Simulations reveal molecular mechanisms of high affinity and selective binding of the tarantula venom protoxin-2 to the human NaV1.7 channel.

Abstract

Human voltage-gated sodium channels (hNaV) are responsible for initiating and propagating action potentials in excitable cells and have been associated with numerous cardiac and neurological disorders. hNaV1.7 channels, present at the endings of pain-sensing nerves, have garnered a lot of scientific interest as potential targets for pain therapeutics by channel inhibition. Certain natural peptide toxins, such as the tarantula protoxin-2 (ProTx2), have high selectivity for hNaV1.7, and hence they serve as valuable scaffolds for peptide design in pain therapeutics. Here, we present the mechanisms by which ProTx2 can bind and modulate hNaV1.7 channel gating kinetics. Using Rosetta biomolecular modeling software, we constructed atomistic structural models of the hNaV1.7 Voltage-Sensing Domain (VSD) 2 and 4 in the activated and deactivated states. Then, we docked ProTx2 onto the VSDs, embedded the structures into lipid bilayers solvated by aqueous NaCl solution, and performed microsecond-long all-atom molecular dynamics (MD) simulations of those systems using the CHARMM36m force field and Amber PMEMD software. Afterward, we performed binding energetics analysis using molecular mechanics Poisson-Boltzmann surface area (MM/PBSA) calculations and conducted Brownian Dynamics simulations using BrownDye to calculate the second-order association rate constants. Our analysis revealed numerous important inter-residue contacts that contribute to the toxin's high affinity for the channel. By understanding the various state- and subtype-specific mechanisms of toxin binding to the channel, we can develop strategies to improve the selectivity and potency of peptide toxins to create effective and safe pain therapeutics. In addition, the results could be incorporated into functional kinetic models to elucidate how ProTx2 can modulate electrical signal propagation in dorsal root ganglion neurons and thus pain sensing.