Published February 15, 2024 | Version v1
Journal article Open

Dynamics of activation in the voltage-sensing domain of Ciona intestinalis phosphatase Ci-VSP

  • 1. University of Chicago

Description

The Ciona intestinalis voltage-sensing phosphatase (Ci-VSP) is a membrane protein containing a voltage-sensing domain (VSD) that is homologous to VSDs from voltage-gated ion channels responsible for cellular excitability. Previously published crystal structures of Ci-VSD in putative resting and active conformations suggested a helical-screw voltage sensing mechanism in which the S4 helix translocates and rotates to enable exchange of salt-bridge partners, but the microscopic details of the transition between the resting and active conformations remained unknown. Here, by combining extensive molecular dynamics simulations with a recently developed computational framework based on dynamical operators, we elucidate the microscopic mechanism of the resting-active transition at physiological membrane potential. Sparse regression reveals a small set of coordinates that distinguish intermediates that are hidden from electrophysiological measurements. The intermediates arise from a noncanonical helical-screw mechanism in which translocation, rotation, and side-chain movement of the S4 helix are only loosely coupled. These results provide insights into existing experimental and computational findings on voltage sensing and suggest ways of further probing its mechanism.

Data availability

The PDB files for the down and up states of Ci-VSD were obtained from wwPDB under accession codes 4G80 and 4G7V, respectively. The trajectory data without lipid or water coordinates, together with simulation parameters and initial and final structures of trajectories have been deposited in Zenodo under accession code 10.5281/zenodo.7502083. The raw simulation data have not been deposited due to their size; access can be obtained by contacting the authors or the Pittsburgh Supercomputing Center (PSC). Source data (CVs and results of DGA calculations) are provided with this paper.

Molecular dynamics simulation data were generated using the Anton 2 machine (code not publicly available; resource handled through the PSC) and AMBER20 with PLUMED 2.7. Analysis was performed using MDAnalysis 2.4.2, MDTraj 1.9.7, PyEMMA 2.5.12, scikit-learn 1.2.1, VMD 1.9.4, and IVAC along with custom scripts written in Python/Jupyter notebooks and tcl. A package for computing kinetic statistics with DGA is available at https://github.com/dinner-group/dgamem. Custom code is available at https://github.com/dinner-group/ci-vsd.

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Additional details

Identifiers

DOI
10.1038/s41467-024-45514-6
Other
oai:uchicago.tind.io:11098

Funding

National Science Foundation
Graduate Research Fellowship
National Institutes of Health
R35 GM136381
NIGMS
R01 GM062342

UChicago Information

Division(s)
Physical Sciences Division
Department(s)
Biochemistry and Molecular Biology, Chemistry
Center(s) or Institute(s)
Institute for Biophysical Dynamics, James Franck Institute