Published December 14, 2023 | Version v1
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Elucidating molecular mechanisms of protoxin-2 state-specific binding to the human NaV1.7 channel

Description

Human voltage-gated sodium (hNaV) channels are responsible for initiating and propagating action potentials in excitable cells and mutations have been associated with numerous cardiac and neurological disorders. hNaV1.7 channels are expressed in peripheral neurons and are promising targets for pain therapy. The tarantula venom peptide protoxin-2 (PTx2) has high selectivity for hNaV1.7 and is a valuable scaffold for designing novel therapeutics to treat pain. Here, we used computational modeling to study the molecular mechanisms of the state-dependent binding of PTx2 to hNaV1.7 voltage-sensing domains (VSDs). Using Rosetta structural modeling methods, we constructed atomistic models of the hNaV1.7 VSD II and IV in the activated and deactivated states with docked PTx2. We then performed microsecond-long all-atom molecular dynamics (MD) simulations of the systems in hydrated lipid bilayers. Our simulations revealed that PTx2 binds most favorably to the deactivated VSD II and activated VSD IV. These state-specific interactions are mediated primarily by PTx2's residues R22, K26, K27, K28, and W30 with VSD and the surrounding membrane lipids. Our work revealed important protein-protein and protein-lipid contacts that contribute to high-affinity state-dependent toxin interaction with the channel. The workflow presented will prove useful for designing novel peptides with improved selectivity and potency for more effective and safe treatment of pain.

Notes

Funding provided by: National Institutes of Health
Crossref Funder Registry ID: https://ror.org/01cwqze88
Award Number: OT2OD026580

Methods

Structures were generated using the Rosetta structural modeling software suite(Rohl et al., 2004) based on experimental cryo-EM structures. All-atom molecular dynamics (MD) simulations were performed using the Amber20 software package (Salomon-Ferrer et al., 2013) and the standard all-atom Chemistry at Harvard Macromolecular Mechanics (CHARMM) force fields for proteins (CHARMM36m), lipids (C36), and ions(Huang and MacKerell Jr, 2013; Klauda et al., 2010; Best et al., 2012) as well as the TIP3P water model.  Afterward, protein-ligand interactions were characterized in each set of simulations using in-house Python scripts incorporating the protein–ligand interaction profiler (PLIP) Python module.(Salentin et al., 2015) Binding free energy calculations were performed using the Molecular Mechanics Poisson-Boltzmann Surface Area (MM/PBSA) approach(Srinivasan et al., 1998; Kollman et al., 2000; Wang et al., 2016a) with all-atom MD simulation trajectories by MMPBSA.py program in Amber Tools(Miller et al., 2012). To calculate the energy contribution of each residue to the binding process for each system, we computed the electrostatic and van der Waals interaction energies of PTx2 with POPC lipids and VSD II/IV using AMBER linear interaction energy analysis.(Salomon-Ferrer et al., 2013; Roe and Cheatham, 2013)

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Additional details

Related works

Is cited by
10.1085/jgp.202313368 (DOI)
Is derived from
10.5061/dryad.jq2bvq8gj (DOI)