Efficient conversion of chemical energy into mechanical work by Hsp70 chaperones
Abstract
Hsp70 molecular chaperones are abundant ATP-dependent nanomachines that actively reshape non-native, misfolded proteins and assist a wide variety of essential cellular processes. Here we combine complementary theoretical approaches to elucidate the structural and thermodynamic details of the chaperone-induced expansion of a substrate protein, with a particular emphasis on the critical role played by ATP hydrolysis. We first determine the conformational free-energy cost of the substrate expansion due to the binding of multiple chaperones using coarse-grained molecular simulations. We then exploit this result to implement a non-equilibrium rate model which estimates the degree of expansion as a function of the free energy provided by ATP hydrolysis. Our results are in quantitative agreement with recent single-molecule FRET experiments and highlight the stark non-equilibrium nature of the process, showing that Hsp70s are optimized to effectively convert chemical energy into mechanical work close to physiological conditions.
Data availability
All the source data used for generating relevant figures (Fig1,2,2Supp1,4,5,6,1App) have been provided as supporting files.All the information necessary for reproducing the molecular simulations have been deposited in github (https://github.com/saassenza/Hsp70Unfoldase) and PLUMED NEST (plumID:19.076) repositories.
Article and author information
Author details
Funding
Agence Nationale de la Recherche (ANR-14-ACHN-0016)
- Alessandro Barducci
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung (200020_163042)
- Paolo De Los Rios
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Copyright
© 2019, Assenza et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Metrics
-
- 2,265
- views
-
- 325
- downloads
-
- 26
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.