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Structural Phylogenetics with Confidence

For evaluating the deepest evolutionary relationships among proteins, sequence similarity is too low for application of sequence-based homology search or phylogenetic methods. In such cases, comparison of protein structures, which are often better conserved than sequences, may provide an alternative...

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Autores principales: Malik, Ashar J, Poole, Anthony M, Allison, Jane R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7475046/
https://www.ncbi.nlm.nih.gov/pubmed/32302382
http://dx.doi.org/10.1093/molbev/msaa100
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author Malik, Ashar J
Poole, Anthony M
Allison, Jane R
author_facet Malik, Ashar J
Poole, Anthony M
Allison, Jane R
author_sort Malik, Ashar J
collection PubMed
description For evaluating the deepest evolutionary relationships among proteins, sequence similarity is too low for application of sequence-based homology search or phylogenetic methods. In such cases, comparison of protein structures, which are often better conserved than sequences, may provide an alternative means of uncovering deep evolutionary signal. Although major protein structure databases such as SCOP and CATH hierarchically group protein structures, they do not describe the specific evolutionary relationships within a hierarchical level. Structural phylogenies have the potential to fill this gap. However, it is difficult to assess evolutionary relationships derived from structural phylogenies without some means of assessing confidence in such trees. We therefore address two shortcomings in the application of structural data to deep phylogeny. First, we examine whether phylogenies derived from pairwise structural comparisons are sensitive to differences in protein length and shape. We find that structural phylogenetics is best employed where structures have very similar lengths, and that shape fluctuations generated during molecular dynamics simulations impact pairwise comparisons, but not so drastically as to eliminate evolutionary signal. Second, we address the absence of statistical support for structural phylogeny. We present a method for assessing confidence in a structural phylogeny using shape fluctuations generated via molecular dynamics or Monte Carlo simulations of proteins. Our approach will aid the evolutionary reconstruction of relationships across structurally defined protein superfamilies. With the Protein Data Bank now containing in excess of 158,000 entries (December 2019), we predict that structural phylogenetics will become a useful tool for ordering the protein universe.
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spelling pubmed-74750462020-09-10 Structural Phylogenetics with Confidence Malik, Ashar J Poole, Anthony M Allison, Jane R Mol Biol Evol Methods For evaluating the deepest evolutionary relationships among proteins, sequence similarity is too low for application of sequence-based homology search or phylogenetic methods. In such cases, comparison of protein structures, which are often better conserved than sequences, may provide an alternative means of uncovering deep evolutionary signal. Although major protein structure databases such as SCOP and CATH hierarchically group protein structures, they do not describe the specific evolutionary relationships within a hierarchical level. Structural phylogenies have the potential to fill this gap. However, it is difficult to assess evolutionary relationships derived from structural phylogenies without some means of assessing confidence in such trees. We therefore address two shortcomings in the application of structural data to deep phylogeny. First, we examine whether phylogenies derived from pairwise structural comparisons are sensitive to differences in protein length and shape. We find that structural phylogenetics is best employed where structures have very similar lengths, and that shape fluctuations generated during molecular dynamics simulations impact pairwise comparisons, but not so drastically as to eliminate evolutionary signal. Second, we address the absence of statistical support for structural phylogeny. We present a method for assessing confidence in a structural phylogeny using shape fluctuations generated via molecular dynamics or Monte Carlo simulations of proteins. Our approach will aid the evolutionary reconstruction of relationships across structurally defined protein superfamilies. With the Protein Data Bank now containing in excess of 158,000 entries (December 2019), we predict that structural phylogenetics will become a useful tool for ordering the protein universe. Oxford University Press 2020-04-17 /pmc/articles/PMC7475046/ /pubmed/32302382 http://dx.doi.org/10.1093/molbev/msaa100 Text en © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. http://creativecommons.org/licenses/by/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Methods
Malik, Ashar J
Poole, Anthony M
Allison, Jane R
Structural Phylogenetics with Confidence
title Structural Phylogenetics with Confidence
title_full Structural Phylogenetics with Confidence
title_fullStr Structural Phylogenetics with Confidence
title_full_unstemmed Structural Phylogenetics with Confidence
title_short Structural Phylogenetics with Confidence
title_sort structural phylogenetics with confidence
topic Methods
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7475046/
https://www.ncbi.nlm.nih.gov/pubmed/32302382
http://dx.doi.org/10.1093/molbev/msaa100
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