The Structural Basis of IKs Ion-Channel Activation: Mechanistic Insights from Molecular Simulations

Abstract

Relating ion channel (iCh) structural dynamics to physiological function remains a challenge. Current experimental and computational techniques have limited ability to explore this relationship in atomistic detail over physiological timescales. A framework associating iCh structure to function is necessary for elucidating normal and disease mechanisms. We formulated a modeling schema that overcomes the limitations of current methods through applications of artificial intelligence machine learning. Using this approach, we studied molecular processes that underlie human IKs voltage-mediated gating. IKs malfunction underlies many debilitating and life-threatening diseases. Molecular components of IKs that underlie its electrophysiological function include KCNQ1 (a pore-forming tetramer) and KCNE1 (an auxiliary subunit). Simulations, using the IKs structure-function model, reproduced experimentally recorded saturation of gating-charge displacement at positive membrane voltages, two-step voltage sensor (VS) movement shown by fluorescence, iCh gating statistics, and current-voltage relationship. Mechanistic insights include the following: 1) pore energy profile determines iCh subconductance; 2) the entire protein structure, not limited to the pore, contributes to pore energy and channel subconductance; 3) interactions with KCNE1 result in two distinct VS movements, causing gating-charge saturation at positive membrane voltages and current activation delay; and 4) flexible coupling between VS and pore permits pore opening at lower VS positions, resulting in sequential gating. The new modeling approach is applicable to atomistic scale studies of other proteins on timescales of physiological function.

Effects of β-subunit on gating of a potassium ion channel: Molecular simulations of cardiac IKs activation

“…The fast stage of the VS movement that is not slowed by the S4S5L movement, covers a larger displacement compared to the slow stage. This result is consistent with the observation by Ramasubramanian and Rudy [28]. Direct experimental evaluation of the role of S4S5L movement during activation gating is difficult to obtain because of its cytosolic position on the channel protein.…”

“…Electrostatic interaction with the C-terminus of KCNE1 transmembrane helix favors extreme z positions for S4S5L in VS A , but does not affect the S4S5L in VS B significantly. Consequently, the two types of VSLs in IKs behave differently during channel activation, a behavior that was also observed in recent simulations using a different, independent approach [28]. This property could contribute to the multiple stages of IKs voltage dependent gating observed experimentally [24].…”

“…We applied this approach to the cardiac IKs channel and studied modulation by the β-subunit KCNE1 of its activation gating. A recent modeling paper introduced a different approach for simulating IKs gating at the atomic scale [28]. In that approach, artificial intelligence (machine learning) methods were used to overcome the computational enormity of the problem.…”

ML277 specifically enhances the fully activated open state of KCNQ1 by modulating VSD-pore coupling

“…The loss of ML277 effects on KCNQ1 +KCNE1 channels with saturating KCNE1 association was suggested to result from a competition between ML277 and KCNE1 in binding to KCNQ1 (Yu et al, 2013). ML277 may bind at the interface between the VSD and the pore from two neighboring subunits, where KCNE1 is also found to bind with KCNQ1 (Chan et al, 2012; Nakajo et al, 2010; Peng et al, 2017; Ramasubramanian and Rudy, 2018; Strutz-Seebohm et al, 2011; Xu and Rudy, 2018). As a result, KCNE1 binding may block ML277 binding and abrogate its effects.…”

Modeling the Interactions Between Sodium Channels Provides Insight Into the Negative Dominance of Certain Channel Mutations

“… Silva et al (2009) , for instance, have derived a Markovian model of the KCNQ1 channel (underlying the cardiac slow delayed rectifier K + current I Ks ) from energy landscapes related to the movement of the voltage sensor, and used their model to evaluate the consequences of channel mutations on the action potential. More recently, Ramasubramanian and Rudy (2018) used molecular dynamics simulations to compute the energies of about 3 million possible I Ks channel conformational states, building up an enormous multidimensional energy landscape. Channel gating was then simulated as a random walk through this landscape.…”