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PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations
Evolutionary conservation is a fundamental resource for predicting the substitutability of amino acids and the loss of function in proteins. The use of multiple sequence alignment alone—without considering the evolutionary relationships among sequences—results in the redundant counting of evolutiona...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9178230/ https://www.ncbi.nlm.nih.gov/pubmed/35639618 http://dx.doi.org/10.1093/molbev/msac114 |
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author | Kuru, Nurdan Dereli, Onur Akkoyun, Emrah Bircan, Aylin Tastan, Oznur Adebali, Ogun |
author_facet | Kuru, Nurdan Dereli, Onur Akkoyun, Emrah Bircan, Aylin Tastan, Oznur Adebali, Ogun |
author_sort | Kuru, Nurdan |
collection | PubMed |
description | Evolutionary conservation is a fundamental resource for predicting the substitutability of amino acids and the loss of function in proteins. The use of multiple sequence alignment alone—without considering the evolutionary relationships among sequences—results in the redundant counting of evolutionarily related alteration events, as if they were independent. Here, we propose a new method, PHACT, that predicts the pathogenicity of missense mutations directly from the phylogenetic tree of proteins. PHACT travels through the nodes of the phylogenetic tree and evaluates the deleteriousness of a substitution based on the probability differences of ancestral amino acids between neighboring nodes in the tree. Moreover, PHACT assigns weights to each node in the tree based on their distance to the query organism. For each potential amino acid substitution, the algorithm generates a score that is used to calculate the effect of substitution on protein function. To analyze the predictive performance of PHACT, we performed various experiments over the subsets of two datasets that include 3,023 proteins and 61,662 variants in total. The experiments demonstrated that our method outperformed the widely used pathogenicity prediction tools (i.e., SIFT and PolyPhen-2) and achieved a better predictive performance than other conventional statistical approaches presented in dbNSFP. The PHACT source code is available at https://github.com/CompGenomeLab/PHACT. |
format | Online Article Text |
id | pubmed-9178230 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-91782302022-06-09 PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations Kuru, Nurdan Dereli, Onur Akkoyun, Emrah Bircan, Aylin Tastan, Oznur Adebali, Ogun Mol Biol Evol Methods Evolutionary conservation is a fundamental resource for predicting the substitutability of amino acids and the loss of function in proteins. The use of multiple sequence alignment alone—without considering the evolutionary relationships among sequences—results in the redundant counting of evolutionarily related alteration events, as if they were independent. Here, we propose a new method, PHACT, that predicts the pathogenicity of missense mutations directly from the phylogenetic tree of proteins. PHACT travels through the nodes of the phylogenetic tree and evaluates the deleteriousness of a substitution based on the probability differences of ancestral amino acids between neighboring nodes in the tree. Moreover, PHACT assigns weights to each node in the tree based on their distance to the query organism. For each potential amino acid substitution, the algorithm generates a score that is used to calculate the effect of substitution on protein function. To analyze the predictive performance of PHACT, we performed various experiments over the subsets of two datasets that include 3,023 proteins and 61,662 variants in total. The experiments demonstrated that our method outperformed the widely used pathogenicity prediction tools (i.e., SIFT and PolyPhen-2) and achieved a better predictive performance than other conventional statistical approaches presented in dbNSFP. The PHACT source code is available at https://github.com/CompGenomeLab/PHACT. Oxford University Press 2022-05-26 /pmc/articles/PMC9178230/ /pubmed/35639618 http://dx.doi.org/10.1093/molbev/msac114 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution. https://creativecommons.org/licenses/by-nc/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com |
spellingShingle | Methods Kuru, Nurdan Dereli, Onur Akkoyun, Emrah Bircan, Aylin Tastan, Oznur Adebali, Ogun PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations |
title | PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations |
title_full | PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations |
title_fullStr | PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations |
title_full_unstemmed | PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations |
title_short | PHACT: Phylogeny-Aware Computing of Tolerance for Missense Mutations |
title_sort | phact: phylogeny-aware computing of tolerance for missense mutations |
topic | Methods |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9178230/ https://www.ncbi.nlm.nih.gov/pubmed/35639618 http://dx.doi.org/10.1093/molbev/msac114 |
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