Parent dataset and code from: Atomistic Mechanisms of the regulation of small conductance Ca 2+ -activated K + channel (SK2) by PIP2
Data files
Aug 30, 2024 version files 636.56 KB
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README.md
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scripts.tar.gz
Abstract
Small conductance Ca 2+ -activated K + channels (SK, K Ca 2) are gated solely by intracellular microdomain Ca 2+. The channel has emerged as a therapeutic target for cardiac arrhythmias. Calmodulin (CaM) interacts with the CaM binding domain (CaMBD) of the SK channels, serving as the obligatory Ca 2+ sensor to gate the channels. In heterologous expression systems, phosphatidylinositol 4,5-bisphosphate (PIP2) coordinates with CaM in regulating SK channels. However, the roles and mechanisms of PIP2 in regulating SK channels in cardiomyocytes remain unknown. Here, optogenetics, magnetic nanoparticles, combined with Rosetta structural modeling and molecular dynamics (MD) simulations revealed the atomistic mechanisms of how PIP2 works in concert with Ca 2+ -CaM in the SK channel activation. Our computational study affords evidence for the critical role of the amino acid residue R395 in the S6 transmembrane domain, which is localized in propinquity to the intracellular hydrophobic gate. This residue forms a salt bridge with residue E398 in the S6 transmembrane domain from the adjacent subunit. Both R395 and E398 are conserved in all known isoforms of SK channels. Our findings suggest that the binding of PIP2 to R395 residue disrupts the R395:E398 salt bridge, increasing the flexibility of the transmembrane segment S6 and the activation of the channel. Importantly, our findings serve as a new platform for testing structural-based drug designs for therapeutic inhibitors and activators of the SK channel family. The study is timely since inhibitors of SK channels are currently in clinical trials to treat atrial arrhythmias.
README: Parent dataset and code from: Atomistic Mechanisms of the regulation of small conductance Ca 2+ -activated K + channel (SK2) by PIP2
https://doi.org/10.5061/dryad.ksn02v7dj
Description of the data and file structure
README file for parent dataset linked to 5 dataset child submissions for the article titled:
Atomistic mechanisms of the regulation of small conductance Ca 2+ -activated K + channel (SK2) by PIP2
File author Dr. Ryan Woltz. For questions please email rlwoltz@arizona.edu.
Document written 2024/08/12
Requirements to load and visualize trajectories.
-vmd\
-minimum 96GB of RAM. (if you do not have this load with the "skip" or "step" in vmd)\
-UCSF Chimera\
-hole2\
TTClust
IMPORTANT NOTES:
- This deposit does not include scripts to run programs TTClust, hole2, or UCSF chimera To replicate all figures in the PNAS paper please download these programs. methods for these programs are found in the methods section of the PNAS paper.
- A coloring script that was used to create the pore volume images is provided (see scripts usage). However, it is only compatible with chimera NOT chimeraX. This script simply extracts sphere radius values, found in output files, for the pseudo atoms created by hole2. The extracted values are then stored in the b-factor column of a pdb file containing the channel and the pseudo atoms. As the script opens chimera and the pdb it sets the VDW of each pseudo atom equal to its b-factor value. Finally, it represents the channel as ribbon and the pseudo atoms as spheres and colors based on b-factor ranges. Please read the script for coloring ranges, color codes, and how to change them.
- To make the color script work many directory paths inside the files must be changed for the user's computer. This is only provided as a convenience/template as a similar script can be made to work with ChimeraX or any other program. There are no guarantees this script will work for the user and no troubleshooting assistance will be provided. However, in-depth usage and disclosures are printed in the terminal to the user when the script is run. So if it doesn't work please read the usage or recreate note 2 in your language/program of choice.
Directory structure:
This deposit contains 18 simulations. The directory names will include descriptions for all simulations which are described here:
The simulations are split into 3 conformations:
-sk2m\
-sk2n\
-sk2o
The name structure for this is
sk2 = protein\
m/n/o = conformation of closed, intermediate, and open (respectively). This letter comes from the sk4 Structures that were used as a template in the homology modeling (6cnm/6cnn/6cno). i.e. sk2m is the human sk2 protein homology model using 6cnm as a template and is the closed state of the sk2 channel.
Inside the sk2o directory, the simulations are then split between applied voltage and no applied voltage. Simulations with applied voltage will have "applied-EV" in the name and are used to confirm the open state is conductive. Sk2o simulations with no applied voltage are compared to sk2m and sk2n as they do not have applied voltage in the simulation.
Within these 4 categories (sk2m/sk2n/sk2o - applied voltage/sk2o - no applied voltage) the simulations are broken down further into PIP2 concentrations and replica numbers (copy1, copy2, etc). The pip2 concentrations and replica numbers are in the name of the directory. The starting AMBER “step5” input files for each replica are copies. To further distinguish these directories the charmm-gui unique job id is included in the name of the simulation. If the simulation has similar conditions but a different unique job id then they are NOT considered a replica.
Inside each simulation, we have starting files used to generate the Anton2 runs. These are not necessary for analysis but are included for transparency and will be described in the file description section. Also contained in each directory is the "workdir.X" directory, where X is a number 1-4. This work directory contains the trajectory (.dcd) and protein structure files (.psf) to load the simulations.
To analyze:
Copy the full contents of the "scripts" directory into the workdir.X you would like to analyze. A script called "automated-analysis-script.sh" is provided which contains detailed descriptions of how to run each script. This file can be edited, as described in the automated-analysis-script.sh file, to run a series of analyses automatically.
automated-analysis-script.sh SCRIPT IS GENERIC TO ALL SIMULATIONS AND MUST BE MODIFIED AS DESCRIBED FOR EVERY ANALYSIS!
Script directory description:
This directory contains all scripts needed for analysis. Copy contents to simulation for analysis
automated-analysis-script.sh | A bash script containing very detailed usage and execution instructions for recreating the figures in the PNAS publication. Please note that the commands require modification to run since current commands are generic and have placeholder strings. If properly modified, this script can automate analysis For full data generations it is highly recommended to create nesting “for” or “while” loops analysis commands inside loops, run in the background to parallelize calculations, and scan through all possible analyses of interests. |
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ion_tracker.py | vmd script that tracks conduction through the selectivity filter (SF). NOTE: This is specific to the SK1-3 channel SF as it selects for the SIGYGD sequence. Please change if the SF sequence is NOT SIGYGD |
pip2_movement-color.tcl | vmd script that saves data required for pip2_time_tracker.py |
pip2_time_tracker.py | Python tracks pip2 movement in the membrane throughout a simulation and plots by time. Requires pip2_movment-color.tcl in the same directory to function. |
prot_center.tcl | vmd script required for most scripts in this list. THIS FILE MUST BE IN THE DIRECTORY THAT SCRIPTS ARE RUN IN OTHERWISE ANALYSIS WILL FAIL. The script centers the protein in all frames to the origin. |
RMSD.py | Python script used to plot data found in the rmsd-data and bond-data directories. This script can be used to graph any data file that has the same format including data generated by the SASA script below or any user-made script given identical file formats. |
simulation_interaction_analysis.py | Python script that tracks and plots all h-bonds, hydrophobic interactions, pi-stacking, and salt bridges found between two selections. see the "automated" script for details and usage. |
aux_scripts/* | location for the main scripts that are not required to be in the same directory as the trajectory |
Files contained within aux_scripts/ | |
bond-gate-measure.tcl | vmd script to measure bond distances between the “CG1” gate atoms on opposing chains and write to a .dat file. used to plot gate distances and for the geometric area histogram. |
bond-SF-measure.tcl | vmd script to measure bond distances between the backbone “O”s of the selectivity filter on opposing chains and writes to a .dat file. used to plot selectivity filter distances. |
hsk2-master-pip2-binding-residues.dat | A file containing a list of residues for SASA analysis. This list was created by identifying any basic residue that interacts with PIP2 at any point in any simulation. This list can be modified to analyze any residues of interest. |
myrmsd.tcl | vmd script that generates RMSD data files for all major sections of the sk2 protein. The only data files that are plotted automatically by automated-analysis-script.sh are the full protein, pore domain (PD), and selectivity filter (SF). If a specific chain or local RMSD is needed, please see the output from this script in rmsd-data/ directory for a list of all data plottable data files. |
rmsd-bond-table-generation.tcl | vmd script that runs all bond measure and rmsd scripts. |
sasa-hSK2-master.tcl | vmd script that measures the SASA for all residues in the file hsk2-master-pip2-binding-residues.dat |
aux_scripts/hole2/* | Directory containing input, running, and coloring scripts to generate pore volume figures. Scripts require downloading of hole2 and UCSF Chimera and for the programs to be in $PATH |
Files contained within aux_scripts/hole2/* | |
chimera-convert.sh | script used to color and expand pseudo atoms in chimera for image purposes only. NOTE: Directory paths must be changed in scripts to work. Requires hole2 to work. |
hole.inp | .inp (input parameters) for hole2 analysis |
hsk2n-starting-structure.pdb | Example of a pdb used as an input to hole2 analysis NOTE: must be protein only. |
Description of starting files contained in the charmm-gui-*/ directory:
NOTES:
- Not all files listed are in each simulation directory.
- These are files for transparency and are supplemental to the simulation. no file in this directory is required for analysis.
- AMBER starting files begin with "step5" and this is the step name generated by charmm-gui.
- AMBER files converted into system files and run on ANTON2 start with "step7.100". Step 7 is the step named in charmm-gui for the production run of AMBER. The "100" stands for the 100th ns of the simulation which is how long it requires to equilibrate the protein before production.
base.ark | File containing running parameters for ANTON2. - |
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cpptraj.log | Log for converting amber simulation to ANTON2 simulations. |
prep1.script - | File containing running parameters for ANTON2. |
run1.script | File containing running parameters for ANTON2. |
step5_input-amber.parm7 | Starting file from the amber simulation. load into vmd with .rst7 or .nc file |
step5_input.inp | Simulation input file generated by charmm-gui. |
step5_input_minimization.str | .str file generated by charmm-gui. Required to perform AMBER equilibration. |
step5_input.out | An output file generated by charmm-gui to describe the making of step5 files. |
step5_input.parm7 | The starting structure file for AMBER simulation. identical to step5_input-amber.parm7. |
step5_input.pdb | Step5 protein data bank file. Structure file with coordinates. |
step5_input.psf | Step5 protein structure file |
step5_input.rst7 | AMBER starting coordinates. Use with .parm7 files as the starting structure descriptor file. |
step7.100_production.ascii.rst7 | Coordinate file from amber converted (cpptraj.log) into an ascii format. |
step7.100_production.mdin | Input parameters for amber for this stage of the simulation. |
step7.100_production.mdinfo | Md information for this stage of the simulation. |
step7.100_production.mdout | Md output file containing energy calculations. |
step7.100_production.nc | Trajectory file for this stage. contains 10 frames. rst7 file is generated from this. |
step7.100_production.output | Output/errors from AMBER on the running of this stage for the simulation. |
step7.100_production.rst7 | Coordinate file used to create starting files for ANTON2. |
step7_production.inp | Step7 file containing import of parameter files needed for simulation. |
submit1.script | Script used to run ANTON2 simulation. |
system.allff.dms | Step 2 of converting. step7.100_production.ascii.rst7 into ANTON2 starting file. |
system.allff.final.dms | Step 3 of converting step7.100_production.ascii.rst7 into ANTON2 starting file. |
system.allff.final.posres.dms | Final step of converting step7.100_production.ascii.rst7 into ANTON2 starting file. THIS FILE IS USED TO RUN ANTON2 SIMULATIONS. |
system.dms | Step 1 of converting step7.100_production.ascii.rst7 into ANTON2 starting file. |
Data and trajectory file description:
Data files are in the workdir.X directory. There are 2 file types:
- psf - protein structure file. starting structure bonding and structural information required for trajectory
- dcd - trajectory file that contains full simulation.
specific file description:
to load trajectory with no analysis use command:
$> vmd step5_input_renumbered.psf pbc-wrap-nowater.dcd
pbc-wrap-nowater.dcd | Main trajectory file.THIS FILE CONTAINS WATER. Creating a file and trajectory purely for analysis with no water is highly recommended as this reduces the hardware and time requirements for analysis to a fraction compared to analyzing the system with water. |
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step5_input_nowater.psf | Copy of step5_input.psf. THIS FILE CONTAINS WATER. Creating a file and trajectory purely for analysis with no water is highly recommended as this reduces the hardware and time requirements for analysis to a fraction compared to analyzing the system with water. |
step5_input.psf | Original and unmodified starting structure file. |
step5_input_renumbered_chain_rename.psf | Modified step5_input.psf to renumber chains to match UniProt numbering and classify SK2 as chain A and CaM as chain B. This file is depreciated. |
step5_input_renumbered.psf | Modified step5_input.psf to renumber chains to match UniProt numbering. This is the file used for analysis in the PNAS publication. |
IMPORTANT NOTE: It is recommended to use step5_input_renumbered.psf for analysis. Although, any of the psf should work with the dcd provided. However, if another psf is used with the dcd the figure residues numbering will be different than the PNAS publication. These extra files are still provided as having unique or alternate residue numbers is preferred in certain cases. The residue numbering listed for sk2 and CaM matches the UniProt numbering, not structural numbering which can be offset by 1 residue. |
Methods
See the PNAS publication for a full description and references
Computational modeling of hSK2 channel to generate starting structures for MD simulations:
The generation of structural models for the hSK2 channel was achieved via three stages using Rosetta molecular modeling (Online Supplemental Fig. S1) as described below.
Electron density map refinement:
In the first stage, we refined and converted three states of the hSK4-CaM cryo-EM structures (PDB IDs: 6CNM, 6CNN, and 6CNO) into Rosetta-optimized energy with Rosetta 2021 software. Cryo-EM refinement was performed with side chains only being optimized. This conversion facilitated the energy terms of these structures to align with Rosetta's scoring function (Score.gd2), leading to improved homology modeling. We used a modified version of the Rosetta demo included in the Rosetta software
(https://new.rosettacommons.org/demos/latest/public/electron_density_structure_refinement/structure_refinement) (7, 8).
Homology modeling of hSK2 channels in closed, intermediate, and open states:
In the second stage, we employed the modified Rosetta Comparative Modeling (RosettaCM) protocol to generate hSK2 homology models (8-15). This involved conducting sequence alignments between hSK4 and hSK2 channels, and subsequently formatting the aligned sequences into a Grishin format suitable for RosettaCM. Regions in hSK2 that were not present in hSK4 structures were modeled using the loop modeling protocol, (https://www.rosettacommons.org/docs/latest/application_documentation/structure_prediction/loop_modeling/KIC_with_fragments) (16) primarily the S3-S4 linker. The template protocol can be found at this link: (https://new.rosettacommons.org/demos/latest/Home). The top model from the cryo-EM refinement of the hSK4 step was then used as the template for homology modeling for hSK2. The first attempt was to only model hSK2, then dock CaM onto the channel. However, the absence of CaM in the models triggered large movements in the CaM binding domain (CaMBD) in the C-terminal domain of hSK2 (main-text Fig. 2A) due to two factors: A) CaMBD is perpendicular to the S1-S6 transmembrane segments of hSK2 and B) the linker region that connects the CaMBD and S1-S6 is very flexible. In contrast, the inclusion of CaM led to convergence and improved agreement in the top models for the CaMBD (main-text Fig. 2B-D), resulting in a model that is much closer to the template. In our attempt to create reliable homology models, several features were included in the protocol, namely implicit lipid membrane environment to accurately model membrane-spanning protein segments, enforcing symmetry to preserve a four-fold homotetrameric hSK2-CaM complex symmetry, explicit inclusion of metal ions to preserve the Ca 2+ binding loops, treatment of multiple chains that include hSK2 and CaM, and loop modeling for the flexible regions of the protein missing from the cryo-EM structures. However, an error occurred between the symmetry function and the metal binding feature, specifically, the Ca 2+ ions assumed the exact coordinates of the first C α atom of the first residue of CaM. This necessitated the homology modeling to be performed without the symmetry function. In addition, we meticulously monitored for possible displacement of the backbone carbonyl oxygen atoms in the selectivity filter (SF) of hSK2 during the homology modeling since deformation of the SF may lead to a non-conducting channel in the MD simulations. Indeed, repulsion of the oxygen atoms results in the SF deformation at amino acid residues I359 with widening and shortening of the SF. This necessitated the inclusion of harmonic restraints that were determined empirically, and a weighted value of 100.0 kcal/mol/Å 2 was used on the C α atoms of the backbone of each amino acid residue in the SF. Additionally, the deformation was minimized with the explicit inclusion of K + ions in the SF. Interestingly, we did observe that the open state of hSK2 required the largest restraints to maintain the SF structure. 50,000 models were created for each conformational state of hSK2-CaM, and a top model was selected with a standard clustering selection process.
Clustering and top model selection:
Standard Rosetta clustering was performed for each cryo-EM refinement and homology modeling step with minor differences in the filtering process, based on the models that were used as inputs. The cryo-EM refinement output structures were filtered first by sorting using the “r15” term (REF2015 terms: SCORE – elec_dens_fast) and keeping the lowest 50% of r15 ranked decoys. The resulting list of decoys was then sorted by elec_dens_fast term, and the lowest 20% were kept. This final selection was then clustered with a radius determined empirically to provide a distribution, where the most decoys (~30%) were in the first cluster, and subsequent clusters were with progressively fewer decoys. An attempt to obtain upwards of 90% of all models in the first 20 clusters was made. The centers of the top 10 clusters were then evaluated for retention of similar critical structural features described above. The top model from these 10 was used as a template for the homology modeling. The results of the homology modeling were sorted by the total score term with the lowest 10% used for clustering. Clustering of the homology models was performed in the same manner as the cryo-EM refinement with the top model used as the starting structure for MD simulations.
Molecular dynamics (MD) simulations:
The final stage involved molecular dynamics (MD) simulations. The hSK2 models derived from homology modeling were initially visualized without a membrane and then embedded into 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) lipid bilayer and solvated by 0.15 M KCl aqueous solution using CHARMM-GUI (17-19) (Fig. 3A). Online Supplemental Table S1 provides a summary of 18 5-µs-long MD simulations on Anton 2 supercomputer (20) of hSK2-CaM complex in POPC membrane with or without mono-protonated state of phosphatidylinositol -(4,5)-bisphosphate (PIP2) with protonation on P4 oxygen atom (SAPI24) at 2.5, 5, and 10% in the lower leaflet of the lipid bilayer. The concentrations of PIP2 were chosen based on recent estimations of PIP2 in the lower leaflet of the lipid bilayer that can be as high as 2-5% (21). In addition, we performed a total of 27 simulations at 1 µs using either NAMD 3.0 alpha (22) or AMBER18 (23) on the high-performance computing (HPC) EXPANSE platform (San Diego Supercomputer Center at the University of California, San Diego) with computational time granted through Extreme Science and Engineering Discovery Environment, XSEDE (now Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support, ACCESS). MD simulations were run in the NPT ensemble at 310 K and 1 atm pressure using tetragonal periodic boundary conditions using a standard set of non-bonded cutoffs and other options as in our previous studies (24, 25). All-atom biomolecular CHARMM36m protein (26), C36 lipid (27, 28), and TIP3 water (29) were used. Each MD simulation system was equilibrated for 2.27 ns with suggested gradually diminishing positional and dihedral restraints provided by CHARMM-GUI scripts. Due to the relatively large size of the hSK2-CaM protein complex in our MD simulations and to ensure its conformational stability (as described above), a follow-up extended equilibration MD simulation was performed for 100 ns with gradually reduced restraints on protein backbone atoms of the hSK2-CaM complex and its components as shown in main-text Fig. 3B. The extended equilibration protocol was performed on the EXPANSE platform with AMBER18 (Fig. 3B). The protein backbone restraints were maintained using the force constant of 1.0 kcal·mol -1 ·Å -2 during the initial environment equilibration until the start of the extended equilibration stage, when the restraints were successively reduced in a 5 or 10 ns stepwise fashion, starting from the periphery of the protein and moving towards the center of the protein over a period of 100 ns (main-text Fig. 3B). The extended equilibration protocol was determined empirically to maintain the stability of essential structural features such as the pore domain or SF. Each successive step of either 5 or 10 ns was determined based on root-mean-square deviation (RMSD) profiles reaching a plateau indicating system equilibration. Post 100 ns of this extended equilibration, the production MD simulation runs were performed for 1000 ns using AMBER18 on EXPANSE or for 5000 ns on Anton 2. Small restraints were used on the C α backbone atoms of the selectivity filter residues SIGYGD throughout the production stage (Fig. 3B). The 27 MD simulations created were divided as follows: 3 distinct hSK2 conformational states (closed, intermediate, and open) embedded into POPC:PIP2 complex membranes with PIP2 residing in the lower leaflet only (100:0, 95:5, 90:10). All simulations were run in triplicate to ensure consistency. The 18 most stable simulations of the 27 runs using AMBER18 were identified and transferred to Anton 2 by using molecular coordinates and velocities from the final frame of the 100 ns protein equilibration stage as a starting point. The MD simulations on Anton 2 are unbiased 5-µs-long runs and are described in Online Supplemental Table S1. The MD simulation trajectories were analyzed via root-mean-square deviation (RMSD) calculations (main-text Fig. 3C).
Pore volume representation and initial state characterization:
The distinct initial channel states were characterized by central channel pore radius mapping using HOLE analysis script (30) (main-text Fig. 4A-C). We thus monitored channel conformational states by measuring the minimum hydrophobic gate diameter for each frame (main-text Fig. 4D-E). This was performed by measuring the distance between side-chain C g1 (CG1) atoms of the V390 residues on the pore-lining S6 helices from opposing subunits.
Ion conduction:
Ion conduction was measured by monitoring the Z-axis coordinates of K + ions through the SF (main-text Fig. 4F-G). We then quantified the number of ions that completed a connected path through the SF to avoid counting ions that would “jump” from the intracellular aqueous compartment to the extracellular one using periodic boundary conditions (PBC) image recentering.
PIP2 movement and specific residues of SK2-CaM complex involved in binding:
This was determined by tracking its XY coordinates and plotting 50 points per graph for each PIP2 molecule. The identification of all possible unbiased PIP2 binding sites was achieved using modified scripts from MD analysis GitHub (https://github.com/MDAnalysis/mdanalysis), (31) and amino acid residues of interest were located by identifying salt bridges formation between the hSK2-CaM complex and PIP2 head group.
Visual, structural, and computational analysis:
Completed using Visual Molecular Dynamics (VMD) (32), UCSF Chimera (33), and ChimeraX (34) (University of California San Francisco).
Clustering Analysis:
After the completion of the MD simulations, we conducted a clustering analysis of the simulation data. The primary objective of this analysis was to categorize conformations based on their similarity and to pinpoint the most frequently occurring conformational states of hSK2. Additionally, this analysis aimed to investigate the coordination of hSK2 and PIP2 clusters and the formation of the R395:PIP2 salt bridge. To achieve these goals, we employed the TTClust program, a specialized tool specifically designed for trajectory clustering (35) (https://github.com/tubiana/TTClust). We first aligned the PIP2 molecule with respect to the hSK2-CaM. The trajectory of the aligned PIP2 molecule was saved as a binary DCD trajectory file. Subsequently, we executed the TTClust program using the command: ttclust -f HETA-c.dcd -t HETA-c.pdb -sa "none" -sr "all". The -sa parameter was set to "none" to indicate no further alignment was required as it was already performed in the first step. The -sr parameter was set to "all" to select all atoms in the analysis. We then analyzed the clustering results to identify clusters with PIP2:R395 salt bridges, focusing on the major residues involved. We visualized and compared these clusters against the hSK2-CaM structure to observe their distribution and identify their location. Furthermore, we calculated the time point at which a salt bridge was detected via a 3.6 Å cutoff.
Solvent-Accessible Surface Area (SASA):
Analyses Solvent-accessible surface area (SASA) analyses were performed to quantify the solvent exposure of each amino acid residue in the transient, transfer, and activation PIP2 binding sites from the closed, intermediate, and open states. There were no significant differences in the SASA over time or averaged SASA for amino acid residues within the same state for MD simulations with the hSK2-CaM embedded in a POPC or a POPC/PIP2 membrane if a PIP2 molecule did not directly interact with that amino acid residue. Therefore, we calculated the SASA for each amino acid residue on the four subunits for each frame based on binary classification: bound vs. unbound by PIP2 (the distance between any anionic oxygen on the PIP2 head group and any cationic nitrogen on the side chain of basic amino acids was <4 Å was defined as bound and >4 Å was defined as unbound). For the open hSK2 state, we further classified the MD simulations into 2 additional groups with an intact hydrophobic gate and a collapsed hydrophobic gate, which became nonconductive after the initial K + ions in the channel pore were depleted. These simulations were excluded from the analyses since there was major asymmetry of the pore.