Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones

To help cells cope with protein misfolding and aggregation, Hsp70 molecular chaperones selectively bind a variety of sequences (“selective promiscuity”). Statistical analyses from substrate-derived peptide arrays reveal that DnaK, the E. coli Hsp70, binds to sequences containing three to five branch...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Erik B. Nordquist, Charles A. English, Eugenia M. Clerico, Woody Sherman, Lila M. Gierasch, Jianhan Chen
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2021
Materias:	Biology (General) QH301-705.5
Acceso en línea:	https://doaj.org/article/ad3b0c700af84c299fcbf138aa4bb030
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:ad3b0c700af84c299fcbf138aa4bb030
record_format	dspace
spelling	oai:doaj.org-article:ad3b0c700af84c299fcbf138aa4bb0302021-11-25T05:42:04ZPhysics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones1553-734X1553-7358https://doaj.org/article/ad3b0c700af84c299fcbf138aa4bb0302021-11-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8604352/?tool=EBIhttps://doaj.org/toc/1553-734Xhttps://doaj.org/toc/1553-7358To help cells cope with protein misfolding and aggregation, Hsp70 molecular chaperones selectively bind a variety of sequences (“selective promiscuity”). Statistical analyses from substrate-derived peptide arrays reveal that DnaK, the E. coli Hsp70, binds to sequences containing three to five branched hydrophobic residues, although otherwise the specific amino acids can vary considerably. Several high-resolution structures of the substrate -binding domain (SBD) of DnaK bound to peptides reveal a highly conserved configuration of the bound substrate and further suggest that the substrate-binding cleft consists of five largely independent sites for interaction with five consecutive substrate residues. Importantly, both substrate backbone orientations (N- to C- and C- to N-) allow essentially the same backbone hydrogen-bonding and side-chain interactions with the chaperone. In order to rationalize these observations, we performed atomistic molecular dynamics simulations to sample the interactions of all 20 amino acid side chains in each of the five sites of the chaperone in the context of the conserved substrate backbone configurations. The resulting interaction energetics provide the basis set for deriving a predictive model that we call Paladin (Physics-based model of DnaK-Substrate Binding). Trained using available peptide array data, Paladin can distinguish binders and nonbinders of DnaK with accuracy comparable to existing predictors and further predicts the detailed configuration of the bound sequence. Tested using existing DnaK-peptide structures, Paladin correctly predicted the binding register in 10 out of 13 substrate sequences that bind in the N- to C- orientation, and the binding orientation in 16 out of 22 sequences. The physical basis of the Paladin model provides insight into the origins of how Hsp70s bind substrates with a balance of selectivity and promiscuity. The approach described here can be extended to other Hsp70s where extensive peptide array data is not available. Author summary Molecular chaperones are proteins that help prevent misfolding and aggregation of their substrates. This is a complex task, as the cell is very crowded, and the chaperone must efficiently bind to misfolded regions of the client protein while avoiding well-folded proteins. An additional confounding detail is that proteins can enter the binding cleft of some Hsp70s in two orientations, a fact often unaccounted for by existing sequence-based models. Here, we developed a model to describe how client proteins bind to DnaK, the E. coli Hsp70, using physics-based molecular dynamics simulations to quantify the interactions between a variety of peptide substrates and key sites on DnaK. The resulting model, which we call Paladin, provides a physical basis to understand how DnaK binds to specific peptides. Given a sequence, Paladin can predict the precise residues that bind at a specific site on DnaK and can further explain challenging features like the binding orientation, which are typically not predicted by sequence-only models. The Paladin model could be used to design ‘super-binder’ therapeutic peptides to inhibit chaperones like DnaK in E. coli.Erik B. NordquistCharles A. EnglishEugenia M. ClericoWoody ShermanLila M. GieraschJianhan ChenPublic Library of Science (PLoS)articleBiology (General)QH301-705.5ENPLoS Computational Biology, Vol 17, Iss 11 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Biology (General) QH301-705.5
spellingShingle	Biology (General) QH301-705.5 Erik B. Nordquist Charles A. English Eugenia M. Clerico Woody Sherman Lila M. Gierasch Jianhan Chen Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones
description	To help cells cope with protein misfolding and aggregation, Hsp70 molecular chaperones selectively bind a variety of sequences (“selective promiscuity”). Statistical analyses from substrate-derived peptide arrays reveal that DnaK, the E. coli Hsp70, binds to sequences containing three to five branched hydrophobic residues, although otherwise the specific amino acids can vary considerably. Several high-resolution structures of the substrate -binding domain (SBD) of DnaK bound to peptides reveal a highly conserved configuration of the bound substrate and further suggest that the substrate-binding cleft consists of five largely independent sites for interaction with five consecutive substrate residues. Importantly, both substrate backbone orientations (N- to C- and C- to N-) allow essentially the same backbone hydrogen-bonding and side-chain interactions with the chaperone. In order to rationalize these observations, we performed atomistic molecular dynamics simulations to sample the interactions of all 20 amino acid side chains in each of the five sites of the chaperone in the context of the conserved substrate backbone configurations. The resulting interaction energetics provide the basis set for deriving a predictive model that we call Paladin (Physics-based model of DnaK-Substrate Binding). Trained using available peptide array data, Paladin can distinguish binders and nonbinders of DnaK with accuracy comparable to existing predictors and further predicts the detailed configuration of the bound sequence. Tested using existing DnaK-peptide structures, Paladin correctly predicted the binding register in 10 out of 13 substrate sequences that bind in the N- to C- orientation, and the binding orientation in 16 out of 22 sequences. The physical basis of the Paladin model provides insight into the origins of how Hsp70s bind substrates with a balance of selectivity and promiscuity. The approach described here can be extended to other Hsp70s where extensive peptide array data is not available. Author summary Molecular chaperones are proteins that help prevent misfolding and aggregation of their substrates. This is a complex task, as the cell is very crowded, and the chaperone must efficiently bind to misfolded regions of the client protein while avoiding well-folded proteins. An additional confounding detail is that proteins can enter the binding cleft of some Hsp70s in two orientations, a fact often unaccounted for by existing sequence-based models. Here, we developed a model to describe how client proteins bind to DnaK, the E. coli Hsp70, using physics-based molecular dynamics simulations to quantify the interactions between a variety of peptide substrates and key sites on DnaK. The resulting model, which we call Paladin, provides a physical basis to understand how DnaK binds to specific peptides. Given a sequence, Paladin can predict the precise residues that bind at a specific site on DnaK and can further explain challenging features like the binding orientation, which are typically not predicted by sequence-only models. The Paladin model could be used to design ‘super-binder’ therapeutic peptides to inhibit chaperones like DnaK in E. coli.
format	article
author	Erik B. Nordquist Charles A. English Eugenia M. Clerico Woody Sherman Lila M. Gierasch Jianhan Chen
author_facet	Erik B. Nordquist Charles A. English Eugenia M. Clerico Woody Sherman Lila M. Gierasch Jianhan Chen
author_sort	Erik B. Nordquist
title	Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones
title_short	Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones
title_full	Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones
title_fullStr	Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones
title_full_unstemmed	Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones
title_sort	physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by hsp70 chaperones
publisher	Public Library of Science (PLoS)
publishDate	2021
url	https://doaj.org/article/ad3b0c700af84c299fcbf138aa4bb030
work_keys_str_mv	AT erikbnordquist physicsbasedmodelingprovidespredictiveunderstandingofselectivelypromiscuoussubstratebindingbyhsp70chaperones AT charlesaenglish physicsbasedmodelingprovidespredictiveunderstandingofselectivelypromiscuoussubstratebindingbyhsp70chaperones AT eugeniamclerico physicsbasedmodelingprovidespredictiveunderstandingofselectivelypromiscuoussubstratebindingbyhsp70chaperones AT woodysherman physicsbasedmodelingprovidespredictiveunderstandingofselectivelypromiscuoussubstratebindingbyhsp70chaperones AT lilamgierasch physicsbasedmodelingprovidespredictiveunderstandingofselectivelypromiscuoussubstratebindingbyhsp70chaperones AT jianhanchen physicsbasedmodelingprovidespredictiveunderstandingofselectivelypromiscuoussubstratebindingbyhsp70chaperones
_version_	1718414536230305792

Physics-based modeling provides predictive understanding of selectively promiscuous substrate binding by Hsp70 chaperones

Ejemplares similares