkar; Rajesh S Gokhale; Raghavan Varadarajan
Journal:  Structure       Date:  2012-02-08       Impact factor: 5.006

Review 2.  Mutational effects and the evolution of new protein functions.

Authors:  Misha Soskine; Dan S Tawfik
Journal:  Nat Rev Genet       Date:  2010-08       Impact factor: 53.242

3.  The evolution and evolutionary consequences of marginal thermostability in proteins.

Authors:  Richard A Goldstein
Journal:  Proteins       Date:  2011-02-18

4.  Topology of protein interaction network shapes protein abundances and strengths of their functional and nonspecific interactions.

Authors:  Muyoung Heo; Sergei Maslov; Eugene Shakhnovich
Journal:  Proc Natl Acad Sci U S A       Date:  2011-02-22       Impact factor: 11.205

5.  A biophysical protein folding model accounts for most mutational fitness effects in viruses.

Authors:  C Scott Wylie; Eugene I Shakhnovich
Journal:  Proc Natl Acad Sci U S A       Date:  2011-05-24       Impact factor: 11.205

6.  Soluble oligomerization provides a beneficial fitness effect on destabilizing mutations.

Authors:  Shimon Bershtein; Wanmeng Mu; Wanmeng Wu; Eugene I Shakhnovich
Journal:  Proc Natl Acad Sci U S A       Date:  2012-03-12       Impact factor: 11.205

7.  Non-adaptive origins of interactome complexity.

Authors:  Ariel Fernández; Michael Lynch
Journal:  Nature       Date:  2011-05-18       Impact factor: 49.962

8.  Virtual genomes in flux: an interplay of neutrality and adaptability explains genome expansion and streamlining.

Authors:  Thomas D Cuypers; Paulien Hogeweg
Journal:  Genome Biol Evol       Date:  2012-01-10       Impact factor: 3.416

Review 9.  Bringing molecules back into molecular evolution.

Authors:  Claus O Wilke
Journal:  PLoS Comput Biol       Date:  2012-06-28       Impact factor: 4.475

10.  Simulated evolution of protein-protein interaction networks with realistic topology.

Authors:  G Jack Peterson; Steve Pressé; Kristin S Peterson; Ken A Dill
Journal:  PLoS One       Date:  2012-06-29       Impact factor: 3.240

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  40 in total

1.  Reconstructed Ancestral Enzymes Impose a Fitness Cost upon Modern Bacteria Despite Exhibiting Favourable Biochemical Properties.

Authors:  Joanne K Hobbs; Erica J Prentice; Mathieu Groussin; Vickery L Arcus
Journal:  J Mol Evol       Date:  2015-09-09       Impact factor: 2.395

2.  Simulations reveal challenges to artificial community selection and possible strategies for success.

Authors:  Li Xie; Alex E Yuan; Wenying Shou
Journal:  PLoS Biol       Date:  2019-06-25       Impact factor: 8.029

Review 3.  Effective models and the search for quantitative principles in microbial evolution.

Authors:  Benjamin H Good; Oskar Hallatschek
Journal:  Curr Opin Microbiol       Date:  2018-12-06       Impact factor: 7.934

4.  Influence of multiple-sequence-alignment depth on Potts statistical models of protein covariation.

Authors:  Allan Haldane; Ronald M Levy
Journal:  Phys Rev E       Date:  2019-03       Impact factor: 2.529

5.  The Role of Evolutionary Selection in the Dynamics of Protein Structure Evolution.

Authors:  Amy I Gilson; Ahmee Marshall-Christensen; Jeong-Mo Choi; Eugene I Shakhnovich
Journal:  Biophys J       Date:  2017-04-11       Impact factor: 4.033

6.  Hidden long evolutionary memory in a model biochemical network.

Authors:  Md Zulfikar Ali; Ned S Wingreen; Ranjan Mukhopadhyay
Journal:  Phys Rev E       Date:  2018-04       Impact factor: 2.529

Review 7.  Decoding mechanisms by which silent codon changes influence protein biogenesis and function.

Authors:  Vedrana Bali; Zsuzsanna Bebok
Journal:  Int J Biochem Cell Biol       Date:  2015-03-26       Impact factor: 5.085

8.  Evolutionary dynamics of viral escape under antibodies stress: A biophysical model.

Authors:  Nicolas Chéron; Adrian W R Serohijos; Jeong-Mo Choi; Eugene I Shakhnovich
Journal:  Protein Sci       Date:  2016-03-24       Impact factor: 6.725

9.  Data-driven supervised learning of a viral protease specificity landscape from deep sequencing and molecular simulations.

Authors:  Manasi A Pethe; Aliza B Rubenstein; Sagar D Khare
Journal:  Proc Natl Acad Sci U S A       Date:  2018-12-26       Impact factor: 11.205

10.  Effect of Protein Structure on Evolution of Cotranslational Folding.

Authors:  Victor Zhao; William M Jacobs; Eugene I Shakhnovich
Journal:  Biophys J       Date:  2020-08-12       Impact factor: 4.033

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