Computational redesign of a fluorogen activating protein with Rosetta.

The use of unnatural fluorogenic molecules widely expands the pallet of available genetically encoded fluorescent imaging tools through the design of fluorogen activating proteins (FAPs). While there is already a handful of such probes available, each of them went through laborious cycles of in vitr...

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Autores principales:	Nina G Bozhanova, Joel M Harp, Brian J Bender, Alexey S Gavrikov, Dmitry A Gorbachev, Mikhail S Baranov, Christina B Mercado, Xuan Zhang, Konstantin A Lukyanov, Alexander S Mishin, Jens Meiler
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/db709dc63ab7480d90a2d7fc01f83e8c
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spelling	oai:doaj.org-article:db709dc63ab7480d90a2d7fc01f83e8c2021-12-02T19:57:58ZComputational redesign of a fluorogen activating protein with Rosetta.1553-734X1553-735810.1371/journal.pcbi.1009555https://doaj.org/article/db709dc63ab7480d90a2d7fc01f83e8c2021-11-01T00:00:00Zhttps://doi.org/10.1371/journal.pcbi.1009555https://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358The use of unnatural fluorogenic molecules widely expands the pallet of available genetically encoded fluorescent imaging tools through the design of fluorogen activating proteins (FAPs). While there is already a handful of such probes available, each of them went through laborious cycles of in vitro screening and selection. Computational modeling approaches are evolving incredibly fast right now and are demonstrating great results in many applications, including de novo protein design. It suggests that the easier task of fine-tuning the fluorogen-binding properties of an already functional protein in silico should be readily achievable. To test this hypothesis, we used Rosetta for computational ligand docking followed by protein binding pocket redesign to further improve the previously described FAP DiB1 that is capable of binding to a BODIPY-like dye M739. Despite an inaccurate initial docking of the chromophore, the incorporated mutations nevertheless improved multiple photophysical parameters as well as the overall performance of the tag. The designed protein, DiB-RM, shows higher brightness, localization precision, and apparent photostability in protein-PAINT super-resolution imaging compared to its parental variant DiB1. Moreover, DiB-RM can be cleaved to obtain an efficient split system with enhanced performance compared to a parental DiB-split system. The possible reasons for the inaccurate ligand binding pose prediction and its consequence on the outcome of the design experiment are further discussed.Nina G BozhanovaJoel M HarpBrian J BenderAlexey S GavrikovDmitry A GorbachevMikhail S BaranovChristina B MercadoXuan ZhangKonstantin A LukyanovAlexander S MishinJens MeilerPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 11, p e1009555 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Nina G Bozhanova Joel M Harp Brian J Bender Alexey S Gavrikov Dmitry A Gorbachev Mikhail S Baranov Christina B Mercado Xuan Zhang Konstantin A Lukyanov Alexander S Mishin Jens Meiler Computational redesign of a fluorogen activating protein with Rosetta.
description	The use of unnatural fluorogenic molecules widely expands the pallet of available genetically encoded fluorescent imaging tools through the design of fluorogen activating proteins (FAPs). While there is already a handful of such probes available, each of them went through laborious cycles of in vitro screening and selection. Computational modeling approaches are evolving incredibly fast right now and are demonstrating great results in many applications, including de novo protein design. It suggests that the easier task of fine-tuning the fluorogen-binding properties of an already functional protein in silico should be readily achievable. To test this hypothesis, we used Rosetta for computational ligand docking followed by protein binding pocket redesign to further improve the previously described FAP DiB1 that is capable of binding to a BODIPY-like dye M739. Despite an inaccurate initial docking of the chromophore, the incorporated mutations nevertheless improved multiple photophysical parameters as well as the overall performance of the tag. The designed protein, DiB-RM, shows higher brightness, localization precision, and apparent photostability in protein-PAINT super-resolution imaging compared to its parental variant DiB1. Moreover, DiB-RM can be cleaved to obtain an efficient split system with enhanced performance compared to a parental DiB-split system. The possible reasons for the inaccurate ligand binding pose prediction and its consequence on the outcome of the design experiment are further discussed.
format	article
author	Nina G Bozhanova Joel M Harp Brian J Bender Alexey S Gavrikov Dmitry A Gorbachev Mikhail S Baranov Christina B Mercado Xuan Zhang Konstantin A Lukyanov Alexander S Mishin Jens Meiler
author_facet	Nina G Bozhanova Joel M Harp Brian J Bender Alexey S Gavrikov Dmitry A Gorbachev Mikhail S Baranov Christina B Mercado Xuan Zhang Konstantin A Lukyanov Alexander S Mishin Jens Meiler
author_sort	Nina G Bozhanova
title	Computational redesign of a fluorogen activating protein with Rosetta.
title_short	Computational redesign of a fluorogen activating protein with Rosetta.
title_full	Computational redesign of a fluorogen activating protein with Rosetta.
title_fullStr	Computational redesign of a fluorogen activating protein with Rosetta.
title_full_unstemmed	Computational redesign of a fluorogen activating protein with Rosetta.
title_sort	computational redesign of a fluorogen activating protein with rosetta.
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/db709dc63ab7480d90a2d7fc01f83e8c
work_keys_str_mv	AT ninagbozhanova computationalredesignofafluorogenactivatingproteinwithrosetta AT joelmharp computationalredesignofafluorogenactivatingproteinwithrosetta AT brianjbender computationalredesignofafluorogenactivatingproteinwithrosetta AT alexeysgavrikov computationalredesignofafluorogenactivatingproteinwithrosetta AT dmitryagorbachev computationalredesignofafluorogenactivatingproteinwithrosetta AT mikhailsbaranov computationalredesignofafluorogenactivatingproteinwithrosetta AT christinabmercado computationalredesignofafluorogenactivatingproteinwithrosetta AT xuanzhang computationalredesignofafluorogenactivatingproteinwithrosetta AT konstantinalukyanov computationalredesignofafluorogenactivatingproteinwithrosetta AT alexandersmishin computationalredesignofafluorogenactivatingproteinwithrosetta AT jensmeiler computationalredesignofafluorogenactivatingproteinwithrosetta
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Computational redesign of a fluorogen activating protein with Rosetta.

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