Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.

Three-dimensional structures of proteins can provide important clues into the efficacy of personalized treatment. We perform a structural analysis of variants within three inherited lysosomal storage disorders, comparing variants responsive to pharmacological chaperone treatment to those unresponsiv...

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Autores principales:	Jaie Woodard, Wei Zheng, Yang Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/ee74011334104e0aae5ed77ec63b1276
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spelling	oai:doaj.org-article:ee74011334104e0aae5ed77ec63b12762021-12-02T19:57:46ZProtein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.1553-734X1553-735810.1371/journal.pcbi.1009370https://doaj.org/article/ee74011334104e0aae5ed77ec63b12762021-09-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009370https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358Three-dimensional structures of proteins can provide important clues into the efficacy of personalized treatment. We perform a structural analysis of variants within three inherited lysosomal storage disorders, comparing variants responsive to pharmacological chaperone treatment to those unresponsive to such treatment. We find that predicted ΔΔG of mutation is higher on average for variants unresponsive to treatment, in the case of datasets for both Fabry disease and Pompe disease, in line with previous findings. Using both a single decision tree and an advanced machine learning approach based on the larger Fabry dataset, we correctly predict responsiveness of three Gaucher disease variants, and we provide predictions for untested variants. Many variants are predicted to be responsive to treatment, suggesting that drug-based treatments may be effective for a number of variants in Gaucher disease. In our analysis, we observe dependence on a topological feature reporting on contact arrangements which is likely connected to the order of folding of protein residues, and we provide a potential justification for this observation based on steady-state cellular kinetics.Jaie WoodardWei ZhengYang ZhangPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 9, p e1009370 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Jaie Woodard Wei Zheng Yang Zhang Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.
description	Three-dimensional structures of proteins can provide important clues into the efficacy of personalized treatment. We perform a structural analysis of variants within three inherited lysosomal storage disorders, comparing variants responsive to pharmacological chaperone treatment to those unresponsive to such treatment. We find that predicted ΔΔG of mutation is higher on average for variants unresponsive to treatment, in the case of datasets for both Fabry disease and Pompe disease, in line with previous findings. Using both a single decision tree and an advanced machine learning approach based on the larger Fabry dataset, we correctly predict responsiveness of three Gaucher disease variants, and we provide predictions for untested variants. Many variants are predicted to be responsive to treatment, suggesting that drug-based treatments may be effective for a number of variants in Gaucher disease. In our analysis, we observe dependence on a topological feature reporting on contact arrangements which is likely connected to the order of folding of protein residues, and we provide a potential justification for this observation based on steady-state cellular kinetics.
format	article
author	Jaie Woodard Wei Zheng Yang Zhang
author_facet	Jaie Woodard Wei Zheng Yang Zhang
author_sort	Jaie Woodard
title	Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.
title_short	Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.
title_full	Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.
title_fullStr	Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.
title_full_unstemmed	Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.
title_sort	protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/ee74011334104e0aae5ed77ec63b1276
work_keys_str_mv	AT jaiewoodard proteinstructuralfeaturespredictresponsivenesstopharmacologicalchaperonetreatmentforthreelysosomalstoragedisorders AT weizheng proteinstructuralfeaturespredictresponsivenesstopharmacologicalchaperonetreatmentforthreelysosomalstoragedisorders AT yangzhang proteinstructuralfeaturespredictresponsivenesstopharmacologicalchaperonetreatmentforthreelysosomalstoragedisorders
_version_	1718375814145245184

Protein structural features predict responsiveness to pharmacological chaperone treatment for three lysosomal storage disorders.

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