Transient exposure of a buried phosphorylation site in an autoinhibited protein
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Autoinhibition is a mechanism used to regulate protein function, often by making functional sites inaccessible through the interaction with a cis-acting inhibitory domain. Such autoinhibitory domains often display a substantial degree of structural disorder when unbound, and only become structured in the inhibited state. These conformational dynamics make it difficult to study the structural origin of regulation, including effects of regulatory post-translational modifications. Here, we study the autoinhibition of the Dbl Homology domain in the protein Vav1 by the so-called acidic inhibitory domain. We use molecular simulations to study the process by which a mostly unstructured inhibitory domain folds upon binding and how transient exposure of a key buried tyrosine residue makes it accessible for phosphorylation. We show that the inhibitory domain, which forms a helix in the bound and inhibited stated, samples helical structures already before binding and that binding occurs via a molten-globule-like intermediate state. Together, our results shed light on key interactions that enable the inhibitory domain to sample a finely tuned equilibrium between an inhibited and a kinase-accessible state.
| Originalsprog | Engelsk |
|---|---|
| Tidsskrift | Biophysical Journal |
| Vol/bind | 121 |
| Udgave nummer | 1 |
| Sider (fra-til) | 91-101 |
| Antal sider | 11 |
| ISSN | 0006-3495 |
| DOI | |
| Status | Udgivet - 2022 |
Bibliografisk note
Funding Information:
We acknowledge support from the NordForsk Nordic Neutron Science Programme (grant number 81912 ), the Lundbeck Foundation BRAINSTRUC structural biology initiative ( R155-2015-2666 ), and Independent Research Fund Denmark (grant number 6108-00471 ). We also acknowledge access to computational resources from the ROBUST Resource for Biomolecular Simulations (supported by the Novo Nordisk Foundation grant no. NF18OC0032608 ), the Danish National Supercomputer for Life Sciences (Computerome) and the Biocomputing Core Facility at the Department of Biology, University of Copenhagen .
Funding Information:
We acknowledge work by Fabio Doro who contributed to the early stages and simulations in this project, and to Micha B. A. Kunze and Elena Papaleo for fruitful discussions. We are grateful to Francesco Pesce for inspiring discussions and for providing his scripts to perform block error analysis. We acknowledge support from the NordForsk Nordic Neutron Science Programme (grant number 81912), the Lundbeck Foundation BRAINSTRUC structural biology initiative (R155-2015-2666), and Independent Research Fund Denmark (grant number 6108-00471). We also acknowledge access to computational resources from the ROBUST Resource for Biomolecular Simulations (supported by the Novo Nordisk Foundation grant no. NF18OC0032608), the Danish National Supercomputer for Life Sciences (Computerome) and the Biocomputing Core Facility at the Department of Biology, University of Copenhagen.
Publisher Copyright:
© 2021 Biophysical Society
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