Katarzyna Walczewska-Szewc1,2, Wiesław Nowak1. 1. Institute of Physics, Faculty of Physics, Astronomy and Informatics, Nicolaus Copernicus University, Grudziądzka 5, 87-100 Toruń, Poland. 2. Centre for Modern Interdisciplinary Technologies, Nicolaus Copernicus University, Wileńska 4, 87-100 Toruń, Poland.
Abstract
Inward rectifying potassium ion channels (KATP), sensitive to the ATP/ADP concentration ratio, play an important, control role in pancreatic β cells. The channels close upon the increase of this ratio, which, in turn, triggers insulin release to blood. Numerous mutations in KATP lead to severe and widespread medical conditions such as diabetes. The KATP system consists of a pore made of four Kir6.2 subunits and four accompanying large SUR1 proteins belonging to the ABCC transporters group. How SUR1 affects KATP function is not yet known; therefore, we created simplified models of the Kir6.2 tetramer based on recently determined cryo-EM KATP structures. Using all-atom molecular dynamics (MD) with the CHARMM36 force field, targeted MD, and molecular docking, we revealed functionally important rearrangements in the Kir6.2 pore, induced by the presence of the SUR1 protein. The cytoplasmic domain of Kir6.2 (CTD) is brought closer to the membrane due to interactions with SUR1. Each Kir6.2 subunit has a conserved, functionally important, disordered N-terminal tail. Using molecular docking, we found that the Kir6.2 tail easily docks to the sulfonylurea drug binding region located in the adjacent SUR1 protein. We reveal, for the first time, dynamical behavior of the Kir6.2/SUR1 system, confirming a physiological role of the Kir6.2 disordered tail, and we indicate structural determinants of KATP-dependent insulin release from pancreatic β cells.
Inward rectifying potassium ion channels (KATP), sensitive to the ATP/ADP concentration ratio, play an important, control role in pancreatic β cells. The channels close upon the increase of this ratio, which, in turn, triggers insulin release to blood. Numerous mutations in KATP lead to severe and widespread medical conditions such as diabetes. The KATP system consists of a pore made of four Kir6.2 subunits and four accompanying large SUR1 proteins belonging to the ABCC transporters group. How SUR1 affects KATP function is not yet known; therefore, we created simplified models of the Kir6.2 tetramer based on recently determined cryo-EM KATP structures. Using all-atom molecular dynamics (MD) with the CHARMM36 force field, targeted MD, and molecular docking, we revealed functionally important rearrangements in the Kir6.2 pore, induced by the presence of the SUR1 protein. The cytoplasmic domain of Kir6.2 (CTD) is brought closer to the membrane due to interactions with SUR1. Each Kir6.2 subunit has a conserved, functionally important, disordered N-terminal tail. Using molecular docking, we found that the Kir6.2 tail easily docks to the sulfonylurea drug binding region located in the adjacent SUR1 protein. We reveal, for the first time, dynamical behavior of the Kir6.2/SUR1 system, confirming a physiological role of the Kir6.2 disordered tail, and we indicate structural determinants of KATP-dependent insulin release from pancreatic β cells.
ATP-sensitive inwardly rectifying potassium channels (KATPs) are
transmembrane proteins present in the pancreas, cardiac myocytes,
skeletal muscles, and neurons.[1] The great
interest in understanding their function stems, i.e., from their critical
role in regulation of insulin secretion from pancreatic β cells.[2] In response to a change in the ratio of ATP to
ADP concentrations, the channels close and stop the potassium ions
outflow, which results in a rapid depolarization of the cell membrane.
Upon such a signal, voltage-gated calcium channels open, and the intracellular
calcium level rises in β cells. More calcium triggers insulin
secretion into the blood. A change of ATP/ADP concentrations is the
physiological response to the increase of the blood glucose level
in healthy individuals. However, some mutations in the KATP complex
may affect its function and lead to neonatal diabetes (ND)[2,3] or congenial hyperinsulinism (HI).[4] To
date, more than 200 mutations in genes encoding the KATP channel (KCNJ11
and ABCC8 for Kir6.2 and SUR1 components, respectively) have been
reported. Spatial localizations of these mutations give useful hints
on KATP architecture and function.[5] The
KATP channels are natural targets in type 2 diabetes treatment. Drugs
from the sulfonylurea (SU) group, as well as other secretogogues,
are known to exert an inhibitory function on these channels.[6] Despite its fundamental physiological role, the
molecular mechanism of the closing and opening of KATP channels is
not known yet.A number of KATP channels structures has been
revealed in 2017–2019
by three independent groups using a cryo-EM technique.[7−10] These structural data have opened the door to gaining a better insight
into the mechanism of KATP action.[11] Cryo-EM
confirmed the earlier notion[12] that a KATP
channel is an octamer (Figure a,b,d) and consists of two types of protein subunits: four
Kir6.2 (inward rectifier potassium channel) and four SUR1 (sulfonylurea
receptor).[13] All eight protein subunits
are required to make a fully functional channel.
Figure 1
Structural details of
the KATP models used in this work. (a) Ribbon
representation of two Kir6.2 in one SUR1 system. The disordered region
of KN tail is placed outside the SUR1 cavity (model KS) and is shown as a thick black ribbon. (b) Domain architecture of
the system. Black bold lines denote regions where no clear density
was observed in the cryo-EM outward open structure. (c) The sequence
of the KN tail region, with three N-terminal peptides used in the
tail model building indicated. (d) Top view of the KATP octamer (outward
open). The shaded part represents domains which were not included
in our modeling. The colored part is included in model K (four Kir6.2 proteins) and model KS (four Kir6.2 and
one SUR1 protein). (e) Possible positions of the disordered KN tail
region (red) in model KS and (f) N tail-constrained variants
of model KS named models KNt. A color representation
of domains remains the same throughout the paper.
Structural details of
the KATP models used in this work. (a) Ribbon
representation of two Kir6.2 in one SUR1 system. The disordered region
of KN tail is placed outside the SUR1 cavity (model KS) and is shown as a thick black ribbon. (b) Domain architecture of
the system. Black bold lines denote regions where no clear density
was observed in the cryo-EM outward open structure. (c) The sequence
of the KN tail region, with three N-terminal peptides used in the
tail model building indicated. (d) Top view of the KATP octamer (outward
open). The shaded part represents domains which were not included
in our modeling. The colored part is included in model K (four Kir6.2 proteins) and model KS (four Kir6.2 and
one SUR1 protein). (e) Possible positions of the disordered KN tail
region (red) in model KS and (f) N tail-constrained variants
of model KS named models KNt. A color representation
of domains remains the same throughout the paper.Unfortunately, the structural picture is not yet complete. When
we initiated this project, several important regions of the KATP channel
remained unresolved in the available cryo-EM structures.[7−10] In particular, for the N-terminus of Kir6.2, the 31 amino acid long
fragment (KN tail) was not localized. A lot of experimental data indicate
that this tail is a functionally important part of KATP. The possible
involvement of the Kir6.2 N-terminus in channel gating modulated by
SUR1 was first reported in 1999. Babenko et al.[14] and Koster et al.[15] noticed
that the truncation of the N-terminus of Kir6.2 increases the probability
of the channel opening in ligand-free solution. Riemann et al.[16] have shown that such an effect manifests only
in the presence of SUR1. The KN tail critically affects binding of
antidiabetic drugs. The shortening of the KN tail by as few as five
amino acids reduces the inhibitory effects of SUs.[17,18] How SUR1 affects Kir6.2 is not clear. Lack of knowledge on the whereabouts
of the KN tail seriously hampers our understanding of the KATP gating.Recent (2018) reports from Wu et al.[6,8] and Martin
et al.[18] suggest a possible position of
the KN tail in the complex. The authors hypothesize that this unit,
despite being a disordered polypetide part of the Kir6.2, interacts
with SUR1 and has a critical role in the regulation of KATP conductance.
Difficulties with experimental determination of the KN tail position
are inherent to KATP, since it is a dynamical, signaling part of the
complex. Disordered regions of proteins, for example, N- or C-termini,
often have regulatory roles and currently are subjects of vigorous
research.[19] Should such a disordered tail
play a control role in the Kir6.2/SUR1 system, it would advance our
understanding of an important class of KATP ion channels.Given
these controversies regarding the position of the KN tail,
and the lack of any dynamical studies of KATP models, here we have
used computational modeling methods to gain a better insight into
interactions between Kir6.2 and SUR1, and the role of the KN tail
in the physiology of KATP. We address three questions: (1) What is
the effect of association of the Kir6.2 pore with SUR1 modules on
a pore’s geometry and dynamics? (2) How does the localization
of the disordered KN tail affect the structure of KATP? (3) What are
the local changes in the KATP pore geometry and dynamics induced by
remote interactions of the KN tail with SUR1? Answering these questions
brings a better understanding of the allosteric interactions and heterogeneous
architecture of KATP.As a starting point, we used the inhibitory
mechanism of KATP action
proposed by Wu et al.[8] The following steps
are distinguished in this working model: (1) The Kir6.2 pore is closed
in the ATP bounded state whereas the SUR1 subunits remain in the inward
facing conformation. The KN tail wedges into a large central cavity
formed by the transmembrane domains of SUR1, and this insertion maintains
the SUR1/ABC subunit in the open state. At the same time, restraining
the KN tail prevents the CTD domain of Kir6.2 from rotation (critical
for the pore opening), which results in the KATP inhibition. No potassium
ions are transported. (2) The situation changes when the intracellular
ADP level increases and more MgADP is produced. MgADP binds to NBDs
of SUR1 (see Figure a), which results in a conformational change of SUR1. (3) The central
cavity of SUR1 can no longer accommodate the KN tail, and this release,
by not yet known signal transduction, activates the KATP channel.
Potassium ions leak out of the β cell. (4) Introducing sulfonylureas
to the central cavity of SUR1 inhibits the conformational change induced
by MgADP binding and increases KN tail binding affinity. Thus, SU
drugs promote insulin release.In this work, we focus exclusively
on step 1; therefore, we do
not include any ligands in our modeling. First, we describe how the
presence of SUR1 affects Kir6.2 dynamics and changes the channel pore
(Section IV.1. and KATP gating (Section IV.2)Next, we analyze the role
of the N-terminal part of Kir6.2 in the
KATP channel activity (Section IV.3). Using
computational docking, we predict energetically favorable binding
modes of N-terminal-derived peptides and propose the positioning of
the Kir 6.2 N-terminus within the SU receptor cavity (Section IV.3.1). Finally, using a combination
of steered and targeted MD, we drive the whole system to the conformation
with the KN tail docked into SUR1, and we investigate the behavior
of the systems using all-atom MD (Section IV.3.2).To the best of our knowledge, this is the first MD study
of the
Kir6.2/SUR1 interface and the role of the disordered KN tail fragment
in the nanomechanics of KATP channels. Structural data collected from
the simulations support our hypothesis that the disordered tail is
a major factor in controlling the state of KATP and thus affecting
insulin release from pancreatic β cells. Our data are more general
and of interest to many researchers, since KATPs are involved in the
regulation of neuronal excitability,[20] cardiac
ischemia and stress adaptation,[21] vascular
smooth muscle tone,[22] skeletal muscle fatigue,[23] and hormonal secretion.[24]
Methods
Initial Structures and
Systems Preparation
The fully solvated KATP complex model
has nearly 1 000 000
atoms and is not practical for studies focused on the Kir6.2/SUR1
interface. Therefore, two basic model systems were prepared: model K (i) and model KS (ii) (see Figure ).Model K is limited to
the four main pore-forming units of Kir6.2 based on the human KATP
channel structure (Protein Data Bank ID 6C3P, outward open SUR1 conformation).[7] Model K contains only amino acids
which were already present in this structure (residues 32–353
of four Kir6.2 chains).Model KS is larger,
since it is model K with one SUR1 subunit added (Figure a,e). We wanted to
investigate the humanSUR1 protein in the inward open conformation, but no such data were available. Therefore, the inward
open structure of SUR1 was prepared using the targeted MD (TargMD)
method, by application of external forces to the available human outward
open channel. A template of the inward open conformation was necessary.
We used the Cricetus cricetus channel (PDB ID 6BAA)[10] as the required target to drive NBD domains of the SUR1ABC transporter from the outward to the inward open conformation.
Then, we added one such TargMD prepared inward open humanSUR1 subunit
to the model K and constructed the model KS. Comparisons of these two systems dynamics allowed us to study the
structural impacts of SUR1 on the KATP gating. To study the role of
the KN tail, variants of model KS, described in detail in Supporting Information Table S1, were prepared
as well.During construction of our models
Kir6.2 and SUR1 proteins
were examined for missing side chains and loops using the Schrodinger
software.[25] The structure of both missing
terminal parts of Kir6.2 subunits in model KS were predicted
using the QUARK server.[26,27] Four missing regions
in SUR1 structure were noticed (Figure b, thick black lines). Two of them interact directly
with the Kir6.2 protein: the intercellular loop (ICL1) and L0 loop
(Figure a). Structures
of these loops, as well as the structures of linkers joining the NBD1
domain with TMD1 and TMD2, were predicted using the I-TASSER server.[28−30][26,27]The initial model K and model KS structures were equilibrated during 50 ns MD simulation with implicit
solvent. We used standard parameters (solvent dielectric constant
78.5, ion concentration 0.15 M). The original parts of the protein,
derived from the cryo-EM experiments, were constrained during the
equilibration stage.Models K and KS were embedded into an
explicit palmitoyloleoyl-phosphatidylcholine (POPC) bilayer generated
by the VMD membrane module.[31] The entire
protein–membrane systems were solvated with the TIP3P water
and 150 mM NaCl. The protonation states were assigned with the Epic
algorithm (pH 7.0) in Maestro.[25] Periodic
boundary conditions were used in MD. The model K simulation
box was 110 × 110 × 190 Å3 and consisted
of approximately 150 000 atoms. For model KS,
the size of a simulation box was 190 × 110 × 190 Å3 and involved ∼380 000 atoms. The prepared membrane
embedded systems underwent 100 ns equilibration runs. In Section III.4, we describe details of N tail-constrained
variants of model KS, named for brevity models KNt (Figure f, SI Table S1).
Molecular
Dynamics Protocols
All
MD simulations were performed with the NAMD 2.13 code.[32] Bonds between hydrogens and oxygen atoms were
held rigid only for water molecules (SHAKE algorithms[33]). The 1 fs time step was used. Long-range electrostatic
forces were calculated using the Particle Mesh Ewald method (188 ×
120 × 196 grid points).[34] The simulations
were performed with a constant temperature of 310 K maintained using
Langevin dynamics and a constant pressure of 1 atm (Langevin piston).
The barostat oscillation and damping time scale were set to 200 and
50 fs, respectively. The CHARMM36 force field was used in all the
MD simulations.[35] The VMD code was used
for molecular visualization diagrams.[31]
Peptide Docking as a Tool for Guiding the
Tail
The exact position of the KN tail is not yet known.
To find the key residues which warrant the tail binding, we used automated
ligand docking to model KS. We have identified the individual
energetic contributions of all residues from the glibenclimide binding
SUR1 cavity (further called SU region) to binding energies of different
variants of KN tail pentapeptides. To select such peptides, the first
20 amino acids from the amino terminus of Kir6.2 (chain A) were considered.
On the basis of the KN tail sequence (Figure c), we constructed 21 individual peptides
having a length of five aa each.The Glide tool (Schrodinger
Inc.) was used to prepare grid maps and flexible peptide ligands for
docking.[25] The grid space for the docking
simulation was limited to the region of a putative binding site of
the tail suggested in works by Martin[18] and Wu.[6,8] The searched region covered the two transmembrane
domains and the TMD0 domain of SUR1. Experiments were performed using
a molecular structure with SUR1 protein in the inward open conformation.
For each KN tail peptide, 5000 poses were generated for 10 starting
conformations. The 10 poses with the lowest docking score are shown
in Tables S2 and S3 in SI. Three of them
were chosen as the anchor positions for the KN tail in the TargMD
simulations. In that way, three alternative variants of model KS, named model KNt26, model KNt37, and model KNt48, were further investigated. Additionally,
we performed a set of simulations in which the target position of
the KN tail was based on the N-terminal fragment from the cryo-EM
structure published by Martin et al. (courtesy of Professor Shyng)[18] (model KNtM). Details are described
in SI.
MD Trajectories
Analysis
Prior to
further analysis, the MD trajectories were aligned by the transmembrane
domains of Kir6.2 subunits (residues 70–170) which were not
in direct contact with SUR1.To quantitatively monitor conformational
changes of the KATP channel during simulations, carefully selected
geometrical parameters were calculated using Python scripts and the
MDAnalysis toolkit.[36] The same toolkit
was used to assess the number of hydrogen bonds.[37] Couplings among parts of molecular systems were analyzed
using the dynamic cross-correlation (DCC) matrices.[38,39] In both model K and model KS, cross-correlation
matrices were obtained by averaging data for one selected Kir6.2 subunit
from three simulation runs.
Results
and Discussion
The KATP channel is the octameric complex,
and the role of SUR1
in regulation of potassium ion transport through its Kir pore is of
great interest. We present and discuss the results of the MD simulations,
focusing ongeneral effects of SUR1 on Kir6.2
dynamics (IV.1),modulation
of the KATP gating by
SUR1 (IV.2), anda functional role of conserved,
disordered KN tail in KATP structure control (IV.3).
How the Presence of SUR1 Affects Dynamics
of Kir6.2 Subunits?
The presence of the TMD0 domain of SUR1
is indispensable for the activity of Kir6.2 pore. SUR1 proteins were
therefore called “gatekeepers”.[40] As a reference for further comparisons, we run three 100 ns long
unbiased simulations of an isolated pore, formed solely by four Kir6.2
subunits, embedded in a membrane and an appropriate water box (model K). All subunits exhibited similar dynamics, after 30 ns the
RMSD stabilizes at the level of around 4 Å with respect to the
original structure (see SI Table S2).Root-mean-square fluctuations (RMSF) of residues from individual
Kir6.2 modules are presented in Figure a.
Figure 2
RMSF of a single Kir6.2 chain. (a) Three 100 ns simulations
of
model K (each consists of four Kir6.2 subunits, so 12
data sets are averaged). Three 100 ns simulations of model KS (gray scale) compared to the averaged RMSF of model K (cyan) (b) for Kir6.2 chain having no direct contact with SUR1 and
(c) for the Kir6.2 subunit with a direct contact with SUR1. Red triangles
and yellow stars denote residues participating in ATP and PIP2 binding, respectively. Black dots refer to residues directly
interacting with SUR1. Dashed rectangles denote regions in which SUR1
affects fluctuations on Kir6.2 amino acids.
RMSF of a single Kir6.2 chain. (a) Three 100 ns simulations
of
model K (each consists of four Kir6.2 subunits, so 12
data sets are averaged). Three 100 ns simulations of model KS (gray scale) compared to the averaged RMSF of model K (cyan) (b) for Kir6.2 chain having no direct contact with SUR1 and
(c) for the Kir6.2 subunit with a direct contact with SUR1. Red triangles
and yellow stars denote residues participating in ATP and PIP2 binding, respectively. Black dots refer to residues directly
interacting with SUR1. Dashed rectangles denote regions in which SUR1
affects fluctuations on Kir6.2 amino acids.One can see that TM helical regions are quite stable, and only
the Turret loop (100–110) and the extracellular loop (ECL)
located next to the selectivity filter (SF) (140–150) exhibit
increased flexibility. The cytoplasmic CTD region (170–350)
is more prone to deformations, with high mobility in 180–200,
220–230, and 252–280 areas. These areas contain flexible
loops joining parts of CTD β sheets. Two such linker regions
are associated with intradomain interactions (a salt bridge between
R192 and E229 from adjacent Kir6.2 subunits) contributing to the stability
of CTD. Elevated values of RMSF at 350 region (Figure ) are natural, since this part of our models
represents the 30 AA long C-term which is perhaps disordered, and
therefore absent in the cryo-EM structures.The model K is extended to model KS by
having one extra SUR1 module added (see Figure d, model KS). We assessed the
possible effects of the SUR1 presence on Kir6.2 dynamics by examining
three 100 ns MD simulations of model KS. The RMS data
indicate that the equilibrium was achieved after 30 ns of the simulation
time. The RMSF data for model KS are presented in Figure b,c. In panel b,
we show data for three Kir6.2 modules localized opposite to SUR1 and
having no direct contact with this protein and in panel c for three
Kir6.2 subdomains in contact with SUR1. On the basis of PDB 6BAA (inward open) and
6C3P (outward open) structures, we identified contact regions between
Kir6.2 and SUR1. The interface residues are marked by black circles
in Figure c. Detailed
data are presented in Figure S3 (SI). We
monitored dynamics of these interfaces during SUR1 association with
Kir6.2 and enforced binding of the KN tail into the SU pocket (vide
infra).The main piece of information shown in Figure is that Kir6.2 residues from
the membrane
embedded part (green bars in Figure a), including the interface region, are rather insensitive
to the presence of the SUR1 protein. Differences in their dynamics
(Figure b,c), measured
by fluctuations, are localized in the loop regions and are within
statistical errors.Interestingly, the only two exceptions showing
the clear sensitivity
to the SUR1 presence are (i) the area near the 48–50 region
which corresponds to the ATP binding site and (ii) the selectivity
filter region 130–134. Thus, we conclude that SUR1 is perhaps
mechanically coupled to the Kir6.2ATP binding site and has a stabilizing
role for this region. The presence of SUR1 increases also fluctuations
in the SF region of the adjacent Kir6.2 subunit. MD simulations indicate
a small stabilizing effect of SUR1 on the PIP2 binding region, located
in the vicinity of R54, K67, R176, R177, R206, R301 (see Figure S5).Correlations of residues in
model K and model KS help to pinpoint the
possible remote effects of Kir6.2–SUR1
interactions on the KATP pore dynamics. Cross-correlation matrices
calculated for Cα atoms of Kir6.2 residues in models K and KS are presented in Figure a,b. The difference in cross-correlations
between these two models is presented in Figure c.
Figure 3
Cross-correlation matrices calculated for Cα
atoms of Kir6.2
residues in (a) model K and (b) model KS. (c) The difference in cross-correlations between these two models.
Cross-correlation matrices calculated for Cα
atoms of Kir6.2
residues in (a) model K and (b) model KS. (c) The difference in cross-correlations between these two models.The presence of SUR1 (model KS) clearly
affects the
motion of the N-ter part already resolved in cryo-EM structures. Due
to interactions with the SUR1 protein, a much longer region of N-ter
(47 amino acids in model KS vs 14 amino acids in model KS) is correlated with the CTD domain motions. A pattern of
internal correlations/anticorrelations in the N-ter (the first 30
AA, Figure a,b) also
changes upon SUR1 binding. Initially, there are relatively strong
internal correlations within the large CTD fragment, which are attenuated
by the SUR1 presence. We noticed also that SUR1 enhances interdomain
correlations between CTDs located in the adjacent Kir6.2 subunits.The TM helix M1 has a direct contact with the TMD0 domain of SUR1
(Figure a). We observed
that M1/M2 motions change upon SUR1 attachment, and they become more
correlated if SUR1 is present. Indeed, detailed analysis of M1–M2
distances showed that these helices are in closer contact in model KS than in model K (see Section IV.2.2). Also, correlations of the N-ter with M1 substantially
increase when SUR1 interacts with Kir6.2. The M1/SF regions, being
correlated with the CTD domain in model K, upon SUR1
binding, become anticorrelated (see Figure b,c). We studied also cross-correlation
matrices in the regions attributed to gating. The G-loop gate (295–296),
the HBC gate (164–168), and the SF (130–134) regions
do not exhibit interesting features in correlation matrices. We conclude
that motions of these classical gating regions are not substantially
affected by SUR1, at least on a short, 100 ns time scale.Thus,
based on the cross-correlation matrices analysis, we infer
that the presence of SUR1 affects mainly cytoplasmic regions of the
Kir6.2 moiety. In particular, the N-ter is affected. The dynamics
of the direct interface between Kir6.2 and TMD0 of SUR1 is only slightly
modified in the M1 region by the association between these two subunits.
No clear signal transduction between SUR1 and Kir6.2 in the transmembrane
region, especially related to helix–helix interaction, was
found in our trajectories. This observation is consistent with the
fact that only a fraction of mutations affecting insulin release were
found in the Kir/SUR1 hydrophobic interface. The mutations W91R and
P45L in Kir6.2 and SUR1, respectively, prevent the correct formation
of the whole KATP system.[41,42]
How
Does Association with SUR1 Affect KATP
Gating?
There are numerous experimental observations that
SUR1 affects KATP gating. At least two mechanisms may be involved:
(1) direct interactions with Kir6.2 regions considered to be gates,
and (2) modulation of ATP/ADP/PIP2 ligand binding affinity. Here,
we focus on computational analysis of group 1 factors since we work
with apo models of KATP. Calculation of the average water flux through
the gating regions for all models indicates that the presence of only
one SUR1 subunit (model KS and models KNt) significantly reduces permeation of water molecules through the
pore (Figure d).
On the basis of this observation, we infer that potassium ion conductance
will be affected as well.
Figure 4
KATP channel gating. (a) Water occupancy along
the pore during
an example simulation run; every blue dot represents a single water
molecule in the pore cavity. Right: average water occupancy per 1
Å slice along the pore axis for model K (cyan) and
model KS (black). (b) Pair of Kir6.2 subunits forming
the gate region in two crystal structures (inward open 6BAA and outward
open 6C3P). Pore residues directly interacting with SUR1 are in red,
and residues responsible for gating are shown in yellow. Volumes representing
the diameter of the pore were calculated using HOLE: wide areas of
the pore (pore radius >2.3 Å) are blue, water accessible parts
(1.15 Å > pore radius < 2.30 Å) are green, and parts
that are inaccessible to water (pore radius <1.15 Å) are red.
(c) Comparison of the HOLE profiles of the pore radius of inward open
6BAA (red) and outward open 6C3P (green).[43] (d) Average water flux per 1 ns of simulation for four gating regions
calculated for all models: model K (cyan), model KS (black), model KNt26 (green), model KNt37 (yellow), model KNt48 (blue), and model KNtM (magenta).
KATP channel gating. (a) Water occupancy along
the pore during
an example simulation run; every blue dot represents a single water
molecule in the pore cavity. Right: average water occupancy per 1
Å slice along the pore axis for model K (cyan) and
model KS (black). (b) Pair of Kir6.2 subunits forming
the gate region in two crystal structures (inward open 6BAA and outward
open 6C3P). Pore residues directly interacting with SUR1 are in red,
and residues responsible for gating are shown in yellow. Volumes representing
the diameter of the pore were calculated using HOLE: wide areas of
the pore (pore radius >2.3 Å) are blue, water accessible parts
(1.15 Å > pore radius < 2.30 Å) are green, and parts
that are inaccessible to water (pore radius <1.15 Å) are red.
(c) Comparison of the HOLE profiles of the pore radius of inward open
6BAA (red) and outward open 6C3P (green).[43] (d) Average water flux per 1 ns of simulation for four gating regions
calculated for all models: model K (cyan), model KS (black), model KNt26 (green), model KNt37 (yellow), model KNt48 (blue), and model KNtM (magenta).The detailed mechanism
in which the KATP pore alternates between
the conducting state and nonconducting one has not been determined
yet. Nevertheless, the Kir6.2 channels share several characteristic
structural features controlling the flux of K+ ions along
their electrochemical gradient (see Figure b,c):G-loop gate (CTD domain, close to
the inner membrane),helix bundle crossing gate (HBC),
andselectivity filter
(close to the outer
membrane).Next, we discuss how SUR1
modulates regions a–c using our
MD results.
G-Loop Gate
G-loop is a region
at the apex of the cytoplasmic domain (residues 295–296) (see Figures a and 4b). Crystallographic and functional studies of other members
of the Kir channels family suggest the gating role of this region.[44−47] A mutation within the loop region I296L causes a significant decrease
in ATP inhibition and gives rise to DEND syndrome (neonatal diabetes
in association with developmental delay, epilepsy, or muscle weakness).[48] All available cryo-EM structures of Kir6.2 determine
the closed conformation of the channel, with the G-loop diameter ranging
from 10.7 to 12.8 Å for the outward open 6C3P structure[9] and 5YKG (“relaxed” state of Kir6.2),[8] respectively. Computational studies of the Kir3.2
channel gating performed by Bernsteiner at al.[47] indicated that the gate diameter, calculated as the distance
between the centers of mass of the G-loop gate-forming residues G318
and M319 from the opposite Kir subunits, varies from ∼3 to
11 Å during the simulations, with the narrowest diameter allowing
K+ ion permeation to be 5.9 Å. They observe also that
the G-loop is remarkably narrower than the HBC gate during MD simulations.
Considered here, the Kir6.2 channels have methionine replaced with
isoleucine in the G-loop region. The diameter of the gate in our simulations
varies from 5.9 to 17 Å. The average distance between opposite
subunits oscillates around 10 Å for a narrower pair and around
14 Å for a most distant pair. Considering a 4-fold symmetry of
the channel, despite its closed conformation, both pairs exhibit the
G-loop gate configuration allowing the passage of hydrated K+ ions. Neither the presence of SUR1 nor a change in the position
of the KN tail affects the dynamics of this gate (see SI Figure S4). This finding supports a hypothesis
that this region might be important for KATP functioning, but the
gate itself does not produce any significant steric obstacles for
ion permeation, even in the closed channel conformation. Notably,
mutations in this regions affect the proper physiology of β
cells.[49]
HBC
Gate and Changes in the Dynamical
Properties of the Pore
In many K+ channels, the
helix bundle crossing is assumed to be a gate which physically opens
and closes in response to a variety of stimuli.[50] The HBC region contains hydrophobic, pore facing residues
F168 and L164, which form the narrowest part of the channel (see Figure a–c). The
diameter of the gate (calculated as the minimal distance between pore
occluding F168 residues) varies from 3.11 to 7.15 Å in MD simulations.
It results in the average of 4.4 Å for all of our models, except
one simulation run for model K, in which just one pair
of the residues stays further apart (∼13 Å). A comparison
of these diameters with those present in cryo-EM structures (from
5.36 to 7.1 Å) confirms that all our MD models remain in the
closed state.HBC is localized in the vicinity of the interface
between Kir6.2 and SUR1. Therefore, we analyzed how SUR1 changes the
conformation and dynamics of the surroundings of this gate. It is
worth noting that several gain-of-function mutations in the HBC area
were reported. They lead to neonatal diabetes (L170R/N/T and V64L)[51,52] or to the DEND syndrome (C166Y/F and I167L).[53−55] This supports
our pursuit to look for the Kir6.2/SUR1 communication in this particular
region.In model KS, we observe a different pattern
of H-bonds
in comparison with model K. In model KS,
the newly formed hydrogen bonds join L170 (M2), T71 (M1), and D65
(Slide helix) providing the direct connection with the intercellular
loop of SUR1 (IL1) (see Figure b,d).The distance between Cα atoms of residues F168
and D65 (Figure c,
lower panel) is lower in model KS with respect to model K.
Figure 5
Influence of SUR1 on the HBC gate. (a) Distortion of 2-fold symmetry
of Kir6.2 upon one SUR1 binding: initial structure (left) and final
structure (right). Cα atoms of residues forming the HBC gate
(F168 and L164) are shown as black dots. (b) Hydrogen bonds formed
in the presence of SUR1. (c) The time evolution of the distances between
the Cα atom of F168 and the axis of the pore (upper panel) and
between Cα atoms of F168 and D65 from the slide helix (lower
panel). (d) The probability of hydrogen bond formation. As in Figure , data related to
model K is shown in cyan, that for model KS is in black, and the gray color denotes the chain of Kir6.2 in model KS which does not interact directly with SUR1.
Influence of SUR1 on the HBC gate. (a) Distortion of 2-fold symmetry
of Kir6.2 upon one SUR1 binding: initial structure (left) and final
structure (right). Cα atoms of residues forming the HBC gate
(F168 and L164) are shown as black dots. (b) Hydrogen bonds formed
in the presence of SUR1. (c) The time evolution of the distances between
the Cα atom of F168 and the axis of the pore (upper panel) and
between Cα atoms of F168 and D65 from the slide helix (lower
panel). (d) The probability of hydrogen bond formation. As in Figure , data related to
model K is shown in cyan, that for model KS is in black, and the gray color denotes the chain of Kir6.2 in model KS which does not interact directly with SUR1.The presence of one SUR1 protein distorts the 2-fold symmetry
of
the channel in the HBC region by pulling two (out of four) opposite
M2 chains of Kir6.2 toward SUR1 (see Figure a). As a result, the distance between the
Cα atom of the F168 residue and the axis of the pore slightly
increases in model KS (Figure c, upper panel), whereas the pairwise distance
between Cα atoms remains nearly the same in all models. One
can expect that adding three more SUR1 proteins to the simplified model KS (as in the available cryo-EM structures) will cause
a widening of a pore with a magnitude around 1 Å, which might
facilitate opening of the pore. This is in agreement with the increased P0 probability of the Kir6.2-SUR1 channels compared
to those made by Kir6.2 alone.[56]
How Does the Association with SUR1 Affect
Kir6.2 Selectivity Filter?
A selectivity filter (SF) is a
common feature in ion channels.[57] In KATP,
it is composed of TIGFG (residues 130–134) and is located in
the outer membrane part of the KATP pore (Figure a). The proper functioning of SF is critical
to channel function. Each Kir6.2 subunit has two transmembrane helices
M1 and M2 separated by a pore-loop that contains a characteristic
GFG motif (G132–F133–G134 here) and an important E126–R136
salt bridge which stabilizes the SF region. The SF is linked directly
to the pore-helix (S116–V129) (see Figure c). McCoy proposed several interactions within
SF which might be crucial for its stability.[57] We checked how the presence of SUR1 affects these interactions.
Figure 6
Histograms
showing the differences in the SF region dynamics between
model K (cyan) and model KS (black): (a)
the pore-helix rotation, (b) the distances between Cα atoms
of the opposite SF residues, and (c) cartoon diagrams depicting interactions
within the selectivity filters and surrounding. Selectivity filter
residue carbon atoms are yellow, and calculated bonds are shown as
dashed black lines. (d) The dihedral angle ψ of F133, (e) the
distance of the hydrogen bond forming residues E126 and I131, and
(f) the distance between the salt bridge forming residues E126 and
R136.
Histograms
showing the differences in the SF region dynamics between
model K (cyan) and model KS (black): (a)
the pore-helix rotation, (b) the distances between Cα atoms
of the opposite SF residues, and (c) cartoon diagrams depicting interactions
within the selectivity filters and surrounding. Selectivity filter
residue carbon atoms are yellow, and calculated bonds are shown as
dashed black lines. (d) The dihedral angle ψ of F133, (e) the
distance of the hydrogen bond forming residues E126 and I131, and
(f) the distance between the salt bridge forming residues E126 and
R136.From the aggregated MD data, we
constructed histograms of parameters
used to monitor an impact of the association between SUR1 and Kir6.2
on the SF structure. In Figure a, we show that in the absence of SUR1 (model K) the inclination of the pore-helix relative to the pore axis (θ, Figure c) varies with a
magnitude of 7°. Binding one SUR1 protein to the Kir6.2 tetramer
(model KS) restrains such movement to a much narrower
distribution, and it shifts the mean value back to those measured
in the experimental structures (θ = 47.4° and θ =
48° for inward open and outward open structure, respectively).
The SF is linked to the pore-helix, and its structure is also affected
by the presence of SUR1. Distances between opposing Cα atoms
of SF forming residues are shown in Figure b. While distances calculated for model KS show a single narrow distribution, those calculated for
model K show much higher variability.[50]Additionally, we calculated histograms of distances between
two critical pairs of residues in the SF region (Figure e,f) and dihedral ψ angles
of residue F133 (Figure d). The distribution of distances between E126–I132 is narrower
in model KS than that calculated for model K. This means that SUR1 stabilizes the geometry of the SF region.
The fact that carbonyl-oxygen flips of F133 are not observed in model KS (Figure d) also corroborates this hypothesis. The stabilization of the SF
region is further supported by the data shown in Figure f. The E126–R136 salt
bridge is crucial for proper functioning of SF. It was present practically
all the time during model KS simulations, while in the
model K case a wide distribution of E126–R136
distances indicates only a transient character of this link. This
salt bridge is physiologically important since mutations of R136 lead
to serious dysfunction of KATP.[42]Proks et al.[58] distinguished slow and
fast gating of KATP. The authors linked conformational changes in
SF to the fast gating. Our MD data confirm that remote interactions
with SUR1 do affect the SF region. However, the perturbation we studied
here is quite large (on/off type). What the effects are of subtle
conformational changes in SUR1 itself, for example, upon KN tail or
drug binding to the SU region, on fast gating is still an open question.
Perhaps SF may be controlled indirectly by changes in CTD as well,
as suggested by Clarke et al.[59] These hypotheses
require more extensive MD simulations.
Association
of Kir6.2 Complex with SUR1
Affects Position and Orientation of CTD Domain
The cytoplasmic
domain of Kir6.2 (CTD, Figure a) and the SF are considered to be major factors controlling
Kir6.2 gating.[59] All components of the
KATP channel (ATP binding site, PIP2 binding site, KN tail orientation,
a contact with SUR1 governed by open/close orientation of SUR1) affect
the CTD domain. Additionally, the relative position of CTD with respect
to the transmembrane part of the channel is different in “activated”
and “inactivated” states of KATP.Numerous mutations
changing the KATP function were found in this region.[5] Those mutations affect both binding sites of ligands and
the proper intersubunit communication. For example, the disruption
of intersubunit salt bridges (R192–E229, R301–E292,
and R314–E229) at the interface of CTDs induces a loss of the
channel activity.[60,61]To check what structural
transformations of CTD are induced solely
by the contacts between SUR1 and Kir6.2, we compared the dynamics
of CTD domains in model K and model KS.
We have monitored the position along the z-axis (Figure c) and the orientation
(angle β, Figure a,b) of the CTD domain with respect to the axis of the KATP channel,
as well as the stability of salt bridges R192–E229′,
and R301–E292′ (Figure d,e).
Figure 7
Dynamics of the CTD domain. (a) Ribbon diagram of Kir6.2
tetramer
showing interdomain interactions of CTD. (b) An angle β between
CTD and the pore axis. (c) Position of the center of mass of CTD along
the pore axis for model K (cyan) and model KS. Gray color states for the Kir6.2 chain without direct contact with
SUR1 in model KS. (d, e) The closest distance between
the residues forming salt bridges.
Dynamics of the CTD domain. (a) Ribbon diagram of Kir6.2
tetramer
showing interdomain interactions of CTD. (b) An angle β between
CTD and the pore axis. (c) Position of the center of mass of CTD along
the pore axis for model K (cyan) and model KS. Gray color states for the Kir6.2 chain without direct contact with
SUR1 in model KS. (d, e) The closest distance between
the residues forming salt bridges.The close proximity of a large SUR1ABC transporter in model KS affects the orientation of CTD substantially. The center
of mass of the CTD domain upon contact with SUR1 is shifted upward
(closer to the membrane) by 4 Å with respect to the coordinates
of the opposite Kir6.2 module separated from SUR1. This shift is also
noticeable (2 Å) with respect to the positions of CTD domains
in model K (Figure c). At the same time, a rotation (from 35° to
50°) of the whole CTD domain induced by interactions with SUR1
is observed (Figure b). Thus, the presence of SUR1 in the open conformation clearly brings
the whole Kir6.2 structure closer to the activated state. Additionally,
we observe that only in the presence of SUR1 are two important “cavities”
serving as the biding sites for ATP and PIP2 properly formed (see SI).
How
Does the Localization of a Disordered
KN Tail of Kir6.2 Affect KATP Function?
During evolution,
protein sequences change in time due to random mutations and deletions.
This alters their physicochemical properties and structural characteristics.
Parts of proteins that are maintained by the natural selection often
have an important biological function which is therefore protected.The presence of a long and disordered N-terminal part is a common
feature of Kir6 channels, and its activity might warrant proper Kir6.2-SUR1
coupling and molecular signal transduction.[6,8,18] In known organisms having functional KATP
channels (chordates), both the sequence and the length of the KN tail
are highly conserved. In comparison, the level of conservation of
the C-terminus in those channels is very low.A localization
of a disordered KN tail in the known cryo-EM structures
of KATP is a matter of debate.[6,8,18,62] Importantly, there is no open
conformation of the SUR1 part of human KATP channels determined yet.
In order to determine possible binding modes of the KN tail to the
SU region in SUR1, we generated, using SMD and TargMD protocols, a
new, structural homology based, structure of the open form of humanSUR1 (see Methods section and SI). The SU region is important for binding antidiabetic
drugs that keep the KATP channel closed.[6,18,63]
Docking Studies Reveal
Possible KN Tail
Binding Modes to the SU Binding Region
The KN tail is disordered
and has no defined secondary structure, but it apparently participates
in KATP closing and opening. Wu et al.[8] hypothesize that binding of the KN tail to open the SUR1 protein
transiently locks the KATP channel. Only very recently has a putative
position of the KN tail been proposed on the basis of cryo-EM data.[18] We asked a question regarding whether there
is any “preferable” way for the binding of the KN tail
into the SU binding region. We docked all tail-derived consecutive
pentapeptides to our open form of humanSUR1 (results are shown in SI Table 2).Only three pentapeptides,
representing the first part of the KN tail, were successfully docked
into the SU pocket. All the other 18 peptides docked in remote places
of SUR1. The docking scores of pentapeptides immersed in the SU site
were similar (KNt37, −7.8 kcal/mol; KNt48, −7.0 kcal/mol; KNt26, −6.5 kcal/mol).
Only those three structures were considered to be promising starting
points for further MD simulations. The interactions of the KN tail
end with the SUR1SU pocket are shown in Figure a–g.
Figure 8
Docking of pentapeptides to the SUR1 cavity.
(a) General view of
the SUR1 structure with the KN tail peptide shown in black and the
approximate binding position of GBM[63] shown
as a pink volume. (b–d) KNt26, KNt37, and KNt48 pentapetide binding position in a top view,
and (e–g) side view, with the main residues forming the binding
spaces shown in a cyan (TMD1) and orange (TMD2) stick representation.
Docking of pentapeptides to the SUR1 cavity.
(a) General view of
the SUR1 structure with the KN tail peptide shown in black and the
approximate binding position of GBM[63] shown
as a pink volume. (b–d) KNt26, KNt37, and KNt48 pentapetide binding position in a top view,
and (e–g) side view, with the main residues forming the binding
spaces shown in a cyan (TMD1) and orange (TMD2) stick representation.We monitored a number of hydrogen bonds between
the KN tail and
Kir (and SUR1) protein moieties during enforced docking of the tail.
We found that the diffusion of the tail on the surface does not change
that number much; it oscillates around 6. The number of H-bonds between
the tail and SUR1 increases from 1 to 5 during this process.Our data indicate that all three configurations of the tail ending
are plausible. However, the best (in terms of energy) docking pose
was observed for the KNt37 model. This indicates that
the tail penetrates the SU pocket in the open form of SUR1. Obviously,
the tail blocks a fast return of SUR1 to the closed form and regulates
KATP conductivity.
How Does the Tail Localization
Affect
Kir6.2 and SUR1 Structure/Dynamic?
One may expect that the
exact embedding of the KN tail in the SU pocket modifies Kir6.2 dynamics.
We monitored RMSF of Kir6.2 residues during simulations. We did not
notice any substantial changes in the Kir6.2 RMSF patterns (SI, Figure S1ab). More interesting effects were
observed in the SUR1 RMSF data (Figure ).
Figure 9
Impact of the KN tail embedding mode into the SU region
on the
SUR1 dynamics. RMSF of SUR1 are calculated for five models: KNt26 (green), KNt37 (yellow), KNt48 (blue), and KNtM (magenta) and compared to KS (black) shown in each panel.
Impact of the KN tail embedding mode into the SU region
on the
SUR1 dynamics. RMSF of SUR1 are calculated for five models: KNt26 (green), KNt37 (yellow), KNt48 (blue), and KNtM (magenta) and compared to KS (black) shown in each panel.Two main observations from SUR1 RMSF data are the following: (1)
In the SU region (residues no. ∼500 and ∼1100), higher
fluctuations are noted, induced by the KN tail presence. (2) The NBD2
domain is much more delocalized by a rigid motion during MD than the
NBD1 unit. That means that NBD2 domain dynamics is indeed affected
by the presence of an NKt tail docked in the SU region. More data
on KN mechanics and interactions with SUR1 residues may be found in
the SI.The general effect of KN
tail docking on SUR1 is presented in Figure a–c. The
presence of the tail, as expected, stabilized SUR1 in the open form.
The size of the SU region in the open SUR1 is bigger that in the closed
one (Figure c).
The size of the SU region allows for multiple binding modes of the
KN tail; we found that at least three modes (KNt26, KNt37, KNt48, and KNtM) are possible.
Notably, the distances between NBD domains depend on the KN tail positions
(Figure b) ranging
from ∼34 Å for model KS to above 50 Å
in model KNt26. Values of NDB separations measured for
cryo-EM structures vary from 28.6 Å, for the structure of SUR1
in the outward open form, to 41.3–44.1 Å for SUR1 in the
inward open form.[9,10]
Figure 10
Structural changes in SUR1 upon KN tail
binding. (a) General view
of SUR1, (b) bottom view of NBD domains, (c) bottom view of TMD domains
showing the SU/tail binding cavity for model KNt26 (left),
model KS (middle), and preopen state of model KS (right).
Figure 11
Disordered KN tail embedding mode (models KNt) into
the SU region in SUR1 affects dynamics of KATP: (a) slide helix rotation,
(b) distance between NBD1 and NBD2, and (c) distance between interdomain
salt bridge forming residues D58 and R206′. Colors denote KNt models; data for model KS are shown in black.
Structural changes in SUR1 upon KN tail
binding. (a) General view
of SUR1, (b) bottom view of NBD domains, (c) bottom view of TMD domains
showing the SU/tail binding cavity for model KNt26 (left),
model KS (middle), and preopen state of model KS (right).Disordered KN tail embedding mode (models KNt) into
the SU region in SUR1 affects dynamics of KATP: (a) slide helix rotation,
(b) distance between NBD1 and NBD2, and (c) distance between interdomain
salt bridge forming residues D58 and R206′. Colors denote KNt models; data for model KS are shown in black.Rotation of the slide helix (AA 55–65) is
affected by the
docking of the KN tail to the SU region. This is one of the most important
findings of this study. The slide helix amino acids participate in
formation of the PIP2 binding site and the ATP binding site. Moreover,
this helix interacts directly with the HBC gate in the Kir6.2 pore
(Figure b,c). The
MD data presented in Figure a show that the slide helix orientation is sensitive to the
presence of SUR1 and the specific orientation of the KN tail. Once
the tail is docked into the SU pocket, the slide helix rotates by
some 10°.We also found that potentially important interdomain
CTD-CTD′
salt bridge D58–R206′ is strongly affected by the KN
tail localization (Figurec). In the absence of the localized tail, the salt bridge
is sometimes broken, but when the tail is captured in the SU pocket,
as in model KNt37 and model KNtM, the presence
of the bridge is much more probable. Thus, we infer that that interdomain
D58–R206′ salt bridge is an important component of the
allosteric regulation of KATP. In the real KATP systems, a chain of
such salt bridges couples together all CTD domains. Notably, the slide
helix mutations heavily affect the KATP functioning.[3,5]
Conclusions
The
recent discovery of relatively high resolution cryo-EM structures
of KATP channels[7−10,18] provided an excellent basis for
computer modeling of possible allosteric regulations involved in the
insulin release pathway and other physiological processes. We used
the targeted MD approach to construct simplified models of Kir6.2
coupled with an open form of the humanSUR1 protein. We focused on
the postulated physiological role of the well-conserved, structurally
disordered KN tail of the Kir6.2 subunit possibly interacting with
the adjacent SUR1. Presumably this tail “sneaks in”
into the sulfonylurea drug binding region of SUR1. Using molecular
docking, we determined preferred conformations of all (21) pentapeptides
derived from the KN tail in that SU region. Modeling indicates that
only 3 pentapetides (KNt26, KNt37, KNt48) effectively come into stable interactions with SUR1.We systematically compared the dynamics of the Kir6.2 pore model
having 4 bare subunits (model K) with a bigger system
(model KS) having just one full SUR1 unit in the inward
open conformation attached to model K. The MD results
reveal a number of conformational changes induced in the generic model K by the interactions with SUR1. Major conformational effects
observed already on the 100 ns time scale include the following: (1)
The HBC gate of Kir6.2 has closer distances between the M1 and M2
helices due to the interaction with SUR1. This effect may modulate
the K+ ion transfer rate. (2) SUR1 limits rotations in
the pore-helix which in turn provides stabilization of SF. (3) The
SUR1 presence favors the activated KATP state versus the inactivated
one by bringing the TMD domain closer to the cell membrane. On the
basis of the present modeling, we may conclude that the disordered
KN tail is a major factor in controlling KATP function. It keeps SUR1
in the open form and is able to limit rotation of the CTD domain.
This underlines the role of the conserved, disordered protein tail
in the molecular pathway controlling insulin release from pancreatic
β cells.Observations from dynamical modeling of our potassium
channel models
provide, perhaps for the first time, the basis and a starting point
for further exploration and explanation of the structural mechanisms
and allosteric regulation of the KATP systems. The local interactions,
revealed in the present MD analysis, may be experimentally tested.
The simulations of more extended KATP models, i.e., having ATP/MgADP/SU
ligands, are under way in our laboratory.
Authors: Leonid V Zingman; Denice M Hodgson; Peter H Bast; Garvan C Kane; Carmen Perez-Terzic; Richard J Gumina; Darko Pucar; Martin Bienengraeber; Petras P Dzeja; Takashi Miki; Susumu Seino; Alexey E Alekseev; Andre Terzic Journal: Proc Natl Acad Sci U S A Date: 2002-09-23 Impact factor: 11.205
Authors: Anna L Gloyn; Ewan R Pearson; Jennifer F Antcliff; Peter Proks; G Jan Bruining; Annabelle S Slingerland; Neville Howard; Shubha Srinivasan; José M C L Silva; Janne Molnes; Emma L Edghill; Timothy M Frayling; I Karen Temple; Deborah Mackay; Julian P H Shield; Zdenek Sumnik; Adrian van Rhijn; Jerry K H Wales; Penelope Clark; Shaun Gorman; Javier Aisenberg; Sian Ellard; Pål R Njølstad; Frances M Ashcroft; Andrew T Hattersley Journal: N Engl J Med Date: 2004-04-29 Impact factor: 91.245
Authors: K Shimomura; F Hörster; H de Wet; S E Flanagan; S Ellard; A T Hattersley; N I Wolf; F Ashcroft; F Ebinger Journal: Neurology Date: 2007-07-25 Impact factor: 9.910