Literature DB >> 28057858

ProtASR: An Evolutionary Framework for Ancestral Protein Reconstruction with Selection on Folding Stability.

Miguel Arenas1,2,3,4, Claudia C Weber5, David A Liberles6,5, Ugo Bastolla3.   

Abstract

The computational reconstruction of ancestral proteins provides information on past biological events and has practical implications for biomedicine and biotechnology. Currently available tools for ancestral sequence reconstruction (ASR) are often based on empirical amino acid substitution models that assume that all sites evolve at the same rate and under the same process. However, this assumption is frequently violated because protein evolution is highly heterogeneous due to different selective constraints among sites. Here, we present ProtASR, a new evolutionary framework to infer ancestral protein sequences accounting for selection on protein stability. First, ProtASR generates site-specific substitution matrices through the structurally constrained mean-field (MF) substitution model, which considers both unfolding and misfolding stability. We previously showed that MF models outperform empirical amino acid substitution models, as well as other structurally constrained substitution models, both in terms of likelihood and correctly inferring amino acid distributions across sites. In the second step, ProtASR adapts a well-established maximum-likelihood (ML) ASR procedure to infer ancestral proteins under MF models. A known bias of ML ASR methods is that they tend to overestimate the stability of ancestral proteins by underestimating the frequency of deleterious mutations. We compared ProtASR under MF to two empirical substitution models (JTT and CAT), reconstructing the ancestral sequences of simulated proteins. ProtASR yields reconstructed proteins with less biased stabilities, which are significantly closer to those of the simulated proteins. Analysis of extant protein families suggests that folding stability evolves through time across protein families, potentially reflecting neutral fluctuation. Some families exhibit a more constant protein folding stability, while others are more variable. ProtASR is freely available from https://github.com/miguelarenas/protasr and includes detailed documentation and ready-to-use examples. It runs in seconds/minutes depending on protein length and alignment size. [Ancestral sequence reconstruction; folding stability; molecular adaptation; phylogenetics; protein evolution; protein structure.].
© The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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Year:  2017        PMID: 28057858     DOI: 10.1093/sysbio/syw121

Source DB:  PubMed          Journal:  Syst Biol        ISSN: 1063-5157            Impact factor:   15.683


  14 in total

1.  Evolutionary Modes in Protein Observable Space: The Case of Thioredoxins.

Authors:  Sara Del Galdo; Josephine Alba; Andrea Amadei; Marco D'Abramo
Journal:  J Mol Evol       Date:  2019-05-25       Impact factor: 2.395

2.  mtProtEvol: the resource presenting molecular evolution analysis of proteins involved in the function of Vertebrate mitochondria.

Authors:  Anastasia A Kuzminkova; Anastasia D Sokol; Kristina E Ushakova; Konstantin Yu Popadin; Konstantin V Gunbin
Journal:  BMC Evol Biol       Date:  2019-02-26       Impact factor: 3.260

3.  A Darwinian Uncertainty Principle.

Authors:  Olivier Gascuel; Mike Steel
Journal:  Syst Biol       Date:  2020-05-01       Impact factor: 15.683

Review 4.  Methodologies for Microbial Ancestral Sequence Reconstruction.

Authors:  Miguel Arenas
Journal:  Methods Mol Biol       Date:  2022

5.  Consequences of Substitution Model Selection on Protein Ancestral Sequence Reconstruction.

Authors:  Roberto Del Amparo; Miguel Arenas
Journal:  Mol Biol Evol       Date:  2022-07-02       Impact factor: 8.800

6.  Influence of mutation bias and hydrophobicity on the substitution rates and sequence entropies of protein evolution.

Authors:  María José Jiménez-Santos; Miguel Arenas; Ugo Bastolla
Journal:  PeerJ       Date:  2018-10-05       Impact factor: 2.984

7.  Modeling Structural Constraints on Protein Evolution via Side-Chain Conformational States.

Authors:  Umberto Perron; Alexey M Kozlov; Alexandros Stamatakis; Nick Goldman; Iain H Moal
Journal:  Mol Biol Evol       Date:  2019-09-01       Impact factor: 16.240

Review 8.  Using the Mutation-Selection Framework to Characterize Selection on Protein Sequences.

Authors:  Ashley I Teufel; Andrew M Ritchie; Claus O Wilke; David A Liberles
Journal:  Genes (Basel)       Date:  2018-08-13       Impact factor: 4.096

9.  Accuracy of ancestral state reconstruction for non-neutral traits.

Authors:  Barbara R Holland; Saan Ketelaar-Jones; Aidan R O'Mara; Michael D Woodhams; Gregory J Jordan
Journal:  Sci Rep       Date:  2020-05-06       Impact factor: 4.379

10.  Alignment-Integrated Reconstruction of Ancestral Sequences Improves Accuracy.

Authors:  Kelsey Aadland; Bryan Kolaczkowski
Journal:  Genome Biol Evol       Date:  2020-09-01       Impact factor: 3.416

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