Mechanistic insights into the Orai channel by molecular dynamics simulations

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Review

Mechanistic insights into the Orai channel by molecular dynamics simulations ⁎

Daniel Bonhenrya, , Romana Schoberb, Tony Schmidtc, Linda Waldherrc, Rüdiger H. Ettricha,d, ⁎ Rainer Schindlc, a

Center for Nanobiology and Structural Biology, Institute of Microbiology, Academy of Sciences of the Czech Republic, Nové Hrady CZ-373 33, Czech Republic Institute for Biophysics, Johannes Kepler University Linz, A-4040 Linz, Austria c Gottfried Schatz Research Center, Medical University of Graz, A-8010 Graz, Austria d College of Biomedical Sciences, Larkin University, Miami, FL 33169, United States b

A R T I C LE I N FO

A B S T R A C T

Keywords: Molecular dynamics MD-simulations Orai Orai1 Calcium Pore Gating STIM

Highly Ca2+ selective channels trigger a large variety of cellular signaling processes in both excitable and nonexcitable cells. Among these channels, the Orai channel is unique in its activation mechanism and its structure. It mediates Ca2+ influx into the cytosol with an extremely small unitary conductance over longer time-scales, ranging from minutes up to several hours. Its activation is regulated by the Ca2+ content of the endoplasmic reticulum (ER). Depletion of luminal [Ca2+]ER is sensed by the STIM1 single transmembrane protein that directly binds and gates the Orai1 channel. Orai mediated Ca2+ influx increases cytosolic Ca2+ from 100 nM up to low micromolar range close to the pore and thereby forms Ca2+ microdomains. Hence, these features of the Orai channel can trigger long-term signaling processes without affecting the overall Ca2+ content of a single living cell. Here we focus on the architecture and dynamic conformational changes within the Orai channel. This review summarizes current achievements of molecular dynamics simulations in combination with live cell recordings to address gating and permeation of the Orai channel with molecular precision.

1. An introduction to molecular dynamics

→ Fi = mi → ai

Molecular dynamics (MD) is a computational method which aims at solving numerically Newton’s equations of motion for each particle in the system. The outcome of a simulation is called a trajectory where the positions and velocities of the particles simulated are stored at constant progressive time-step intervals. This trajectory corresponds to sampling of the phase space of the system and, therefore, thermodynamic quantities may be calculated. Only a short introduction to molecular dynamics will be given here as the interested reader will find a more immersing view of the theory and the implementation behind it in various available textbooks [1–5]. Although Newton derived his equations to study the motion of celestial bodies, MD is a well-fitted method in order to simulate the behavior of matter at a molecular level, as long as quantum effects do not overcome classical thermal energy effects. The fundamental aspect behind molecular dynamics simulations is to represent each atom or set of atoms by a particle. For each of these particles present in the system, the following equation is being solved:

Where i applies for the i-th particles in the system (0 < i < N, N being the total number of particles). Fi represents the sum of the forces acting upon i and mi its mass. With the acceleration ai, being the second derivative of the position with respect to time, Newton’s equations can be rewritten as a set of differential equations:

⁎

→ d 2→ ri = Fi dt 2 → Herein, r is the Cartesian position vector of the particle in space and time. In the absence of external forces, the particles will be either at rest or will have a uniform motion. Forces are introduced into the system by being derived from a force field. This contains all the parameters relative to the bonded and nonbonded interactions required to describe the molecules and particles within the system. For a deeper approach related to force field implementation and parametrization, the reader may find satisfaction to its curiosity in more dedicated works [6–8] Bonded interactions between atoms are usually represented by

mi

Corresponding authors. E-mail addresses: [email protected] (D. Bonhenry), [email protected] (R. Schindl).

https://doi.org/10.1016/j.semcdb.2019.01.002 Received 11 September 2018; Received in revised form 12 December 2018; Accepted 5 January 2019 1084-9521/ © 2019 Elsevier Ltd. All rights reserved.

Please cite this article as: Bonhenry, D., Seminars in Cell and Developmental Biology, https://doi.org/10.1016/j.semcdb.2019.01.002

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harmonic springs. Although many different types of force fields are available, intramolecular interactions are usually being represented as the following:

Uintra =

∑ bonds

1 kb (r − r0)2 + 2

+ cos (n ϕ− δ)] +

angles

1 ka ( θ− θ0)2 + 2

∑

Vn

∑

∑ torsions

Vn [1 2

impropers

The first sum describes the bond itself, r0 is the equilibrium distance and kb the spring constant, those terms can be inferred from X-ray and Raman spectroscopy, respectively. Because of the harmonic description, covalent bonds cannot be broken during a molecular dynamics simulation. Harmonic bonds are not computationally expensive compared to other potentials that are able to replicate chemical bonds breaking, and although being an imperfect approximation at first glance, this harmonic description remained somehow valid during most of the cases. The second term describes the angles between atoms, θ0 is the equilibrium angle and ka the spring constant. These parameters can be fitted based on vibrational spectra. The third term refers to torsional or dihedral angles and translates the rotation around bonds. These terms allow to describe the rigidity of a molecule and thus its conformations. Compared to bonds or angles, torsional angles are being modeled using cosine functions. The term Vn describes the height of the potential barrier between minima, n gives the number of minima between 0 and 2π, Φ is the torsional angle and δ is the phase. These parameters are usually derived from ab initio calculations and can be then refined based on vibrational spectra or molecular geometry. Finally, the last term is necessary to describe out-of-plane motions. The previous torsional term is not able to represent such vibrations and thus needs to be added separately to ensure that the planarity of some groups, such as carbonyl groups or aromatic rings, is maintained. Non-bonded interactions encompass usually electrostatic, dispersion and repulsion contributions. In most force fields these interactions are modeled as:

Uinter =

∑ i, j > i

qi qj 4πε0 rij

+

⎡ r

12

∑ E0 ⎢ ⎜⎛ rm ⎟⎞

i, j > i

⎣⎝

ij

⎠

Fig. 1. Top and side view of the hOrai1 channel The homology model for hOrai1 was designed based on the crystal structure of Drosophila Orai [15]. The side view of hOrai1 (upper panel) reveals the long narrow pore (TM1, light red) and represents the main pore-lining residues. The additional TM regions are shown in light grey. At the top of the channel, the selectivity filter (SF) at position 106 is depicted in red spheres. Further, the CAR (calcium-accumulating region) forming amino acids are represented in dark red sticks. In the bottom panel, the top view of hOrai1 is shown, highlighting the extent of the channel pore and the CAR. The color code for specific amino acids refers to the following: red are aspartates/glutamates, white are hydrophobic residues, blue are basic residues are polar residues. Model archive entry for hOrai1: ma-akdjp [51].

6

r ⎤ − 2 ⎜⎛ m ⎟⎞ ⎥ ⎝ rij ⎠ ⎦

Here, the first sum represents electrostatic interactions via Coulomb’s law where qi and qj are the charges of the particles, ε0 the vacuum permittivity and rij the distances between the two particles. These interactions are long-range interactions and dominate for charged or polar particles. The second term describes short-range interactions by using a Lennard-Jones potential. The term in rij−12 is a repulsive term and represents Pauli repulsions due to the overlapping of the electronic clouds. The term in rij-6 is attractive and comes from the Van-der-Waals forces. The parameters E0 and rm represent the depth of the potential well and the distance at which the potential reaches its minimum, respectively. Depending on the system studied, different types of force fields are available for both organic or inorganic materials. Choosing an appropriate force field is a crucial task as the outcome of the simulations might be greatly influenced by it [9–12]. Each force field has its strong points and drawbacks, which must be kept in mind when analyzing the trajectory that derived from molecular dynamics simulations. As a final note, the outcome of a molecular dynamics simulation is meaningful as long as the system reached equilibrium and the studied reaction coordinates (observables) have been sampled with sufficient statistical relevance during the course of the simulation. However, some biological events might appear on time-scales that are difficult to observe with standard MD or even out of reach. To circumvent this problem, many different techniques have been implemented. Choosing the adequate technique depends on the problem at hand and the sensitivity needed by the user. In general, they are regrouped under the term of enhanced-sampling techniques. A complete overview of all these techniques would be beyond the scope of this short introduction, hence the

reader is pointed toward more profound materials, present in the literature [13,14]. In the following sections of this review we will discuss the theoretical work performed so far on the structure of the calcium releaseactivated calcium (CRAC) channel Orai1. For this purpose, we will first present different modeling protocols that have been used in studies of this biological system. 2. Modeling and architecture of the Orai channel Simulations of proteins often require an already resolved 3D structure, originating either from X-ray or NMR measurements. Fortunately, a structure of Orai, derived from the Drosophila Melanogaster (dOrai) has already been resolved [15], allowing numerous simulation studies to be performed and published. The crystallized Orai channel is unique in its architecture. The hexameric homomeric structure includes a central pore ring of six transmembrane (TM) 1 helices surrounded by two rings of transmembrane helices. TM2 and TM3 helices surround the pore, and TM4 helices form an outer ring (Fig. 1) [15]. All TM helices are tightly packed and exclude lipids within the channel architecture. 2

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Fig. 2. Comparison of diverse ion channel structures Side-by-side representation of the top (top row) and side views (bottom) of various ion channels explains differing structural features, particularly in respect to selectivity and conductance. While the pore of the KcsA (grey), NavAb (green), CavAb (blue) and TRPV6 (yellow) channels have a V-like shape, the Orai1 channel (light red) pore is formed by long alpha helices. Especially highlighted are the most important amino acids in the CAR (calcium-accumulating region, red circles) and amino acids that build the selectivity filter (SF). The same color code for the amino acids as in Fig. 1 was applied and in addition green sticks for polar residues. PDB codes: KcsA: 4UUJ [86], NavAb: 4EKW [87], CavAb: 5KLB [21], TRPV6: 5IWK [20]. Model archive entry for hOrai1: ma-akdjp [51].

pass the selectivity filter face a central, hydrophobic barrier within the pore. This segment includes the residues V102, F99 and L95 in Orai1 (V174, F171 and L167 in dOrai). This specific region is so narrow that even water molecules are hindered to pass through, clearly demonstrating that the dOrai channel is crystallized in its closed conformation. Mutations of V102 to an alanine or several other amino acids results in large constitutive active Orai1 channels [19], independent of storedepletion and STIM1 binding. In addition, the pore-lining F99 also yields leaky Orai1 channels upon mutations [31]. However, these constitutively active Orai1 mutants result in a greatly reduced Ca2+ selectivity [19,31]. Interestingly, the interaction of STIM1 with these leaky Orai1 mutants regains the high Ca2+ selectivity [19,31]. These experiments are well in line with the model that the selectivity filter of Orai1 is not only manifested by the charge, generated by six symmetric glutamates (E106 in hOrai1), but also by the amount of time the Ca2+ ion is coordinated by the selectivity filter residues. In particular, Yamashita et al. have shown that the entry and exit barriers of the selectivity filter largely control the high Ca2+ selectivity of the Orai1 channel [32]. This mechanism has been precisely described for the Orai3 channel, which is highly homologous to Orai1. Interestingly, a unique feature of the Orai3 channel is its activation by the small molecule 2APB (2-aminoethoxydiphenyl borate), besides STIM1. While STIM1/Orai3-mediated currents generate highly selective Ca2+ currents, 2APB-mediated Orai3 currents are non-selective cation currents [32,33]. The 2APB-mediated Orai3 currents have a fourfold larger single-channel conductance due to reduced barriers of the selectivity filter. In the upcoming chapters, we will specifically highlight mechanistic achievements for the Orai channel with a special focus on MD simulations. The combination of wet and dry lab experiments provides a clearer picture of how the Orai channel works upon specific conditions.

TM4 helices include a slight kink mediated by a conserved proline residue. The C-terminal TM4 helices then extend into the cytosol with a short loop and form pair-wise coiled-coil helices that are oriented in an antiparallel direction [15]. This coiled-coil structure is a well-described docking site for STIM1 (Stromal Interaction Molecule 1), a [Ca2+]ER sensor protein that directly gates Orai channels [16,17]. The cytosolic STIM1 C-terminus also includes a coiled-coil structure that forms dimers [17,18]. Subsequently, the STIM1/Orai channel interaction is based on a super coiled-coil structure [17]. This active STIM1/Orai1 channel complex permeates Ca2+ ions with a remarkable selectivity [19]. In general, ion channels are able to single out ions from the aqueous media by mimicking the coordination sphere of the ions they are meant to conduct. This task is assigned to a domain of the protein called the selectivity filter (SF). This domain, usually the narrowest portion of the pore, is lined up with residues where either their carbonyl group or their side-chains will interact with the metal. The pore of the Orai1 channel is unusual for a Ca2+ selective channel and shows no structural similarities with highly Ca2+ selective TRPV6 [20], voltage-gated CavAb [21] (Fig. 2), inositol trisphosphate receptor IP3R [22,23] or ryanodine receptor RyR [24]. These Ca2+ selective channels resemble their channel architecture much closer to K+ or Na+ channels than to Orai1 (Fig. 2). TRPV6, voltage-gated Cav1 and Cav2 channels are homotetrameric channels where the selectivity filter is formed by four glutamates, whereas the SF domain of Cav3 is formed by two glutamates and two aspartates [25]. These substitutions have a clear impact on the selectivity as the preference for calcium towards sodium drops fivefold compared to Cav1 and Cav2. In conclusion, selectivity for calcium over sodium is usually dictated by a higher number of glutamate residues. Interestingly, by using the pore from the sodium voltage-gated channel NavAb (175TLESWSM181 motif), Tang et. al. [26] have been able to engineer a calcium voltage-gated channel CavAb by introducing the following mutation 175TLDDWSD181 (bold letters indicate mutated residues). Several mutants have been created by exchanging the residues in this sequence with aspartic acids. The prevalence of calcium ions is dependent upon the number of aspartates introduced. Some sodium channels even enforce their selectivity for sodium by adding hydrophobic or positively charged residues within their SF (DEKA locus) [27]. The selectivity filter in human Orai1 (hOrai1) is a conserved glutamate 106 (E178 in dOrai) (Fig. 1). A single Ca2+ ion is visible in the crystallized Drosophila Orai channel, slightly external of this glutamate ring. Even a conservative mutation of this glutamate to an aspartate largely reduces Ca2+ selectivity of this channel [28–30]. Mutations to an asparagine even abolish Ca2+ permeation [28,30]. Ca2+ ions that

2.1. Pore water helps Orai channel gating The first simulation of Orai has already been published [34] one year after the crystal structure had been released. In this study, Dong et al. explore the characteristics of the channel pore and link the hydration properties of the pore with its conductance. Due to the complexity of biological membranes, it is nearly impossible to replicate its composition in a molecular dynamics simulation. The membrane has been modeled by a bilayer of phospholipid molecules (namely 1-Oleoyl2-palmitoyl-phosphatidylcholine or POPC molecule) with the channel inserted into it. As a simulated system requires to be electroneutral, hence electrostatically uncharged, sodium chloride is added to neutralize the system, with an ionic strength equivalent to 0.15 M, as in extracellular conditions. After the simulations reach equilibrium, a fair 3

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both values are estimated for a transmembrane potential of −100 mV while the concentration of sodium chloride is set up at 150 mM in the simulation and the saturation concentration of sodium is estimated experimentally to be 90 mM. In their paper, Yamashita et al. have further commented that the major difference between the free-energy profiles for a sodium ion or a calcium ion would be the presence of a central binding site for calcium ions related to the presence of the selectivity filter [32]. Interestingly, the profile by Dong et al. estimated for sodium, do not show any pronounced well around the selectivity filter [34]. Although already a lot of work has been performed to estimate freeenergy barriers in ion channels [38,39], comparing this value to the free-energy barrier of other ion channels could be delicate. Especially the mechanism of gating and the ionic specificity, which differs among ion channels, could draw some misleading conclusions. However, here we present an attempt to give a couple of relevant case studies. Probably two pertinent channels, at least for this case, would be the gramicidin channel and the voltage-gated NavAb sodium channel. Gramicidin [40] is a small protein that acts as an antimicrobial agent. Upon insertion within a phospholipidic bilayer, this protein forms a dimer, resulting in a channel. Through this channel, monovalent cations, such as sodium, cross the bacterial cell membrane, thus disrupting the membrane potential between the extracellular media and the cytosol. Due to its relatively small size and early characterization at a high resolution, gramicidin A has been often used as a role model in simulations to benchmark and check free-energy calculation protocols [41,42]. For this channel [41], the free-energy barrier calculated for a sodium ion to cross the channel is around 8 kcal/mol. NavAb is a sodium channel belonging to the super-family of the voltage-gated ion channels. The cornerstone of electrical signaling in excitable cells, NavAb [43], is a sodium-conducting voltage-gated channel, opening in response to depolarization of the cell. In silico studies [44] based on molecular dynamics simulations and free-energy calculations have been performed to explore the selectivity of this channel for sodium in spite of other cations, such as potassium or calcium. The free-energy barrier experienced by a sodium ion leaving the selectivity filter towards the central cavity of the channel is estimated at ∼3.8 kcal/mol. Another study [45] on the same channel has reported a free-energy barrier of the same order (i.e. ∼4 kcal/mol). In general, even if the estimations of free-energy barriers are possible, relating them to the experimentally measured conductivity requires more calculations, as also the value of the diffusion coefficient is needed [38]. If both quantities have been computed, then the conductance of the channel could be calculated and compared with experiments. However, care needs to be taken as simulations often do not necessarily mimic a biological environment and corrections due to the presence of ionic gradients and transmembrane voltage ought to be taken into account during the appreciation of the results [46]. In a subsequent study on Orai channels, the voltage effect has been further investigated by adding explicitly a transmembrane voltage within the simulations rather than post-processing the free-energy profiles [47]. A transmembrane voltage can be modeled by applying a uniform electric field across the simulation box along the geometric normal to the bilayer [48]. The authors observe that under a hyperpolarized potential subtle changes in the pore conformation and water reorganization happen, facilitating the passage of ions. In the same line, the impact of mutations on the hydration level within the Orai channel has been studied by MD simulations [49]. Alavizargar et al. have focused on a mutation present in the third transmembrane segment of Orai, thus located rather far away from the gating pore. It has been revealed experimentally [50] that the selectivity of the channel is altered by a mutation at position 190 in hOrai1 [30]. Replacing the glutamate by a glutamine shifts the sensitivity from calcium to sodium. In their study, Alavizargar et al. have focused on the hydration of peripheral channels located at the back of the pore formed by the TM1, TM2 and TM3 helices. While in the wild-

amount of sodium ions is located at the entrance of the gate, approximately eight cations, while an unusual amount of chloride ions is located within the pore, inside the basic region. In comparison, the crystal structure of dOrai exhibits a small negatively charged plug instead of the chloride ions [15]. As the crystal structure captured the channel in a closed conformation, additional simulations have been performed by using specific mutants that are known to create a leaky channel, even without STIM1 binding, to get the active state conformation of the channel. Herein, the Drosophila Orai mutant V174 A (human Orai1-V102 A) has been investigated due to its large constitutively active current even in the absence of STIM1 [19]. Based on the wild-type (WT) structure, mutations in the channel have been generated by replacing the six valine side-chains at position 174 to alanines, thus providing the possibility to simulate the protein with this gain-of-function mutation. From their simulations, Dong et al. have been able to come up with molecular perspectives relative to ion permeation [34]. The level of hydration, i.e. the number of water molecules within the pore, is higher for the mutant in comparison to the wild-type Orai channel [34]. This observation is related to the difference in the chemical composition of the amino acids. When comparing valine to alanine, the latter offers a lower hydrophobic barrier as the isopropyl group of the valine sidechain is replaced by a methyl group. Based on these findings, the authors have been able to explore the energetic pathways of an ion crossing the channel. Simulating calcium ions or other multivalent ions is still a delicate endeavor in respect of the analysis of calcium selective channels, like Orai [35]. Multivalent ions have a tendency to strongly polarize their environment, reflected in a non-negligible displacement of the electronic clouds in the atoms or molecules located in close vicinity of these ions. A feature that is unfortunately not reproducible with conventional molecular dynamics, since electronic polarization is neglected due to the representation of the atoms as hard-spheres. Hence, in their study, the authors have used sodium ions and estimate the free-energy barriers encountered by such cations during their journey through the pore. Electrophysiological recordings of Orai channels have determined that Orai1 efficiently conducts Na+ when all divalents are buffered in the extracellular medium [28,30]. As mentioned in the section dedicated to molecular dynamics, such ion crossing would represent a rare event as the conductance of Orai channels is relatively low, even for sodium ions, ∼30 fS for Ca2+ [36] and ∼700 fS for Na+ [29]. In the case of sodium, this can be translated into one permeation event every two microseconds [29]. Such time-scale is currently out of reach with conventional MD, therefore, the authors have used an enhanced sampling technique called adaptive biasing force (ABF) [37] to estimate the free-energy barriers and to observe the crossing of a sodium ion through the conducting pore. The conducted calculations show a marked increase of the free-energy barriers when the sodium ions have been driven through the hydrophobic gate in MD simulations. This barrier is more pronounced for the wild-type Orai compared to the mutant, which is consistent with the lower level of hydration in the wild-type Orai1 pore. However, these barriers are further reduced when correcting the profiles by taking the transmembrane voltage into account. In the end, the mutations lower down the barrier by ∼4 kcal/mol compared to the wild-type protein. This barrier is precisely located at the exit of the hydrophobic gate. Overall, the hydrophobic gate represents a free-energy barrier of 7 kcal/mol for the sodium ion to cross through the Orai pore. This value relates well with the experimental value obtained for Orai3 [32]. Yamashita et al. have used a model based on rate theory where the energy profile for a permeating ion is based on a series of discrete energy wells separated by energy barriers. By measuring permeating rates and associated saturating flux concentrations, the overall free-energy barrier for a sodium ion is around 12 R.T. (with R being the ideal gas constant and T the temperature). Assuming a temperature of 300 K, the freeenergy barrier obtained from simulations is around 11.7 R.T. Note, that 4

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compete with the calcium binding in the CAR through the formation of salt-bridges between the aspartate at position 112 and an arginine at position 210, as seen in the simulations and in cysteine cross-linking experiments of hOrai1 [51].

type protein, these channels are amply hydrated, the mutation E262Q in dOrai (E190Q for hOrai) significantly reduces the level of hydration of the peripheral regions of the channels. From around 200 water molecules (∼30 per subunit), in the case of the native protein, the number drops down by almost 50% for the mutant (∼17 water molecules per subunit). Diffusion of sodium ions has been reported as well in this peripheral region but without witnessing any permeation events. Furthermore, in dOrai E262 is involved in salt-bridges with K270 in TM3. In the case of the mutant, these lysines are found to stretch towards the extracellular side, close to the selectivity filter. The impact of this particular lysine on the Ca2+ selectivity of the channel has been further explored by Brownian dynamics. The selectivity filter of dOrai has been modeled by a ring of 12 negative particles (corresponding to the 12 oxygens in the glutamate sidechains), each bearing a negative charge of 0.5. These 12 particles are surrounded by a ring of 6 other particles where their charges were scaled from 0 (no elementary charge at the entrance of the pore) to 1 (6 elementary charges at the entrance of the pore). This toy model, in presence of a concentration of sodium and calcium mixed together, is able to not only reproduce the natural selectivity of Orai towards calcium but also the anomalous mole fraction effect. The anomalous mole fraction behavior is typical for Ca2+ channels. Orai channels select Ca2+ ions for permeation by a factor of 1000 more than Na+ ions. When extracellular Ca2+ levels drop to a micromolar concentration, the Ca2+ ions bound to the selectivity filter still block Na+ permeation. The low extracellular Ca2+ concentration limits Ca2+ permeation, hence currents reach a minimum. Even lower Ca2+ concentration results in frequent Na+ permeation [50]. When the particles around the selectivity filter have been assigned a +1.0 charge (dOrai mutant E262Q is leading to free lysines at position K270), the calcium current drops significantly while the sodium current remains unaffected in agreement with experimental observations.

2.3. The hydrophobic gate of Orai Ca2+ ions that permeate through Orai1 channels are first attracted by the CAR region and pass the selectivity filter. Subsequently, the Ca2+ ions need to pass the narrowest, hydrophobic part of the pore. As mentioned before, the hydrophobic residues V102, F99 and L95 in hOrai1 form a barrier in the pore. Yamashita et al. [31] have sought to explore the gating mechanism of dOrai with a special focus towards the hydrophobic gate. Specifically, the phenylalanine at position 99 in hOrai1 (F171 in dOrai) has been thought to be the barrier for calcium permeation. By using cysteine mutations at residue positions corresponding to the hydrophobic gate and by looking at Cd2+ accessibility, the authors conclude that a reorientation of the pore-facing sidechain from F99 is linked to Orai1 activation by STIM1. Following these results, mutations aiming at lowering or increasing the hydrophobicity at position F99 have been generated. Electrophysiological recordings in combination with genetic engineering and molecular dynamics simulations are used to explore the impact of these mutations on the channel conductance. Lowering the hydrophobicity at F99 (substitution of phenylalanine to cysteine, serine, threonine, glycine, methionine or tyrosine) causes a constitutively active channel. In opposition, when hydrophobicity is increased (substitution with leucine, isoleucine or valine), the channel remains closed, even when STIM1 is present. Hence, mutations that allow more water molecules to be accumulated within the hydrophobic gate increase the permeation of ions across the channel. However, no correlation is found with respect to the size of the amino acid at position 99. Molecular dynamics simulations are then used in order to decipher the role of F99 in the gating mechanism. The wild-type phenotype of dOrai as well as several of its mutants, namely V174 A, F171Y and F171 V (correlating to V102 A, F99Y and F99 V in hOrai1, respectively), are simulated. In each of these cases, multiple replicas of the simulations are performed with a total amount of simulation time between 2 μs to 7 μs, depending on the constructs. For the constitutively active mutants (V174 A and F171Y), larger counterclockwise shifts of the pore-forming helices, with respect to the crystal structure, are observed compared to WT or F171 V (loss-of-function mutation). The authors suggest that a pore helix rotation is more likely to be the origin of the increased hydration rather than a lateral displacement of the helices. The degree of pore hydration observed in the simulations, in both theoretical studies, correlates nicely with the level of experimentally recorded conductance for the different constitutively active mutants [52,53]. Mutations within the pore of Orai channels induce the largest leaky channels. However, these mutations may highly alter the pore and could interfere with the regulation of the gating mechanism. Thus, engineering Orai mutations in the surrounding TM helices alters the permeation properties less drastic than pore mutations. Screens for constitutively active Orai mutants have yielded several hits in all four transmembrane domains [52–54]. A set of mutants (A137 V, L138 F, H134 A, S141C) in TM2 of hOrai1 have been identified to create constitutively open channels where the H134 A mutant shows the highest level of activation [52,53]. Numerous small residue substitutions of H134 result in constitutively active hOrai1 currents [53]. Instead, engineered large hydrophobic mutations for H134 block hOrai1 currents almost completely. Then, even STIM1 and store-depletion fail to stimulate currents of hOrai1-H134 hydrophobic mutant [53]. Yeung et al. have performed a cysteine screening, where all residues in the four TM helices of hOrai are mutated [52]. The aim has been to explore possible pathways within the channel, where communications between residues could convey the gating signal from the STIM binding sites of Orai to the pore itself. Here, light is brought on a histidine at position 134

2.2. The calcium-accumulating region (CAR) of Orai The studies that have been reviewed so far are solely based on simulations. Some studies combine in vitro with in silico experiments as well, to rationalize cellular events at a molecular level. Until now, the Orai channel from Drosophila Melanogaster has been the only one resolved experimentally, therefore no other structures for this channel were available. Furthermore, also the extracellular loops have not been resolved, only the transmembrane regions. However, in 2015, a template for the human Orai1 channel, including the missing loops, has been constructed by using homology modeling based on the published Drosophila crystal structure. In their study, Frischauf et al. explore the Orai1 region upstream of the selectivity filter comprising the extracellular loop of the channel [51]. This region, rich in aspartate residues, is stated to form a calcium-accumulating region (CAR) helping to enhance permeation by attracting calcium ions and increasing the local calcium concentration close to the pore entrance [51]. Single point mutations of key residues in the CAR of hOrai1, namely aspartate at positions 110, 112 and 114, induce a decrease of channel conduction especially at a low level of extracellular calcium (< 2 mM). In agreement with those observations, density profiles of Ca2+ ions, computed from molecular dynamics simulations, show a shift outward the selectivity filter as well as a decrease of calcium density in the case of the mutants compared to wild-type hOrai1. It is of note that other Ca2+ selective channels include a similar Ca2+ accumulation region extracellularly to the selectivity filter. Within voltage-gated CavAb, TRPV6, IP3 and ryanodine receptor (RyR) two to four aspartates or glutamates per subunit are expected to coordinate initial Ca2+ binding and thereby enhance the local, extracellular Ca2+ concentration (Fig. 2). A further observation of the CAR region has also pointed towards interactions between the extracellular loop 1, bearing acidic residues, and loop 3, bearing positive residues. These interactions are found to 5

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Orai1 protein. In all three studies, the missing loops of Orai in the crystal structure have been added (either rebuilt de novo or added by homology modeling) without applying any constraints, external stimuli or any other triggers during the simulations. However, despite these differences, in all of the cases, simulations are able to corroborate experimental observations coming from mutagenesis studies. The discrepancy of the modulated Orai channel gating is explained by different simulation protocols. The first variation in these MD simulations are the force fields, as this is known to lead to different protein dynamics and folding [11,56,59] The second difference in the protocol used for the simulations is the membrane composition that is known to affect Orai properties [58]. To further exemplify the former, the transmembrane connections noted in our study, involving H134 and S93, are not confirmed by the other study. Such an outcome might be attributable to the force fields themselves as partial charges differ. To clearly decipher which effects may lead to these differences, further in-depth theoretical studies are welcomed.

whose gain-of-function mutants have been shown to give pores the highest constitutive activity [52,53]. In MD simulations, mutations to H206S and H206C for dOrai (H134S and H134C in hOrai1) yield a counterclockwise pore helix rotation of 30 ± 1° and 34 ± 2°, respectively based on the crystal structure. Those values are higher than for WT or V174 A Orai (V102 A hOrai1) with values being respectively 17 ± 1° and 22 ± 2°. The extent of rotation is accompanied by an increase of water molecules within the pore. Again, these results are fitting perfectly with experimental observations where H206S and H206C dOrai mutants show higher conductance compared to dOraiV174 A. 2.4. The electrostatic gate Frischauf et al. have investigated the gating of the hOrai1 channel in MD simulations based on their previous homology template [53]. Our screen to investigate the effect of gain-of-function mutations within the transmembrane segments has been based on a cancer database. Similar as later on by Yeung et al., H134 A turns out to be the most efficient constitutively active hOrai1 mutation outside the pore [52,53]. Additional mutations are determined in the third and fourth TM helix. Some of these constitutively active mutants do not overlap with leaky Orai1 mutants from the cysteine mutagenesis screen [52,53]. These mutagenesis experiments suggest that the constitutive activity of the mutants not only depends on the residue position but also on the specifically engineered side-chain of amino acids. Simulations of WT-Orai1 in comparison to the Orai1-H134 A mutant determine a slight increase of pore radius in the hydrophobic pore segment of the constitutively active mutant. While WT-Orai1 extensively excludes water molecules to access the hydrophobic pore segment, the constitutively open Orai1H134 A pore yields a chain of water molecules [53]. The possibility of a second gate at the end of the hydrophobic gate, just at the beginning of the basic region and under control of R91, has been explored. In the theoretical part of the study, steered molecular dynamics [55], another enhanced sampling technique, has been used to drive a calcium ion through the conducting pore of both wild-type hOrai1 and its mutant H134 A. The final results show that a higher force is needed to be applied in the case of the wild-type pore to drag the ion through. Pore surface calculations also show that the pore of H134 A is more accessible, while several zones of constriction are observed in the wild-type protein. These areas are mainly located at the end of the hydrophobic gate and around the R91 region. As a result of the pulling experiment, R91 residues are seen to interact through hydrogen bonds with neighboring serines (S90) in the case of the Orai1 H134 A channel, hence liberating the path within the conducting pore to ease the permeation of the incoming ions. In contrast, almost no such interactions are observable in the wild-type Orai1 pore and the arginine side-chains are pointing towards the pore. Here, we would like to report an interesting case on how simulations of a similar system can result in different mechanistic outcomes, due to variations of the simulation parameters. In the first case, the gating takes place by a TM1 helix rotation, and in the second case by an increase in flexibility in the pore-forming transmembrane helices. The simulations reported in Yamashita et al. [31] and Yeung S.-W. P. et al. [52] differ from ours [53] with respect to the used force field, as well as solvent and membrane composition. For the simulations based on the Drosophila crystal structure, the CHARMM36 [56] force field for both protein and lipids has been chosen and a membrane composed solely of phospholipids has been used as an anchoring matrix for the channel, respectively DPPC [31] and POPC [52]. While for our simulations, the OPLS-AA (Optimized Potentials for Liquid Simulations-All Atoms) force field for the protein and the Berger [57] parameters for the lipids have been used. Based on experimental evidence performed in vivo [58], showing that a depletion of cholesterol from the membranes leads to enhanced hOrai1 channel activity, our simulations include cholesterol molecules in addition within the POPC bilayer in interaction with the

2.5. A new open channel structure of dOrai Recently, the Long laboratory determined new insights into an active configuration of the Orai channel based on crystal structures. These structures are determined from Drosophila Orai with an engineered H206 A mutation [60], corresponding to H134 A in human Orai1 [53]. This constitutively active mutant shows two major structural conformational switches. First, the TM4 and its C-terminal extension are straightened and do not longer form antiparallel dimers [60]. In addition, the whole TM helices show an outward rotation of all helices, away from the central axis. Specifically, TM1 shows an additional outward bend that results, for example, at the electrostatic gate, position K159 (R91 in hOrai1), in an extension of about 10 Å [60]. The resolution of this new structure does not allow to accurately determine the position of the side-chains, but suggests a similar orientation of the residues as previously determined in the closed Orai channel [15]. The straightened TM4 is a prerequisite for the outward rotation of all other TM helices [60]. In a closed conformation, TM4 interacts with TM3 and thereby stabilizes the whole packed closed configuration of the TM helices of dOrai [60]. The authors describe the closed configuration as a belt that is released for channel activation [60]. Interestingly, a straightened TM4 helix is observed additionally as a transition state between closed and opened configuration. A second wild-type dOrai structure also still showed a tight pore configuration and a similar position of TM1, TM2 and TM3 in combination, yet with an extended TM4/C-terminus [60]. Hence, stabilizing the configuration of extended TM4/C-terminus by STIM1 may be required for the second conformational switch of an outward rotation of all TM helices and consequently an open pore. This new open dOrai structure provides exciting results that need to be compared with previous MD simulations. Opened conformations of Orai generated by MD simulations originate all from the initially closed dOrai channel [15]. An obvious point is that these open channel configurations did not result in such a drastic extension of the pore as in the novel crystal structure of dOrai-H206 A. Previous MD simulation of an analogous hOrai1-H134 A could not determine the straightened TM4/ C-terminus [53]. It is expected that the available time of MD simulations is not sufficient to determine such a large conformational switch. Additionally, further insights are required to understand why the TM4/ C-terminus can switch between two orientations without necessarily affecting the other TM helices. In comparison to previous work [31,34,53] the outward rotation of dOrai-H206 A is sufficient to permeate Ca2+ through the hydrophobic and electrostatic gate. Even smaller changes within the pore have been suggested to allow gating of Ca2+ ions, including an anticlockwise rotation or flexible widening of the TM1 pore [31,34,53]. Closer insights if the TM1 helix is also anticlockwise rotated cannot be determined by the current resolution of the dOrai-H206 A structure. Obviously, the histidine 206 (H134 in 6

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activates Orai1 mediated Ca2+ entry to a small extent upon slightly decreased ER Ca2+ concentrations [75]. Instead, STIM1 requires a more pronounced depletion of ER Ca2+ stores than STIM2. These important functional differences are partially due to the higher Ca2+ affinity of the STIM1 EF-hand structure compared to that of STIM2. Additionally, the EF-hand of STIM2 binds stronger to the SAM domain, when compared to STIM1 [74,75]. The different activation sensitivity allows to keep balanced ER Ca2+ concentrations and only stimulate down-stream signal propagation upon larger ER Ca2+ store-depletion. Not only the luminal EF-hand and SAM domains in STIM1 and STIM2 isoform control activation of Orai channels. Additionally, the binding affinity of STIM1 isoforms to Orai1 channels differ [78]. STIM1/2 include a long coiled-coil region to directly bridge the membranes of the ER and the plasma membrane followed by the Orai binding domain, named SOAR or CAD (STIM1 Orai1-activating region, CRAC-activating domain) [70,79]. This dimeric, helical structures can directly bind to the C-terminus of Orai1 [17]. Although at the time of this review no complete structure for STIM is available, several domains have been resolved experimentally. These NMR or crystal structures include the EF-hand and SAM domain of STIM1 and STIM2 [74,75], the long coiled-coil domain of STIM1 [80] and the domains that interact with Orai1 [17,18]. These structures provide molecular insights into how this protein participates in calcium signaling and, furthermore, allowing molecular dynamics simulations to be performed [81,82]. The first simulations reported within publications on STIM have been done on its luminal domain which bears the calcium-sensing motif, an EF-hand. In their study, Furukawa et al. [82] have looked at the stability of the STIM1 luminal domain in the presence or absence of calcium ions and its repercussion upon the outgoing signal. The simulations have used a structure of the luminal domain of STIM1 previously resolved via NMR techniques [74]. This protein fragment has been simulated with or without a calcium ion bound to the EF-hand at the position indicated within the NMR structure. It has to be noted that for these simulations, discrete molecular dynamics [83,84] (DMD) have been used. This method relies on the same theory as conventional MD, i.e. Newton’s equation, is solved for each atom within the systems, with the exception that the potential functions used to describe inter- or intramolecular interactions are represented by step-wise functions, hence discrete. As a consequence, instead of updating the velocities and forces on all atoms at each step, only the atoms involved in a collision are considered. DMD is, therefore, less expensive than MD in terms of computational power. To study the unfolding mechanism of the luminal domain, the authors have performed a series of DMD simulations at different temperatures, ranging from 240 K to 380 K. The specific heat capacity Cv has been calculated for the apo (without Ca2+) and holo (with Ca2+) state. A first, a sharp peak around 295 K in the Cv-T diagram can be observed for the apo state, indicating a transition event, in this case unfolding. For the holo state, the transition appears at around 310 K. Hence, the authors deduce that the apo form of the luminal domain has a propensity to unfold much easier than the holo state. In comparison, circular dichroism measurements for the isolated EF-hand SAM protein in its apo form reveal a midpoint of thermal transition from the folded to unfolded structure at 294 K [85]. In the presence of Ca2+, this transition is determined at 318 K in analogous recordings [85] both in line with MD simulations [82]. It has been proposed that calcium is able to stabilize the structure by screening the electrostatic repulsion between the negatively charged residues in the cEF-hand. Finally, it has been pointed out that in the absence of Ca2+ the nEFhand contributes significantly to the instability of the overall EF-SAM domain. Lately, another study [81] using traditional MD on the luminal domain and its interactions with calcium has been published. Here, the transmembrane section of STIM1 has been rebuilt in silico and added to the existing NMR structure, thus providing a minimal version of a STIM protein and this time anchored to a phospholipidic membrane. In order to examine calcium effects upon the stability of STIM, the same protocol

hOrai1) is a key position that is expected to control the closed configuration of the wild-type Orai channel due to electrostatic interactions with TM1. New MD experiments on the wild-type Orai with straightened TM4/C-terminus as well as on the opened dOrai-H206 A (hOrai1H134 A) configuration are expected to provide new exciting results of the sequential steps of Orai channel gating. 2.6. MD simulations of Orai3 channels Finally, also an isoform of Orai, namely human Orai3, has been simulated [61]. All three Orai isoforms can multimerize to either homoor heteromeric channels [33,62–64]. The electrophysiological characteristics of the three Orai isoforms are relatively similar. All Orai isoforms are highly Ca2+ selective over monovalents, as expected from their identical pore forming residues. A major physiological difference is their extent of Ca2+ dependent fast inactivation [65–68]. This important feedback mechanism guarantees to limit the amount of Ca2+ influx into the cell. In a similar manner as for hOrai1, a 3D structure of hOrai3 has been obtained by homology modeling based on the crystal structure of dOrai. These models have been used to explore possible interactions between intracellular loop 2, connecting the TM1 and TM2 of Orai1/Orai3 with their N-termini close to the pore-forming TM1helix. N-terminal deletions in Orai1 and Orai3 also target a proposed interaction site with STIM1 and hence might alter channel activity [61]. Yet, it is still under debate whether STIM1 binds directly to the N-terminus [69–71]. While in electrophysiological experiments, the deletion mutant Orai1 ΔN1-76/78 lose their function, Orai3 ΔN1-51/53 retain their activation capacity. With the help of chimera studies, it has been experimentally shown that Orai1 containing loop 2 of Orai3, instead of loop 2 of Orai1, allows partial recovery of channel function [61]. Further, molecular dynamics simulations of wild-type Orai1, Orai1 ΔN1-78, wild-type Orai3 and Orai3 ΔN1-53 have been performed. These simulations show that a deletion of the N-termini of Orai1 increases the disorder from the intracellular loop 2 and move apart from their initial position. These observations do not occur in the case study of Orai3 [61]. Furthermore, modeling of Orai3 suggests that the cytosolic extension of TM2 is longer in Orai3 compared to Orai1. As a consequence, the flexible portion, i.e. loop 2, in Orai3 would be smaller. Altogether, those proofs indicate that loop 2 together with the N-terminus of Orai might serve as a tuner upon binding to STIM1. 3. Stromal interaction molecule – STIM In its resting state, Orai channels are in a closed state located in the plasma membrane, thus forbidding entry for any calcium ions into the cytosol. It is only upon binding to its partner protein, STIM, that Orai can switch to an open state and create an influx of calcium ions through the plasma membrane. STIM1 and Orai1 need to be seen as a channel complex upon binding, as STIM1 even controls the selectivity of the Orai1 channel [55]. Two isoforms of STIM can be found in mammalian cells, STIM1 and STIM2 [72]. The activation cascade and their overall structure is largely similar for the two STIM isoforms. As already mentioned at the beginning of this review, STIM is a single pass transmembrane protein and located within the membrane of the calcium stores, either at the endoplasmic or sarcoplasmic reticulum, depending on the type of cells being looked at [73]. Within the ER lumen, STIM proteins contain a single functional EF-hand (cEF) that binds Ca2+ and a second non-canonical EF-hand (nEF). The EF-hand domains are bound to a luminal SAM (sterile α-motif) domain, which is followed by the transmembrane region [74,75]. In the cytosolic C-terminus, STIM forms dimeric, helical structures that can directly bind to Orai1 [17,18]. Although the overall sequence of STIM1 and STIM2 is relatively similar in essential domains, their roles in calcium homeostasis fulfill two different tasks. While STIM1 acts as signaling processing protein, e.g. regulating T-cell activation, STIM2 acts in feedback regulation to keep the ER stores full [76,77]. Hence, STIM2 already 7

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as in the previous reviewed article is used, more precisely both, the apo and holo state are simulated. In these simulations, the authors observe that in the absence of calcium, an opening of the cEF-hand is happening thus exposing the hydrophobic residues to the surrounding water. A displacement between the two EF-hands, the nEF-hand moving away from the cEF-hand, is noted as well. The latter observation being in accordance with the previous simulations has been performed on the sole luminal domain. Finally, some consequences involving the loss of Ca2+ on both the TM region and the helix α10 from the SAM domain appear. The authors speculate, based on their simulations, that some residues in the α10 region would form a β-strand-like structure, able to interact with the phospholipids, that will be pulled into the bilayer. This would induce a displacement of the TM region within the membrane and trigger a rearrangement in the cytosolic domain. However, it has to be brought to attention that those simulations only cover a really short time-scale as they only span 10 ns. Thus, the results coming from this study are more likely to give a preview of how the absence of calcium ions impacts the structure of the luminal domain as other events might unfold later.

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4. Outlook This review summarizes how MD simulations provide astonishing insights into gating, selectivity and stability of the Orai channel family and the initial store-operated activation process of STIM1. Specifically, a Ca2+ accumulating region is predicted by MD simulations and verified experimentally. Also, open pore conformations of Orai channels are visualized by MD simulations based on constitutively active Orai1 mutants. Still many fascinating aspects of the STIM/Orai channel complex function remain unknown. Further studies are needed to explain how Ca2+ store-depletion leads to STIM oligomerization and subsequent coiled-coil zipping. Additionally, MD simulations can help to determine the molecular steps that are involved in STIM1 – Orai1 docking, as in the resting state, the SOAR structure is protected from interaction via structures in the long coiled-coil helix 1. It would also be important to determine if STIM1 could gate Orai1 channels in a similar way as single point mutations do. Furthermore, it would be interesting to examine the clustering of STIM/Orai channels that control the size of Ca2+ signaling for cellular downstream signaling processes. A structural and mechanistic picture by simulations and live cell experiments would then allow to visualize temporal tuning of open and closed STIM/Orai channels to explain physiological important Ca2+ oscillations. Acknowledgments We thank Prof. Christoph Romanin and Dr. Irene Frischauf (Johannes Kepler University, Linz) for carefully proofreading the manuscript. We gratefully acknowledge the support by the Austrian Science Fund (FWF) through project P28701 to Ra.S, by the Czech Science Foundation through a grant to R.H.E. (13-21053S) and by the Czech Research Infrastructure for Systems Biology C4SYS (LM2015055). DB was supported by the EFRR project Interreg Austria Czech Republic "Czech-Austrian Center for Supracellular Medical Research (CAC-SuMeR, No# ATCZ14)”. Ra. S and R.H.E. were funded in part through a European Cooperation in Science and Technology (COST) action (BM1406) and by the program Inter-COST (project LTC17069 to R.H.E.). References [1] M. Tuckerman, Statistical Mechanics: Theory and Molecular Simulation, Oxford, 2011. [2] D.C. Rapaport, The Art of Molecular Dynamics Simulation, 2 ed., Cambridge University Press, Cambridge, 2004. [3] F. Daan, S. Berend, Understanding Molecular Simulation: From Algorithms to Applications, Academic Press, Inc., 1996.

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