The metal cofactor zinc and interacting membranes modulate SOD1 conformation-aggregation landscape in an in vitro ALS Model
- CSIR-Indian Institute of Chemical Biology, India
- Harvard University, United States
- Jadavpur University, India
- National Institute of Science Education and Research (NISER), India
- Indian Institute of Technology Madras, India
Abstract
Aggregation of Cu-Zn superoxide dismutase (SOD1) is implicated in the motor neuron disease, ALS. Although more than 140 disease mutations of SOD1 are available, their stability or aggregation behaviors in membrane environment are not correlated with disease pathophysiology. Here, we use multiple mutational variants of SOD1 to show that the absence of Zn, and not Cu, significantly impacts membrane attachment of SOD1 through two loop regions facilitating aggregation driven by lipid induced conformational changes. These loop regions influence both the primary (through Cu intake) and the gain of function (through aggregation) of SOD1 presumably through a shared conformational landscape. Combining experimental and theoretical frameworks using representative ALS disease mutants, we develop a 'co-factor derived membrane association model' wherein mutational stress closer to the Zn (but not to the Cu) pocket is responsible for membrane association mediated toxic aggregation and survival time scale after ALS diagnosis.
Data availability
All data generated or analyzed during this study are included in the manuscript and supporting files
Article and author information
Author details
Krishnananda Chattopadhyay
Funding
University Grants Commission (Fellowship)
- Achinta Sannigrahi
University Grants Commission (Fellowship)
- Sourav Chowdhury
Department of Biotechnology, Ministry of Science and Technology, India (BT/PR8475/BRB/10/1248/2013)
- Sanat Karmakar
Science and Engineering Research Board (EMR/2016/000310)
- Krishnananda Chattopadhyay
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
Reviewing Editor
- Hannes Neuweiler, University of Würzburg, Germany
Publication history
- Received: July 25, 2020
- Accepted: April 1, 2021
- Accepted Manuscript published: April 7, 2021 (version 1)
- Version of Record published: April 30, 2021 (version 2)
Copyright
© 2021, Sannigrahi 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.
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The metal cofactor zinc and interacting membranes modulate SOD1 conformation-aggregation landscape in an in vitro ALS Model
eLife 10:e61453.
https://doi.org/10.7554/eLife.61453
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The design of compounds that can discriminate between closely related target proteins remains a central challenge in drug discovery. Specific therapeutics targeting the highly conserved myosin motor family are urgently needed as mutations in at least 6 of its members cause numerous diseases. Allosteric modulators, like the myosin-II inhibitor blebbistatin, are a promising means to achieve specificity. However, it remains unclear why blebbistatin inhibits myosin-II motors with different potencies given that it binds at a highly conserved pocket that is always closed in blebbistatin-free experimental structures. We hypothesized that the probability of pocket opening is an important determinant of the potency of compounds like blebbistatin. To test this hypothesis, we used Markov state models (MSMs) built from over 2 milliseconds of aggregate molecular dynamics simulations with explicit solvent. We find that blebbistatin’s binding pocket readily opens in simulations of blebbistatin-sensitive myosin isoforms. Comparing these conformational ensembles reveals that the probability of pocket opening correctly identifies which isoforms are most sensitive to blebbistatin inhibition and that docking against MSMs quantitatively predicts blebbistatin binding affinities (R2=0.82). In a blind prediction for an isoform (Myh7b) whose blebbistatin sensitivity was unknown, we find good agreement between predicted and measured IC50s (0.67 mM vs. 0.36 mM). Therefore, we expect this framework to be useful for the development of novel specific drugs across numerous protein targets.
