Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action

Failure of a protein to achieve its functional structural state and normal cellular location contributes to the etiology and pathology of heritable human conformational diseases. The autosomal dominant form of retinitis pigmentosa (adRP) is an incurable blindness largely linked to mutations of the m...

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Autores principales:	Angelo Felline, Davide Schiroli, Antonella Comitato, Valeria Marigo, Francesca Fanelli
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Molecular simulations Protein structure network Conformational diseases GPCRs Rhodopsin Pharmacological chaperones Biotechnology TP248.13-248.65
Acceso en línea:	https://doaj.org/article/6b05cf102d514fdb81a8be978d6899c1
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spelling	oai:doaj.org-article:6b05cf102d514fdb81a8be978d6899c12021-11-18T04:46:28ZStructure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action2001-037010.1016/j.csbj.2021.10.040https://doaj.org/article/6b05cf102d514fdb81a8be978d6899c12021-01-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2001037021004621https://doaj.org/toc/2001-0370Failure of a protein to achieve its functional structural state and normal cellular location contributes to the etiology and pathology of heritable human conformational diseases. The autosomal dominant form of retinitis pigmentosa (adRP) is an incurable blindness largely linked to mutations of the membrane protein rod opsin. While the mechanisms underlying the noxious effects of the mutated protein are not completely understood, a common feature is the functional protein conformational loss. Here, the wild type and 39 adRP rod opsin mutants were subjected to mechanical unfolding simulations coupled to the graph theory-based protein structure network analysis.A robust computational model was inferred and in vitro validated in its ability to predict endoplasmic reticulum retention of adRP mutants, a feature linked to the mutation-caused misfolding. The structure-based approach could also infer the structural determinants of small chaperone action on misfolded protein mutants with therapeutic implications.The approach is exportable to conformational diseases linked to missense mutations in any membrane protein.Angelo FellineDavide SchiroliAntonella ComitatoValeria MarigoFrancesca FanelliElsevierarticleMolecular simulationsProtein structure networkConformational diseasesGPCRsRhodopsinPharmacological chaperonesBiotechnologyTP248.13-248.65ENComputational and Structural Biotechnology Journal, Vol 19, Iss , Pp 6020-6038 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Molecular simulations Protein structure network Conformational diseases GPCRs Rhodopsin Pharmacological chaperones Biotechnology TP248.13-248.65
spellingShingle	Molecular simulations Protein structure network Conformational diseases GPCRs Rhodopsin Pharmacological chaperones Biotechnology TP248.13-248.65 Angelo Felline Davide Schiroli Antonella Comitato Valeria Marigo Francesca Fanelli Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action
description	Failure of a protein to achieve its functional structural state and normal cellular location contributes to the etiology and pathology of heritable human conformational diseases. The autosomal dominant form of retinitis pigmentosa (adRP) is an incurable blindness largely linked to mutations of the membrane protein rod opsin. While the mechanisms underlying the noxious effects of the mutated protein are not completely understood, a common feature is the functional protein conformational loss. Here, the wild type and 39 adRP rod opsin mutants were subjected to mechanical unfolding simulations coupled to the graph theory-based protein structure network analysis.A robust computational model was inferred and in vitro validated in its ability to predict endoplasmic reticulum retention of adRP mutants, a feature linked to the mutation-caused misfolding. The structure-based approach could also infer the structural determinants of small chaperone action on misfolded protein mutants with therapeutic implications.The approach is exportable to conformational diseases linked to missense mutations in any membrane protein.
format	article
author	Angelo Felline Davide Schiroli Antonella Comitato Valeria Marigo Francesca Fanelli
author_facet	Angelo Felline Davide Schiroli Antonella Comitato Valeria Marigo Francesca Fanelli
author_sort	Angelo Felline
title	Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action
title_short	Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action
title_full	Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action
title_fullStr	Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action
title_full_unstemmed	Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action
title_sort	structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/6b05cf102d514fdb81a8be978d6899c1
work_keys_str_mv	AT angelofelline structurenetworkbasedlandscapeofrhodopsinmisfoldingbymutationsandalgorithmicpredictionofsmallchaperoneaction AT davideschiroli structurenetworkbasedlandscapeofrhodopsinmisfoldingbymutationsandalgorithmicpredictionofsmallchaperoneaction AT antonellacomitato structurenetworkbasedlandscapeofrhodopsinmisfoldingbymutationsandalgorithmicpredictionofsmallchaperoneaction AT valeriamarigo structurenetworkbasedlandscapeofrhodopsinmisfoldingbymutationsandalgorithmicpredictionofsmallchaperoneaction AT francescafanelli structurenetworkbasedlandscapeofrhodopsinmisfoldingbymutationsandalgorithmicpredictionofsmallchaperoneaction
_version_	1718425044439269376

Structure network-based landscape of rhodopsin misfolding by mutations and algorithmic prediction of small chaperone action

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