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. 2020 Apr 21;16(4):e1007405. doi: 10.1371/journal.pcbi.1007405

Structural and molecular insight into the pH-induced low-permeability of the voltage-gated potassium channel Kv1.2 through dewetting of the water cavity

Juhwan Lee 1,2,3, Mooseok Kang 1,4, Sangyeol Kim 1,5,*, Iksoo Chang 1,3,4,5,*
Editor: Peter M Kasson6
PMCID: PMC7173763  PMID: 32315300

Abstract

Understanding the gating mechanism of ion channel proteins is key to understanding the regulation of cell signaling through these channels. Channel opening and closing are regulated by diverse environmental factors that include temperature, electrical voltage across the channel, and proton concentration. Low permeability in voltage-gated potassium ion channels (Kv) is intimately correlated with the prolonged action potential duration observed in many acidosis diseases. The Kv channels consist of voltage-sensing domains (S1–S4 helices) and central pore domains (S5–S6 helices) that include a selectivity filter and water-filled cavity. The voltage-sensing domain is responsible for the voltage-gating of Kv channels. While the low permeability of Kv channels to potassium ion is highly correlated with the cellular proton concentration, it is unclear how an intracellular acidic condition drives their closure, which may indicate an additional pH-dependent gating mechanism of the Kv family. Here, we show that two residues E327 and H418 in the proximity of the water cavity of Kv1.2 play crucial roles as a pH switch. In addition, we present a structural and molecular concept of the pH-dependent gating of Kv1.2 in atomic detail, showing that the protonation of E327 and H418 disrupts the electrostatic balance around the S6 helices, which leads to a straightening transition in the shape of their axes and causes dewetting of the water-filled cavity and closure of the channel. Our work offers a conceptual advancement to the regulation of the pH-dependent gating of various voltage-gated ion channels and their related biological functions.

Author summary

The acid sensing ion channels are a biological machinery for maintaining the cell functional under the acidic or basic cellular environment. Understanding the pH-dependent gating mechanism of such channels provides the structural insight to design the molecular strategy in regulating the acidosis. Here, we studied the voltage-gated potassium ion channel Kv1.2 which senses not only the electrical voltage across the channels but also the cellular acidity. We uncovered that two key residues E327 and H418 in the pore domain of Kv1.2 channel play a role as pH-switch in that their protonation control the gating of the pore in Kv1.2 channel. It offered a molecular insight how the acidity reduces the ion permeability in voltage-gated potassium channels.

Introduction

Electrical signals in neurons are generated by sequential gating of several voltage-gated ion channels on their cell membranes. The opening and closing of these channels are not only sensitively controlled by membrane potentials in general, but also respond to the intra- and extracellular conditions, such as chemicals [1, 2], mechanical pressure [3], temperature [4], and proton concentrations [5]. Among these channels, the voltage-gated potassium channels (Kv) are selectively permeable to potassium ions and repolarize the membrane potential in response to depolarizing voltage [6]. The molecular mechanisms underlying this potassium ion-selectivity and voltage-dependent gating of the Kv channels have been extensively studied [7–11]. However, the molecular mechanism of pH-dependent gating in Kv channels is less well-understood, although it has been revealed that the potassium ion permeability is inhibited by the high proton concentration in acidosis [12]. The low permeability in the Kv channels is intimately correlated with the prolonged action potential duration observed in acidosis diseases such as cardiac arrhythmias.

These Kv channels have a tetrameric structure composed of four homo-subunits surrounding an ion-transporting pore, with each subunit containing six membrane-spanning α-helices called S1–S6. They are spatially separated from a voltage-sensing domain-containing S1–S4 and a central pore domain-containing S5–S6 that includes a P-helix (Fig 1A). These two domains are connected by an S4–S5 helical linker [13]. The pore domain contains a potassium ion-selective pathway and gates spanning the cell membrane. The narrowest part (extracellular side) on the pore in the channels is the “selectivity filter”, whereas the opposite part (intracellular side) of the filter on the pore is the “water-filled cavity” (Fig 1B). The gating of the Kv channels is structurally determined by whether the water-filled cavity is wetted or dewetted.

Fig 1. Schematic illustration of the Kv channel structure.

Fig 1

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(A) A cartoon model of a subunit of the Kv channel showing the voltage-sensing domains (VSDs) (S1–S4) in yellow, the S4–S5 helical linker in green, the S5 helix in cyan, the P-helix in pink, and the S6 helix in blue. (B) Two opposite subunits of the pore domain of the Kv channel are represented by ribbons. The other two subunits have been omitted. The selectivity filter is shown in purple, and the water cavity is located below the water cavity. The hinge region in S6 helix is highlighted in red.

In Kv1.2 channels, as in the other members of the non-inactivating ion channel family, ionic currents flow in response to the applied depolarized voltage and are maintained until the end of depolarization. Kv1.2 channels maintain the closed conformation at polarized (resting) potentials or the open conformation at depolarized potentials. A permeability of ion channels is defined by the ionic currents per surface area. The appearance of ionic currents is induced by the opening transformation of the channels with wetting water cavity. On the other hand, the disappearance of ionic currents is accompanied by the closing transformation of the channels with dewetting cavity [7]. Previous experimental work at depolarized voltage showed that the permeability of Kv1.2 channels to potassium ions gradually decreases as the pH changes from 7.5 to 4.5 (midpoint at around 5.3), whereas pH-independent zero permeability appeared at resting voltage [12]. This implies that the protonation of some titratable residues make the channels resist the transition from closed to open conformations against depolarized voltage.

Here, we report our observations from an all-atom molecular dynamics (MD) simulation. We found that the voltage-gated Kv1.2 ion channel has dual-functionality due to protonation of the conserved residues E327 and H418 situated near the water cavity on the intracellular side because it induces the gating transition of the pore domain from an open to closed position under acidic conditions. We characterized the structural role of the two determinant residues E327 and H418 in the gating of Kv1.2 channels, which can be protonated under a reasonable acidic condition, as demonstrated in the previous experimental study [12]. We suggest the molecular and structural mechanism underlying the acid-induced low permeability of Kv1.2 channels by uncovering the mechanism under acidic conditions.

Results

Identification of the key acid-responding residues in Kv1.2

To identify the key residues that might be protonated under acidic pH and resting voltage conditions, that is, from pH 7.5 to around pH 5.3, we attempted to estimate the pKa values of the titratable residues in Kv1.2 channels with closed conformations. The Kv1.2 channel is inactivated with zero permeability in the resting voltage [12]. Thus, physiologically the default state of the Kv1.2 channel is an inactivated state with the pore closure. Nevertheless, the unprotonated wild-type (named WildUnP) conformation provided by PDB 2R9R [14] was in the open conformation. Therefore, we needed to generate the closed structure of Kv1.2 channel from the opened structure either by applying the resting voltage (about -60mV) or the acidic pH to an initial opened structure. We, however, noted that our MD simulation was done only with the pore domain of the channel while the voltage sensing domain (VSD) of the channel is necessary to induce such conformational change subject to the application of the resting voltage. In our setting of MD simulation, we therefore applied the strong acidic condition (namely protonating E327/H418/E420) to an initial opened structure in order to obtain the closed state in the physiological condition for Kv1.2 pore domain. Here, we considered the pore domains (residue numbers: 312–421) that are responsible for the gating of the Kv1.2 channel, excluding the voltage-sensing domains. Based on the representative structural ensembles of the closed conformations in forth trajectory (S5E Fig), the pKa values of the titratable residues in the channel were estimated (Fig 2A) [15]. The pKa values of both E327 in the A- and D-chain and H418 were around 6.0, which means that these two residues can be protonated under the above acidic conditions. Here, pKa of E327 residues were seemed to reside in the 2-fold symmetry whereas pKa of H418 residues remained in the 4-fold symmetry. The closed conformations of the channel, considered for our pKa estimations, were shown to maintain 2-fold symmetry near the water cavity, while the other parts of the channel were remained in 4-fold symmetry (Upper panels of Fig 3A). Presumably, the pKa of E327 residues sensitively reacted to the structural change near the water cavity with 2-fold symmetry rather the pKa of H418 residues. Multiple sequence alignment for Kv1 subfamily proteins showed that almost residues are conserved (Fig 2B). Among these conserved residues two residues E327 and H418 are located near the water-filled cavity, and many charged amino acids are distributed around E327 and H418. Since the protonation of E327 and H418 residues could affect the conformational transition of the pore domain of the Kv1.2 channel, we decided to investigate the effect of protonation of the E327 and H418.

Fig 2. pKa estimates of H418 and acidic residues and two key residues in the Kv1.2 channel.

Fig 2

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(A) The pKa estimates of H418 and the acidic residues in the pore domain of the closed Kv1.2 channels. (B) Multiple sequence alignment for the pore domains of the rat Kv1 subfamily. The cylinders above the sequences denote the secondary structural information of the four helical segments. The two key conserved residues E327 and H418 are highlighted in yellow and bold font. (C) Bottom and side views of the close pore domain of the Kv1.2 channel. The four subunits are represented by different colors in the ribbon diagram. The magnified view shows the key residues E327 and H418 and their neighbors in the inner helical bundle, which are represented by the licorice and Cα balls.

Fig 3. Pore closure due to protonation of the two key residues E327 and H418 in the Kv1.2 channel.

Fig 3

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(A) The structures of the open and closed Kv1.2 channel. Here, the ribbons represent the pore domain of Kv1.2 channels, the blue spheres denote water molecules, and the gray spheres denote potassium ions. The upper panel illustrates the bottom view of the open and closed conformations. The lower panel shows the wetted and dewetted water cavity in the channel. Both the two opposite subunits and lipid molecules have been omitted from the lower panel. (B) The time evolution of the number of water molecules in the water cavity of the WildUnP or Ep327/Hp418 states of the Kv1.2 channel. The five individual plots in each state represent the simulation results from each trajectory of our MD simulations. In addition, the red horizontal line separates the wetted state from the dewetted state of the water cavity. (C) The distributions of the number of water molecules in the water cavity. The left region with fewer water molecules corresponds to the dewetting condition, whereas the right region with many water molecules corresponds to the wetting condition.

Protonation of E327 and H418 induces closure of Kv1.2

We performed atomistic MD simulations of the central pore domain in the Kv1.2 channel for both a Ep327/Hp418 state (here, “p” indicates the protonation; details of our MD simulations are provided in the Supplementary Information) and WildUnP (as a control group). Starting from the initial open conformation of the central pore domain in the Kv1.2 channel, five trajectories of MD simulations for each of a WildUnP and a Ep327/Hp418 state were run for 2 μs, and the conformational ensembles of the central pore domain in the Kv1.2 channel were sampled (Fig 3A) [16]. The number of water molecules in the cavity implicates that the closed conformations were sampled in Ep327/Hp418 (Fig 3B and S3 Fig), but not in WilldUnP [17]. This result demonstrates that the protonation of E327 and H418 destabilizes the charge interaction network of R326, E327, and H418 under acidic condition. As a result, it induces conformational change from open to close form (Fig 3B and 3C).

Structural and molecular mechanisms of the pore closure of Kv1.2

Based on the structural ensembles collected from our MD simulations, we quantified the structural alterations between the open and close form of Kv1.2 channels. The PVP (P405-V406-P407) motif which is located in the middle of H6 (Fig 1B) is flexible and acts as a hinge [17, 18]. This flexible hinge allows the change of kinked angle during channel gating. We studied how inter-subunit interaction (R326, E327, and H418) affect the channel gating (Fig 4A). We used two structural determinants that can distinguish the open conformation from the closed conformation of the pore in Kv1.2 channels, namely, the R326–H418 inter-subunit distance defined by the nearest inter-atom distances in these two residues (the bottom view in Fig 4A) and the dihedral angle extended by the positions of the Cα atoms in four residues (L393, L400, V408, and Y415) on the S6 helix (yellow ball of the side view in Fig 4A) as a measure of the kinked angle of S6. The dihedral angle determines whether the S6 helix is bent or straight [18].

Fig 4. Straightening of the S6 helix due to protonation of the two key residues E327 and H418 in the Kv1.2 channel.

Fig 4

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(A) The detailed structures of the open (left panels) and closed (right panels) Kv1.2 channels. The upper panel illustrates the distance between the R326 and H418 residues. For the open conformation of the pore, the distance between E327 and H418 is 7.6 Å, whereas it is 14.7 Å for the closed conformation. In addition, the lower panel shows the S6 helix when it is bent (black dotted line) or straight (solid red line). Here, two neighbor subunits are displayed using purple and cyan color, respectively, while the other subunits have been omitted. (B) The probability distribution curves for the inter-subunit distances between the R326 and H418 residues of the WildUnP and Ep327/Hp418 states. (C) The probability distribution of the dihedral angles, extended by the position of the Cα atoms in L393, L400, V408, and Y415, for each state. The left half region with the angle smaller than 180° corresponds to the bent S6 helix, whereas the right half and the secondary peak is the straight S6 helix. (D) Ensembles population of log scale for the R326–H418 distances and the dihedral angles. In the right panel for the Ep327/Hp418 state, a high correlation value of 0.84 was detected. (E) Ensembles population of log scale for the dihedral angles and the number of water molecules in the water-filled cavity. In the right panel for the Ep327/Hp418 state, a high correlation value of 0.77 was also detected.

The Supplementary Information in S1C, S1D, S3C and S3D Figs shows the time evolution of the values of the R326–H418 inter-subunit distance and the dihedral angle from the structural ensembles collected in the last 500 ns time window of our MD simulations, which demonstrates the effects of the protonation of E327 and H418. The R326–H418 distances in the Ep327/Hp418 state of the Kv1.2 channels become longer and the distance distribution is much broader compared with those of the WildUnP, for which the most frequent distances are around 6 Å (Fig 4B). The drastic increase in the R326–H418 distances in the Ep327/Hp418 state is due to the repulsive Coulomb interaction between R326 and Hp418. The distribution of the dihedral angles extended by L393, L400, V408, and Y415 on the S6 helix of the WildUnP Kv1.2 channels has a distinct peak at around 130°, indicating that the S6 helix is bent (the dotted black line in Fig 4C). On the other hand, the protonation of both E327 and H418 gives rise to a secondary peak around 245° in their distribution, indicating that the S6 helix is straightened (the solid red line in Fig 4C). The increase in the R326–H418 distance is closely correlated with the increase in the dihedral angle extended by L393, L400, V408, and Y415 on the S6 helix and is well captured by the heat map of the ensemble population along the two axes of each quantity (Fig 4D). The heat map in the Ep327/Hp418 state revealed that the increase in the R326–H418 inter-subunit distance straightened the S6 helix. The change in the degree of the dewetting in the cavity of the Kv1.2 channels is also closely correlated with the straightening of the S6 helix. This close correlation is demonstrated in the heat map of the ensemble population along the two axes of the dihedral angle and in the number of water molecules in the cavity (Fig 4E).

Overall, Hp418 was electrostatically pushed by R326 at the end of the S6 helix under acidic conditions. This changed the shape of the S6 helix from bent to straight. Therefore, the straightening of the S6 helix is a robust indication of pore closure in the potassium channel Kv1.2 [19–21]. Here, we suggest that the repulsive Coulomb interaction of the inter-subunits triggered by the protonation of the two key residues E327 and H418 is the molecular mechanism of the pore closure in the Kv1.2 channels, together with both the increase in the inter-subunit distance and the straightening of the S6 helix.

Altering the conformation of Kv1.2 through protonation or mutation

The conformation of the Kv1.2 channel was further probed by examining the changes in the inter-subunit interactions among R326, E327, and H418 and the intra-subunit interaction between K312 and E420. We were able to modify the charge states of these residues through protonation or mutation. First, we modified the inter-subunit interaction by changing the charge state of H418 to Hp418 (S2 Fig) or H418R (S6 Fig) which resembled the weak acidic condition. Second, we broke the inter-subunit interactions by changing to Ep327/Hp418 (S3 Fig) or E327A/H418R (S7 Fig) which resembled the strong acidic condition. Third, we modified the intra-subunit interaction by changing the charge state of E420 to Ep420 (S4 Fig) or E420A (S8 Fig). The protonation or mutation of E420 weakens the charge interaction between E420 and K312. It destabilized the open conformation of the Kv1.2 channel and induced conformational change from open to closed. Additionally, these effect on K312, which located in the S4-S5 linker, could propagate to the VSD throughout the S4 helix. Finally, we broke both the inter- and intra-subunit interactions by changing to Ep327/Hp418/Ep420 (S5 Fig) or E327A/H418R/E420A (S9 Fig) which resembled stronger acidic condition.

Our MD simulations for these 8 variants showed the structural transition from the open to the closed conformation in the pore of the Kv1.2 channel for at least 1 out of 5 trajectories (S2E to S9E Figs). The closed conformations of the variants commonly showed both an increase in the inter-subunit distance (S2C to S9C Figs) and a straightening of the S6 helix (S2D to S9D Figs), as like as the molecular mechanism of the pore closure of Ep327/Hp418 state. Of the variants, the correlation values between the R326-H418 distance and the dihedral angles range from 0.64 to 0.89 (S2A to S9A Figs), and the correlation values between the number of cavity water and the dihedral angles range from 0.49 to 0.78 (S2B to S9B Figs). We were thus able to control the pore closure of Kv1.2 through the various protonation or mutation, which corroborated the molecular mechanism regarding the effect of charge-charge interactions on the structure and gating of the pore domain of Kv1.2 channel.

Discussion

We investigated the molecular mechanism underlying the pH-dependent gating of the pore domain of the Kv1.2 channel protein under intracellular acidic conditions. A decrease in environmental pH from 6 to 5 with depolarized voltage causes Kv1.2 to undergo a conformational change from open to closed [12]. Our pKa estimates indicate that only two amino acids E327 and H418 change their charge states in response to a change in the environmental pH. Thus, E327 and H418 are proposed as key residues for pH sensing. To assess the role of the key residues under acidic pH conditions, we performed MD simulations with key protonated residues. Ep327 and Hp418 highly destabilize the electrostatic interaction. Inter- and intra-subunit interactions, which consists of K312, R326, E327, H418, and E420, were critically destabilized by the change in the charge states of these titratable residues. Because the net charge of this cluster changes from zero to positive (+1, +2, or +3), the intra-subunit interaction K312-Ep420 weakens and the repulsive force between R326 and Hp418 increases the distance. This repulsive force pushes the end of S6, leading to its distortion. In our simulation, the channels are perfectly closed when the two opposite subunits of S6 undergo a conformational change. Two distorted S6 helices move close together and fill the space previously occupied by the water. As a result, the closed conformation of Kv1.2 under acidic conditions was induced by the protonated E327 and H418. We tracked the step-by-step conformational change using MD simulation. H418R and E327A/H418R mutants undergo a structural change from an open to closed conformation. Thus, we were able to modulate the conformation of Kv1.2 via in silico mutation of the key residues. It imply that H418R and E327A/H418R mutants have low ion permeability, even under the neutral pH condition. With various protonated or mutated MD simulations, we found that the charge interaction of inter- and intra-subunit affects the channel gating. However, because of the sampling issues, we are not sure about a quantitative comparison that which interactions are more important. Therefore, additional in-vivo or in-vitro experiments are needed for the quantitative comparison.

The molecular mechanism of the voltage-dependent gating of the Kv channels involves displacement of the VSD that regulate the wetting or dewetting of the cavity [7]. The previous study shows that the S4 helix is the main moving part in the VSD which moved down ~15Å across the membrane during the deactivation, and the motion of S4 affects the pore domain through the S4-S5 linker [7]. In our simulation, the intra-subunit interaction between K312 and E420 is affected by the protonation state of E420, so the K312 (locate at the S4-S5 linker) could restrict the motion of S4 depending on the environmental pH condition. As a result, S4-S5 linker is affected by environmental pH. Since we simulated with the pore domain (residues 312–421, without VSDs) of Kv1.2, it does not fully reflect the realistic motion of a full chain of Kv1.2 with VSDs. However, it would be used to understand the effect of the acidic environment on channel gating of the pore domain. The coexistence of these voltage- and acid-dependent gating mechanisms in Kv1.2 channels implies that both the voltage-induced structural pressure and acid-induced structural pressure can simultaneously influence the gating of the channels. The possibility for this simultaneous action of two different mechanisms of pore gating was indicated in previous experimental studies of the behavior of the potassium ion current of Kv1.2 channels that suggested that the acidity competes with the depolarizing voltage [12]. At a glance, this might be counterintuitive because the neuronal channels were not able to distinguish the environmental factor that played a role in their own gating. However, it is worth noting that the time scale for the fluctuation in the membrane potential is on the order of milliseconds, whereas that of the cellular pH is from seconds to minutes. Thus, the permeability of potassium ion currents through Kv1.2 channels is not only finely controlled by the depolarizing voltage in the short time interval but also governed by the acidity in the long time interval. Our study offers insight into the dual-gating mechanisms of the Kv channels, which orchestrate both the voltage-dependent and pH-dependent gating mechanisms of different molecular mechanisms.

Methods

All-atom molecular dynamics simulation

We performed MD simulations using GROMACS 5.0 [22] with the CHARMM36 force field [23]. The initial configurations of the Kv1.2 channel for the MD simulation were generated using CHARMM-GUI lipid builder [24]. The system consists of a channel protein, lipids (271 POPE in upper and lower leaflets), water molecules (~10,000 TIP3P water molecules). In order to conduct the simulation under the same ionic conditions in the previous studies [7, 19], we added 0.6M of K+ and Cl- ions. The channel protein is a symmetric tetramer structure with an open-pore domain (residues 312–421) that is derived from the X-ray crystal structure of the Kv1.2 channel (PDB code: 2R9R) [14]. The system includes ~71,000 atoms in a rectangular box (100 × 100 × 75 Å) under the periodic boundary condition. The particle-mesh Ewald (PME) method [25] was applied for assessing long-range electrostatic interactions with a 12 Å cut-off distance, and potential-based switching functions were used for van der Waals interactions with a 10–12 Å switching range. The position of the hydrogen atoms was restrained by the equilibrium bond length using the LINCS algorithm [26]. Approximately 5,000 steps of steepest-descent minimization were conducted. We performed the heating process by gradually removing the restraint on lipids and protein over 20,000 steps for the stable 310K system temperature. An additional 30 ns simulation with a restrained protein backbone was performed to equilibrate the water cavity position, followed by a production run. The production simulations were carried out for 2 μs with a 2 fs time step in NPT ensemble holding a constant particle number (N = ~71,000), pressure (P = 1 bar), and temperature (T = 310 K). Temperature was controlled by the Nosé–Hoover temperature coupling method [27, 28] with a tau-t of 1 ps and pressure was maintained by the semi-isotropic Parrinello–Rahman method [29, 30] with a tau-p of 5 ps and compressibility of 4.5 × 10−5 bar−1. All trajectories were recorded every 10 ps, and VMD software [31] was used for the visual analysis.

pKa calculation

For pKa estimates of H418 and the acidic residues in the pore domain of the closed Kv1.2 channels, several processes were executed. 1) We extracted 98 ensemble structures of the Kv1.2 channels with pore closure in the last 1 μs time window from our MD simulation for an Ep327/Hp418/Ep420 state. In our setting of MD simulation the pore domain of Kv1.2 channel together with explicit membrane lipids, water molecules, and ions were included. 2) In order to select preferred titration states among all possible titration states in the pH range from 3 to 8, we took advantage of MEAD algorithms [15] to the 10 out of 98 pore closure ensembles with these options (dielectric constants of a molecular interior region / solvent region were εin = 6.0, εsol = 80.0, ionic strength was 0.15 mol/l, and the effect of membrane was excluded.). 3) We selected 765 titration states of the channels that were predominant in the pH range from 3 to 8. For the estimation of pKa values we utilized these 765 titration states and 10 pore closure structural ensembles from our MD simulation. 4) At each titration state on all 98 ensemble structures, we calculated the system energies in the implicit water using AMBER force field 99SB [32]. 5) From the titration states of 3) and the system energies of 4), we reconstructed the partition function, the protonation fractions and estimated pKa values of H418 and the acidic residues (Fig 2) [33]. Red circles in the figure represent the pKa values when the average energies (using AMBER force field 99SB) of ensemble structures, 〈E〉, were used to calculate the protonated fraction as a function of pH for the corresponding titration states. The blue crosses represent the pKa values when the statistical variance of the energies 〈E〉±0.1σ,〈E〉±0.2σ,…,〈E〉±1σ was considered to reflect the uncertainty of the pKa values due to the structural fluctuation of ensemble structures.

Supporting information

S1 Fig. Simulation results for WildUnP.

(A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for WildUnP.

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S2 Fig. Simulation results for Hp418.

(A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for Hp418.

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S3 Fig. Simulation results for Ep327/Hp418.

(A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for Ep327/Hp418.

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S4 Fig. Simulation results for Ep420.

(A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for Ep420.

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S5 Fig. Simulation results for Ep327/Hp418/Ep420.

(A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for Ep327/Hp418/Ep420.

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S6 Fig. Simulation results for H418R.

(A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for H418R.

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S7 Fig. Simulation results for E327A/H418R.

(A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for E327A/H418R.

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S8 Fig. Simulation results for E420A.

(A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for E420A.

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S9 Fig. Simulation results for E327A/H418R/E420A.

(A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for E327A/H418R/E420A.

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Acknowledgments

We acknowledge DGIST Supercomputing Bigdata Center for the allocation of dedicated supercomputing time. Protein structure images were made with VMD software support. VMD is developed with NIH support by the Theoretical and Computational Biophysics group at the Beckman Institute, University of Illinois at Urbana-Champaign.

Data Availability

Deposit files We performed MD simulations using GROMACS 5.0.6 that can be obtained from http://www.gromacs.org/Downloads_of_outdated_releases We provide all input files to run the MD simulations including input coordinates, topologies and parameter files and etc. Additionally, we provide all the trajectory files. Input files: http://wyu.dgist.ac.kr/kv12/input/ Trajectory files: http://wyu.dgist.ac.kr/kv12/traj/.

Funding Statement

This study was supported by the Creative Research Initiatives of the National Research Foundation (NRF) of Korea (grant number 2008-0061984, http://www.nrf.re.kr/eng/main). Received by Iksoo Chang. The DGIST Core Protein Resources Center funded by MOTIE, Korea (grant number N0001822, http://english.motie.go.kr). Received by Iksoo Chang. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

References

  • 1.Paulsen CE, Armache JP, Gao Y, Cheng Y, Julius D. Structure of the TRPA1 ion channel suggests regulatory mechanisms. Nature. 2015;520(7548):511–7. Epub 2015/04/10. 10.1038/nature14367 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 2.Baronas VA, Yang RY, Kurata HT. Extracellular redox sensitivity of Kv1.2 potassium channels. Sci Rep. 2017;7(1):9142 Epub 2017/08/24. 10.1038/s41598-017-08718-z [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 3.Clausen MV, Jarerattanachat V, Carpenter EP, Sansom MSP, Tucker SJ. Asymmetric mechanosensitivity in a eukaryotic ion channel. Proc Natl Acad Sci U S A. 2017;114(40):E8343–E51. Epub 2017/09/20. 10.1073/pnas.1708990114 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 4.Grandl J, Kim SE, Uzzell V, Bursulaya B, Petrus M, Bandell M, et al. Temperature-induced opening of TRPV1 ion channel is stabilized by the pore domain. Nat Neurosci. 2010;13(6):708–14. Epub 2010/04/24. 10.1038/nn.2552 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5.Hu H, Ataka K, Menny A, Fourati Z, Sauguet L, Corringer P-J, et al. Electrostatics, proton sensor, and networks governing the gating transition in GLIC, a proton-gated pentameric ion channel. Proceedings of the National Academy of Sciences. 2018;115(52):E12172–E81. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6.Misonou H, Trimmer JS. Determinants of voltage-gated potassium channel surface expression and localization in Mammalian neurons. Crit Rev Biochem Mol Biol. 2004;39(3):125–45. Epub 2004/12/15. 10.1080/10409230490475417 . [DOI] [PubMed] [Google Scholar]
  • 7.Jensen MØ, Jogini V, Borhani DW, Leffler AE, Dror RO, Shaw DE. Mechanism of voltage gating in potassium channels. Science. 2012;336(6078):229–33. 10.1126/science.1216533 [DOI] [PubMed] [Google Scholar]
  • 8.Kim DM, Nimigean CM. Voltage-Gated Potassium Channels: A Structural Examination of Selectivity and Gating. Cold Spring Harb Perspect Biol. 2016;8(5). Epub 2016/05/04. 10.1101/cshperspect.a029231 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 9.Li J, Ostmeyer J, Cuello LG, Perozo E, Roux B. Rapid constriction of the selectivity filter underlies C-type inactivation in the KcsA potassium channel. J Gen Physiol. 2018;150(10):1408–20. Epub 2018/08/04. 10.1085/jgp.201812082 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10.Toombes GE, Swartz KJ. Twists and turns in gating ion channels with voltage. Science. 2016;353(6300):646–7. 10.1126/science.aah4194 [DOI] [PubMed] [Google Scholar]
  • 11.Fernandez-Marino AI, Harpole TJ, Oelstrom K, Delemotte L, Chanda B. Gating interaction maps reveal a noncanonical electromechanical coupling mode in the Shaker K(+) channel. Nat Struct Mol Biol. 2018;25(4):320–6. Epub 2018/03/28. 10.1038/s41594-018-0047-3 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12.Ishii K, Nunoki K, Yamagishi T, Okada H, Taira N. Differential sensitivity of Kv1. 4, Kv1. 2, and their tandem channel to acidic pH: involvement of a histidine residue in high sensitivity to acidic pH. Journal of Pharmacology and Experimental Therapeutics. 2001;296(2):405–11. [PubMed] [Google Scholar]
  • 13.Tombola F, Pathak MM, Isacoff EY. How does voltage open an ion channel? Annu Rev Cell Dev Biol. 2006;22:23–52. Epub 2006/05/18. 10.1146/annurev.cellbio.21.020404.145837 . [DOI] [PubMed] [Google Scholar]
  • 14.Long SB, Tao X, Campbell EB, MacKinnon R. Atomic structure of a voltage-dependent K+ channel in a lipid membrane-like environment. Nature. 2007;450(7168):376–82. Epub 2007/11/16. 10.1038/nature06265 . [DOI] [PubMed] [Google Scholar]
  • 15.Bashford D, Gerwert K. Electrostatic Calculations of the Pka Values of Ionizable Groups in Bacteriorhodopsin. J Mol Biol. 1992;224(2):473–86. WOS:A1992HL81200016. 10.1016/0022-2836(92)91009-e [DOI] [PubMed] [Google Scholar]
  • 16.Sehnal D, Vařeková RS, Berka K, Pravda L, Navrátilová V, Banáš P, et al. MOLE 2.0: advanced approach for analysis of biomacromolecular channels. Journal of cheminformatics. 2013;5(1):39 10.1186/1758-2946-5-39 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Aryal P, Sansom MS, Tucker SJ. Hydrophobic gating in ion channels. J Mol Biol. 2015;427(1):121–30. Epub 2014/08/12. 10.1016/j.jmb.2014.07.030 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Fowler PW, Sansom MS. The pore of voltage-gated potassium ion channels is strained when closed. Nat Commun. 2013;4:1872 Epub 2013/05/23. 10.1038/ncomms2858 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 19.Jensen MO, Borhani DW, Lindorff-Larsen K, Maragakis P, Jogini V, Eastwood MP, et al. Principles of conduction and hydrophobic gating in K+ channels. Proc Natl Acad Sci U S A. 2010;107(13):5833–8. Epub 2010/03/17. 10.1073/pnas.0911691107 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20.Labro AJ, Raes AL, Bellens I, Ottschytsch N, Snyders DJ. Gating of shaker-type channels requires the flexibility of S6 caused by prolines. J Biol Chem. 2003;278(50):50724–31. Epub 2003/09/19. 10.1074/jbc.M306097200 . [DOI] [PubMed] [Google Scholar]
  • 21.Syrbe S, Hedrich UBS, Riesch E, Djemie T, Muller S, Moller RS, et al. De novo loss- or gain-of-function mutations in KCNA2 cause epileptic encephalopathy. Nat Genet. 2015;47(4):393–9. Epub 2015/03/10. 10.1038/ng.3239 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22.Abraham MJ, Murtola T, Schulz R, Páll S, Smith JC, Hess B, et al. GROMACS: High performance molecular simulations through multi-level parallelism from laptops to supercomputers. SoftwareX. 2015;1–2:19–25. 10.1016/j.softx.2015.06.001 [DOI] [Google Scholar]
  • 23.Venable RM, Sodt AJ, Rogaski B, Rui H, Hatcher E, MacKerell AD Jr., et al. CHARMM all-atom additive force field for sphingomyelin: elucidation of hydrogen bonding and of positive curvature. Biophys J. 2014;107(1):134–45. Epub 2014/07/06. 10.1016/j.bpj.2014.05.034 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24.Lee J, Cheng X, Swails JM, Yeom MS, Eastman PK, Lemkul JA, et al. CHARMM-GUI Input Generator for NAMD, GROMACS, AMBER, OpenMM, and CHARMM/OpenMM Simulations Using the CHARMM36 Additive Force Field. J Chem Theory Comput. 2016;12(1):405–13. Epub 2015/12/04. 10.1021/acs.jctc.5b00935 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25.Essmann U, Perera L, Berkowitz ML, Darden T, Lee H, Pedersen LG. A smooth particle mesh Ewald method. The Journal of chemical physics. 1995;103(19):8577–93. [Google Scholar]
  • 26.Hess B, Bekker H, Berendsen HJ, Fraaije JG. LINCS: a linear constraint solver for molecular simulations. Journal of computational chemistry. 1997;18(12):1463–72. [Google Scholar]
  • 27.Nosé S. A molecular dynamics method for simulations in the canonical ensemble. Molecular Physics. 2006;52(2):255–68. 10.1080/00268978400101201 [DOI] [Google Scholar]
  • 28.Hoover WG. Canonical dynamics: Equilibrium phase-space distributions. Physical Review A. 1985;31(3):1695–7. 10.1103/PhysRevA.31.1695 [DOI] [PubMed] [Google Scholar]
  • 29.Parrinello M, Rahman A. Polymorphic transitions in single crystals: A new molecular dynamics method. Journal of Applied Physics. 1981;52(12):7182–90. 10.1063/1.328693 [DOI] [Google Scholar]
  • 30.Nosé S, Klein ML. Constant pressure molecular dynamics for molecular systems. Molecular Physics. 2006;50(5):1055–76. 10.1080/00268978300102851 [DOI] [Google Scholar]
  • 31.Humphrey W, Dalke A, Schulten K. VMD: visual molecular dynamics. Journal of molecular graphics. 1996;14(1):33–8. 10.1016/0263-7855(96)00018-5 [DOI] [PubMed] [Google Scholar]
  • 32.Wickstrom L, Okur A, Simmerling C. Evaluating the performance of the ff99SB force field based on NMR scalar coupling data. Biophysical journal. 2009;97(3):853–6. 10.1016/j.bpj.2009.04.063 [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Bashford D, Karplus M. Multiple-site titration curves of proteins: an analysis of exact and approximate methods for their calculation. The Journal of Physical Chemistry. 1991;95(23):9556–61. [Google Scholar]
PLoS Comput Biol. doi: 10.1371/journal.pcbi.1007405.r001

Decision Letter 0

Peter M Kasson, Nir Ben-Tal

8 Nov 2019

Dear Dr Chang,

Thank you very much for submitting your manuscript 'Structural and molecular insight into the pH-induced low-permeability of the voltage-gated potassium channel Kv1.2 through dewetting of the water cavity' for review by PLOS Computational Biology. Your manuscript has been fully evaluated by the PLOS Computational Biology editorial team and in this case also by independent peer reviewers. The reviewers appreciated the attention to an important problem, but raised some substantial concerns about the manuscript as it currently stands. While your manuscript cannot be accepted in its present form, we are willing to consider a revised version in which the issues raised by the reviewers have been adequately addressed. We cannot, of course, promise publication at that time.

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Nir Ben-Tal

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PLOS Computational Biology

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

[LINK]

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: The authors investigate the pH-dependent gating mechanism for the pore domain of Kv1.2 channel. The authors report that a decrease in pH, leads to protonation of residues H418 and E327. The resulting repulsive coulombic interactions between R326 and Hp418 straightens the S6 helices, leading to de-wetting of the internal cavity and channel closure. These findings could help to better understand the role of pH in the gating mechanism of channels from the Kv family in health and disease conditions.

I would like the authors to address the following comments:

*The authors refer to the deprotonated and protonated states as wild-type and Ep327/Hp418, respectively. This naming should be corrected. Both, the deprotonated and protonated states are “wild-type” if no aminoacid-residue substitution was performed.

*On page 15, the authors mention E327/H418R variant, but according to table 1, it should be E327A/H418R double-mutant.

*The authors should make clear their definition of permeability. From the paper, I understand that it is based on the access of water molecules to the internal cavity of the channel. However, it can be confused with ion permeation events, for which the authors didn’t report any occurrence.

*The authors claim to have modified “genetically” the permeability of Kv1.2 via mutation of key residues (page 16). This can be understood as if the authors performed experimental mutagenesis, which they didn’t. Hence, I would recommend using “in silico” instead of “genetically” in this sentence to avoid confusion.

*The authors should discuss if pH changes not only affect gating by leading to closure of the pore domain as they propose. For instance should pH-decrease also affect voltage sensing and gating through modification of protonation states of key residues at the voltage-sensor domain of this channel?

Regarding methodologies:

*It is not clear why the authors used the Ep327/Hp418/Ep420 MD simulation for pKa estimates. Why not to use the MD simulation of the wild-type instead?

*Could the authors discuss why the pKa analysis shows that all four H418 residues could be protonated but only two of the four E327 residues?

*The statistical significance of the results is not clear. For instance, is 3/5 closing events statistically different from 2/5, 1/5 or 0/5 closing events? The authors should increase the number of replicas per system and use some statistical figure or metric for comparison.

*For each system, were the replicas run from different initial conditions?

Reviewer #2: Review of PCOMPBIOL-D-19-01546

This is a potentially interesting computational study of pH-induced low-permeability of Kv1.2 channels. The authors suggest on the basis of simulations that acid-induced reduction in permeability of this channel is due to protonation of E327 and H148 which in turn leads to loss of curvature/bending of the helices and a consequent dewetting of water-filled cavity. This would be an interesting result. However I have some questions about the underlying logic of how the simulations were designed and performed.

The pKa calculations use MEAD – does this work for membrane proteins? How is the bilayer modelled (e.g. as a region of low dielectric)? This needs to be made explicit. The description in the Methods (page 17) is very unclear – I am still uncertain as to what was actually done even after reading is several times. It also fails to mention that the use of red circles and blue crosses refers to Fig. 2A which does not help.

From the main Results text (page 12) and Fig. 2 it is stated that “pKa values of both E327 in the A- and D-chain and H418 were around 6.0”. From Fig. 2A it can be seen that the values for E327 of the B & C chains are ~4.5. To me this implies there must have been loss of 4-fold symmetry in the closed state model – this should be described and discussed.

After describing the pKas for the closed state (model) they then go back to the open state structure (page 13), protonate E327 and H418 (earlier on they also protonated E420, page 12) and show that the channel closes. What is the relationship of the Ep327/Hp418 closed state model to the previous Ep327/Hp418/Ep420 model? Are they the same? Do they show comparable breakdown of 4-fold symmetry.

This then leads me to question the logic of the design of the simulations. Would it not be more logical to start with the (experimental) open state, calculate pKas, decide on a protonation state for lowered pH and then run the simulations to see if the channel closes? This seems to me to be a major flaw in the design of the study, and needs to be addressed directly by running the open state pKa calculations and simulations based on these (or at least explaining the logic of the simulation design used).

I have a couple of more technical points:

Fig. 3 – This describes pore closure. It would be helpful to have pore radius profiles shown for that start and end of each simulation. These should reveal to what extent dewetting is the consequence of pore narrowing/occlusion.

Fig. 4 – I suggest better descriptions of the S6 helix would be ‘bent’ and ‘straight’. However, it looks to me that even after ‘straightening’ the S6 helix remains kinked, but in a different direction. Helix kink angles can be quantified and perhaps this is needed to assess the reproducibility of the open -> closed transition in the various simulations.

Reviewer #3: This manuscript presents a molecular dynamics study of voltage-gated K+ channel Kv1.2. The authors investigate the effect of protonating residues located on the intracellular side of the channel on channel closure. Protonating two residues, E327 and H418, results in the loss of electrostatic interactions at the end of the S6 helix and correlate with S6 straightening and pore dewetting, providing molecular insight into the observed reduction in ion current at low pH.

The paper is interesting and the work appears to be well executed, but clarifying the rationale for the calculations and extending the analysis of the results presented to all the systems studied would strengthen the paper. In particular:

1. The rationale for the simulations is unclear. Why was only the closed state of the channel considered for pKa calculations? If conduction is lower but not abolished at low pH, doesn't that suggest that the channel still has a significant propensity to be open?

2. Why were only two out of four copies of E327 estimated to have a higher pKa? On the one hand, this result indicates that the simulations have not converged (the four residues should have identical pKa). On the other hand, if taken at face value, this result questions the rationale for protonating all four E327 residues in the subsequent simulations.

3. Most importantly, the manuscript indicates that as many as 8 variants of the channel were simulated (Table 1), but detailed analysis is only reported for 4 of them (Ep/Hp, EA/HR, HR, and Ep/Hp/Ep), and, surprisingly, a full analysis of the results is only provided for the Ep/Hp system without any justification for neglecting the other systems. In particular, full analysis of the above as well as the other channel variants in which dewetting was observed (namely, Ep, Hp, EA and EA/HR/EA) should be provided in order to test the validity and the generality of the mechanism proposed by the authors, linking the changes in electrostatic interactions to helix straightening and pore dewetting.

In other words, limiting the full analysis to doubly-protonated E327 and H418 is not justified. Since all the other variants lead to pore dewetting, they should all be analyzed to the same extent as the wild type and Ep/Hp variants.

4. Contrary to the claim made by the authors, the multiple sequence alignment presented in Fig. 2B does not provide rigorous evidence that the 2 residues considered are highly conserved, since most residues are conserved in the sequences shown.

5. It should be noted that the simulations have not reached equilibrium, since some trajectories led to dewetting while some others remained wetted. As such, the simulations do not provide a rigorous estimate of the relative stability of wetted and dewetted states. Although the fact that dewetting is observed in the doubly-protonated system and not in the wild type suggests that dewetting is favoured by double protonation, strictly speaking it does not rule out that dewetting could occur in the wild type over longer time scales—in other words, the apparent relative kinetic stability (or lack thereof) of the wetted state does not imply its thermodynamic stability (or lack thereof). Therefore, statements such as “This result demonstrates that the pore domain of Kv1.2 channels prefers the closed conformations under acidic conditions”, as well as multiple other statements regarding such “preference”, are not supported by the results provided. The text should be carefully revised to omit any implication that the simulations have reached equilibrium.

6. The text states: “The hinge of the S6 helix maintains electrostatic balance through two inter-subunit interactions of R326-H418 and E327-H418. These interactions stabilize the open conformation of the Kv1.2 pore domain under a neutral pH condition.” The “hinge” of S6 is not define. Moreover, the authors do not provide evidence that these are the only interactions that change upon closing of the channel. Finally, as noted in comment #3 above, the authors should provde corroborating evidence for this mechanism by analyzing the other systems that they simulated as positive controls.

In addition, note that in the interpretation of the results, correlation does not imply causality.

7. What do the authors mean by “Hp418 was electrostatically pushed by R326 at the hinge of the S6 helix”? The helical hinge seems to be far from the residues in question and is not defined (see comment #6 above).

8. The fact that the VSDs are missing from the simulations suggests that the results presented may not have been observed if the VSDs had been present. In other words, the present simulations may not provide a realistic model of the closed state of the full channel. The authors should comment on that in the manuscript.

9. Correlation coefficients should be provided for the left panels of Fig. 5.

10. Methods: Why the very high 0.6 M salt concentration? What did the “20,000 steps of equilibrating simulations” consist of?

11. “After applying MEAD programs” is vague. Enough details should be provided on the pKa calculations for a competent researcher to be able to reproduce the results provided.

12. In the description of pKa estimates, “uncertainty” should be used rather than “flexibility”.

**********

Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Computational Biology data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #2: No:

Reviewer #3: None

**********

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Reviewer #1: No

Reviewer #2: No

Reviewer #3: No

PLoS Comput Biol. doi: 10.1371/journal.pcbi.1007405.r003

Decision Letter 1

Peter M Kasson, Nir Ben-Tal

12 Feb 2020

Dear Prof. Chang,

Thank you very much for submitting your manuscript "Structural and molecular insight into the pH-induced low-permeability of the voltage-gated potassium channel Kv1.2 through dewetting of the water cavity" for consideration at PLOS Computational Biology. As with all papers reviewed by the journal, your manuscript was reviewed by members of the editorial board and by several independent reviewers. The reviewers appreciated the attention to an important topic. Based on the reviews, we are likely to accept this manuscript for publication, providing that you modify the manuscript according to the review recommendations.  While some of the reviewers' remaining changes require attention, we anticipate that this should be feasible.

Please prepare and submit your revised manuscript within 30 days. If you anticipate any delay, please let us know the expected resubmission date by replying to this email. 

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Peter M Kasson

Associate Editor

PLOS Computational Biology

Nir Ben-Tal

Deputy Editor

PLOS Computational Biology

***********************

A link appears below if there are any accompanying review attachments. If you believe any reviews to be missing, please contact ploscompbiol@plos.org immediately:

[LINK]

Reviewer's Responses to Questions

Comments to the Authors:

Please note here if the review is uploaded as an attachment.

Reviewer #1: The revised version improved and a lot. I am very pleased to recommend it for publication pending proof-reading and editorial changes. Several of the figures are very complex and multi-panel with low resolution (this could be an artefact of the submission system). I also had difficulties in places to comprehend take-home message due to very convoluted and very long paragraphs. Nonetheless, the story is interesting and will without doubts find its readership.

Reviewer #3: Some of my earlier concerns have not been addressed satisfactorily.

1. In particular, my earlier point #3: To support the conclusions of the paper, it is essential to report the full detailed analysis of all 8 systems studied in order to provide controls for the proposed mechanism. To address this request, the authors have added supplementary figures showing full analysis of the other systems. However, they do not mention or discuss these results explicitly in the main text. This is all the more surprising because the results actually corroborate their mechanistic conclusions regarding the effect of charge-charge interactions on the structure and gating of the pore domain. The authors should discuss these results, which would significantly strengthen the paper.

2. All the responses given to the reviewers should also be reflected in the text. However, this was not done for my previous request #10: the authors should explain the choice of 0.6 M salt concentration not only in their reply to me, but also in the text of the manuscript. This comment also applies to some of the responses made to the other 2 reviewers.

Problems with the interpretation of the results:

3. Since none of the closing simulations are at equilibrium, the quantities reported in the Figures as “free energy landscapes (in arbitrary units)” are wrong on two counts: (a) these are not free energies; and (b) free energy is not unitless. I would recommend that the authors report the results as 2D histograms to avoid these issues.

4. In addition, since none of the closing simulations are at equilibrium (observed dewetting transitions being irreversible), the amount of time spent in the closed state (reported as number of snapshots in Table 1) is meaningless. Whether or not closing occurred early or late in any simulation is essentially random (as it would be in an exponential relaxation process). As such, it is more appropriate to report, as the authors did in the previous version of the paper, the number of simulations that underwent irreversible closing events (i.e., at least 1 out of 5 for all the systems except the unprotonated WT), as an indication of the capacity of the systems to undergo dewetting. While all the systems other than the unprotonated WT underwent closing, based on the data provided and the above considerations, it is not possible to quantify the likelihood that any of these systems would close. As such, it is not possible to rank them either. In other words, ALL THE VARIANTS PRODUCED INDISTINGUISHABLE RESULTS. This point should be conveyed in the text.

5. The simulations show that the channel closes when the total charge of the titratable cluster changes by +1, +2, or +3. However, the authors confine their analysis and conclusions to the effect of a +2 change, when in fact the same result is observed with +1 and +3 changes, both with protonation and with mutations. This should be conveyed in the text.

6. The statement that “the H418 residue is a more suitable target for a single mutation than E327” is not supported by the data shown and should be removed. There is no discernible effect of changing one residue or the other or both.

**********

Have all data underlying the figures and results presented in the manuscript been provided?

Large-scale datasets should be made available via a public repository as described in the PLOS Computational Biology data availability policy, and numerical data that underlies graphs or summary statistics should be provided in spreadsheet form as supporting information.

Reviewer #1: Yes

Reviewer #3: None

**********

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Reviewer #1: No

Reviewer #3: No

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PLoS Comput Biol. doi: 10.1371/journal.pcbi.1007405.r005

Decision Letter 2

Peter M Kasson, Nir Ben-Tal

13 Mar 2020

Dear Prof. Chang,

We are pleased to inform you that your manuscript 'Structural and molecular insight into the pH-induced low-permeability of the voltage-gated potassium channel Kv1.2 through dewetting of the water cavity' has been provisionally accepted for publication in PLOS Computational Biology.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch with a set of requests.

***The editor would also suggest the following minor change to the text***

In your revision, you altered text to read "Ensembles population of log scale".  I would recommend writing "log probabilities of sampled conformations", which I believe more precisely describes the plotted data.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

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Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Computational Biology. 

Best regards,

Peter M Kasson

Associate Editor

PLOS Computational Biology

Nir Ben-Tal

Deputy Editor

PLOS Computational Biology

***********************************************************

PLoS Comput Biol. doi: 10.1371/journal.pcbi.1007405.r006

Acceptance letter

Peter M Kasson, Nir Ben-Tal

2 Apr 2020

PCOMPBIOL-D-19-01546R2

Structural and molecular insight into the pH-induced low-permeability of the voltage-gated potassium channel Kv1.2 through dewetting of the water cavity

Dear Dr Chang,

I am pleased to inform you that your manuscript has been formally accepted for publication in PLOS Computational Biology. Your manuscript is now with our production department and you will be notified of the publication date in due course.

The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript.

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Thank you again for supporting PLOS Computational Biology and open-access publishing. We are looking forward to publishing your work!

With kind regards,

Laura Mallard

PLOS Computational Biology | Carlyle House, Carlyle Road, Cambridge CB4 3DN | United Kingdom ploscompbiol@plos.org | Phone +44 (0) 1223-442824 | ploscompbiol.org | @PLOSCompBiol

Associated Data

    This section collects any data citations, data availability statements, or supplementary materials included in this article.

    Supplementary Materials

    S1 Fig. Simulation results for WildUnP.

    (A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for WildUnP.

    (TIF)

    Click here for additional data file. (1.4MB, tif)
    S2 Fig. Simulation results for Hp418.

    (A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for Hp418.

    (TIF)

    Click here for additional data file. (1.7MB, tif)
    S3 Fig. Simulation results for Ep327/Hp418.

    (A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for Ep327/Hp418.

    (TIF)

    Click here for additional data file. (1.8MB, tif)
    S4 Fig. Simulation results for Ep420.

    (A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for Ep420.

    (TIF)

    Click here for additional data file. (1.7MB, tif)
    S5 Fig. Simulation results for Ep327/Hp418/Ep420.

    (A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for Ep327/Hp418/Ep420.

    (TIF)

    Click here for additional data file. (1.7MB, tif)
    S6 Fig. Simulation results for H418R.

    (A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for H418R.

    (TIF)

    Click here for additional data file. (1.6MB, tif)
    S7 Fig. Simulation results for E327A/H418R.

    (A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for E327A/H418R.

    (TIF)

    Click here for additional data file. (1.7MB, tif)
    S8 Fig. Simulation results for E420A.

    (A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for E420A.

    (TIF)

    Click here for additional data file. (1.8MB, tif)
    S9 Fig. Simulation results for E327A/H418R/E420A.

    (A) Ensembles population of log for the R326–H418 distances and dihedral angles, and (B) ensembles population of log scale for the dihedral angles and number of water molecules in the water-filled cavity. The time evolution of (C) the distance between R326 and H418 residues, (D) the dihedral angle, and (E) the number of water molecules in the water cavity from five individual trajectories for E327A/H418R/E420A.

    (TIF)

    Click here for additional data file. (1.8MB, tif)
    Attachment

    Submitted filename: Highlighted_final_Revision_20191224.docx

    Click here for additional data file. (1.4MB, docx)
    Attachment

    Submitted filename: Respons_2020_03_04.docx

    Click here for additional data file. (660.6KB, docx)

    Data Availability Statement

    Deposit files We performed MD simulations using GROMACS 5.0.6 that can be obtained from http://www.gromacs.org/Downloads_of_outdated_releases We provide all input files to run the MD simulations including input coordinates, topologies and parameter files and etc. Additionally, we provide all the trajectory files. Input files: http://wyu.dgist.ac.kr/kv12/input/ Trajectory files: http://wyu.dgist.ac.kr/kv12/traj/.

    Articles from PLoS Computational Biology are provided here courtesy of PLOS

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