Dynamics of activation in the voltage-sensing domain of Ci-VSP

Abstract

TheCiona intestinalisvoltage-sensing phosphatase (Ci-VSP) is a membrane protein containing a voltage-sensing domain (VSD) that is homologous to VSDs from voltage-activated ion channels responsible for cellular excitability. Two crystal structures of Ci-VSD in putative resting and active conformations suggest a stepwise voltage-sensing mechanism involving translocation and rotation of the S4 helix. Relying on a theoretical framework based upon dynamical operators, we use mechanistic statistics estimated from an ensemble of unbiased molecular dynamics trajectories to elucidate the molecular determinants of the resting-active transition. Sparse regression with a small set of coordinates reveals that activation is primarily governed by the movement of arginine side chains through a central hydrophobic constriction, independent of global S4 movements. While translocation and rotation do provide a meaningful representation of the overall motion of the S4 helix, the analysis indicates that the activation mechanism cannot be accurately described without incorporating more fine-grained details such as the sequential exchange of salt bridges between arginines along S4 and negative countercharges along the S1--S3 helices. The importance of these salt bridges has been previously suggested by structural and functional studies. These results highlight how molecular dynamics simulations can now quantitatively characterize complex and functionally important conformational changes of proteins.

Temperature-Dependent Fold-Switching Mechanism of the Circadian Clock Protein KaiB

“…Despite Upside’s speed, prohibitively long times are required to observe fold switching in unbiased MD simulations. However, we can obtain statistical information about fold-switching pathways through an approach called the dynamical Galerkin approximation (DGA) (27, 28, 75, 76). In this approach, relatively short unbiased simulations are used to sample portions of the fold-switching pathways, and these data are then used to estimate averages that determine the coefficients of basis expansions of functions of the dynamics, subject to a Markov assumption.…”