Differential molecular information of maurotoxin peptide recognizing IKCa and Kv1.2 channels explored by computational simulation
© Yi et al; licensee BioMed Central Ltd. 2011
Received: 16 September 2010
Accepted: 25 January 2011
Published: 25 January 2011
Scorpion toxins are invaluable tools for ion channel research and are potential drugs for human channelopathies. However, it is still an open task to determine the molecular basis underlying the diverse interactions between toxin peptides and ion channels. The inhibitory peptide Maurotoxin (MTX) recognized the distantly related IKCa and Kv1.2 channel with approximately the same potency and using the same functional residues, their differential binding mechanism remain elusive. In this study, we applied computational methods to explore the differential binding modes of MTX to Kv1.2 and IKCa channels, which would help to understand the diversity of channel-toxin interactions and accelerate the toxin-based drug design.
A reasonably stable MTX-IKCa complex was obtained by combining various computational methods and by in-depth comparison with the previous model of the MTX-Kv1.2 complex. Similarly, MTX adopted the β-sheet structure as the interacting surface for binding both channels, with Lys23 occluding the pore. In contrast, the other critical residues Lys27, Lys30, and Tyr32 of MTX adopted distinct interactions when associating with the IKCa channel. In addition, the residues Gln229, Ala230, Ala233, and Thr234 on the IKCa channel turret formed polar and non-polar interactions with MTX, whereas the turret of Kv1.2 was almost not involved in recognizing MTX. In all, the pairs of interacting residues on MTX and the IKCa channel of the bound complex indicated that electrostatic and Van der Waal interactions contributed equally to the formation of a stable MTX-IKCa complex, in contrast to the MTX-Kv1.2 binding that is dominantly mediated by electrostatic forces.
Despite sharing similar pharmacological profiles toward both IKCa and Kv1.2 channels, MTX adopted totally diverging modes in the two association processes. All the molecular information unveiled here could not only offer a better understanding about the structural differences between the IKCa and Kv1.2 channels, but also provide novel structural clews that will help in the designing of more selective molecular probes to discriminate between these two channels.
Scorpion venoms produce a large variety of peptide toxins that target ion channels [1–5]. Especially, the widespread use of scorpion-venom peptides acting on K+-channels as neuroscience tools and excellent ligand models has tremendously increased our knowledge in many fields, including exploration of the 3-dimensional structures and elucidation of the pharmacological characteristics of K+ channels [4, 6–8]. In addition, peptide toxins are increasingly recognized as valuable sources of new drugs for channelopathies [9, 10]. Although natural toxins often lack sufficient efficacy and specificity toward an individual channel type, most peptide toxins adopt a cysteine-stabilized α/β scaffold; thus, they could serve as good candidates for further structure-based drug design [4, 10]. However, crystal structures for many medically important potassium channels have not been determined, which makes the rational designing of K+-channel modulators difficult. Therefore, applying computational methods to model reasonably stable structures of channel-peptide toxin complexes could be a good alternative, which would greatly help to highlight the diversity of channel-toxin interactions and provide structural information for toxin-based drug design.
The intermediate-conductance calcium-activated potassium channels (IKCa) act as positive modulators of cell proliferation by hyperpolarizing the cell membrane in T and B cells, fibroblasts, and vascular smooth muscle cells [11–13]. Furthermore, blocking of IKCa channels has been shown to be a potential therapeutic strategy against autoimmune disorders involving these tissues [13–15]. However, almost all the peptidic and small molecular IKCa blockers could not discriminate well between the IKCa channel and other related Kv-family channels and, thus, lack the specificity needed for further drug development [12, 13, 15, 16].
Maurotoxin (MTX), a peptide derived from the venom of the scorpion Scorpio maurus palmatus, is the most potent peptidic blocker of the IKCa channel [17, 18]. In addition, MTX could distinguish the IKCa channel from the other calcium-activated channels and the Kv1-family channels, except for the voltage-gated Kv1.2 channel [17–21]. Interestingly, although the IKCa channel is entirely different from the Kv1.2 channel in tissue contribution and physiological function [11, 12, 15, 16], MTX shows very similar pharmacological profiles in recognizing these two channels with approximately the same potency and using the same functional residues [17, 18, 21]. In this study, we aimed to interpret the differential binding mechanisms of MTX with reference to the IKCa and Kv1.2 channels, which would provide a deep insight into the topological differences of these two channels and offer important clues for designing inhibitors that are more selective toward the therapeutic IKCa channel.
Combined computational methods were used to investigate the details of the interactions between MTX and the IKCa channel; the structural details were further compared with the previous model of the MTX-Kv1.2 complex . A stable structure of the MTX-IKCa complex was obtained by using ligand docking, clustering analysis, and molecular dynamics simulation (MDS) methods. The validity of the final MTX-IKCa complex was supported by good accordance between the computational alanine-scanning results and the experimental data. On comparison, although with similar pharmacological profiles, MTX adopted very different modes for associating with the IKCa and the Kv1.2 channels. In both MTX-IKCa and MTX-Kv1.2 complexes, MTX adopted the β-sheet domain as the interaction surface with the Lys23 occluding the pore. However, the other key residue, Tyr32, was positioned quite differently in these two complexes. Meanwhile, the turret region of the IKCa channel played an important role in binding with MTX, which is different from the noninvolvement of the Kv1.2 turret during interaction with MTX. In addition, due to the different physicochemical profiles of the two channels, electrostatic and van der Waals (vdW) interactions made different contributions to the free energies of binding in MTX-Kv1.2 and MTX-IKCa complexes. All these structural and energetic discrepancies constitute the key determinants responsible for the binding specificity of MTX to the IKCa and Kv1.2 channels, which could help design MTX derivatives that would discriminate between these two channels.
Results and Discussion
Different MTX binding modes towards IKCa and Kv1.2 channels
MTX-IKCa complex from docking and MDS
We next applied a routine molecular docking and clustering analysis to screen plausible MTX-IKCa complexes [22–25]. All the 35 nuclear magnetic resonance conformations of MTX with different side-chain positions were used in the ZDOCK program, and 35, 000 complexes were generated in total.
To check the confidence of our MTX-IKCa model, the ΔΔGbinding of eight single mutations of MTX were calculated and compared with the experimental data [17, 18]. An overall high degree of correlation was found between the calculations and the experiments involving mutational effects (Figure 3C). Replacing the Lys23 residue of MTX with alanine caused the most noticeable decrease of 4.4 kcal/mol in the calculated binding energy, which is well in accordance with the experimental data of 4.32 kcal/mol. Substitution of another important residue, Tyr32, with alanine significantly reduced the MTX affinity by over 1000 fold , and the calculated ΔΔGbinding value of 4.31 kcal/mol corresponded well with the experimental data of 4.21 kcal/mol. However, MTX affinity for IKCa was decreased by less than 10 fold by the S2A, T4A, S6A, K7A, Y10A, and G33A mutants . This is strongly supportive for the little change in binding energy when these residues were mutated to alanine; this is because Ser2, Thr4, Ser6, and Lys7 were located at the N-terminal of MTX, whereas Tyr10 was in the middle of the α-helix of MTX, all outside the interface of MTX.
Consistent with the findings in previous docking experiments of MTX onto IKCa channel , in the final MTX-IKCa complex, the peptide used its β-sheet as the interacting surface, with Lys23 as a structurally conserved pore-blocking residue (Figure 3D). This phenomenon was also observed when MTX associated with the Kv1.2 channel in both our study  and the previous docking results by Visan . All these studies underline the key role of MTX β-sheet region in IKCa and Kv1.2 channel recognition. Interestingly, such importance is strongly supported by the previous experimental data that when substituting the β-sheet region of MTX with that of another toxin, HsTX1, its activity toward the two channels almost disappeared .
Despite that MTX used the β-sheet to interact with both IKCa and Kv1.2 channels, when analyzing the conformation of other bioactive residues, the molecular information for the recognition of IKCa by MTX showed several distinct features, compared to those for the Kv1.2 channel.
Differential molecular information contained by Tyr32 and Lys7 in MTX
In addition, rather than forming strong electrostatic interactions with the aspartic acid residues in the pore region of the channel, the side chain of the Lys7 of MTX pointed to an opposite orientation from the IKCa channel, contacting no residue of the channel within a 5-Å distance (Figure 4C). This is different from the result of the mutant-cycle analysis that Lys7 is situated near the Asp239 of the IKCa channel [17, 18]. However, as the K7A mutation only affected the blocking activity of MTX by less than 10 fold [17, 18], it is possible that the Lys7 just faced its alternative partner Asp239 in the interface reorganization process, but does not contact Asp239 directly in the final conformation. Such a position of the Lys7 while associating with the IKCa channel differed significantly from that in the MTX-Kv1.2 complex, in which the Lys7 formed strong polar interactions with the Asp373 at the pore region of the channel  (Figure 4D). This distinctness was in consistence with the experimental data that the blocking activity of the MTX-K7A mutant decreased by about 100 fold in the case of the Kv1.2 channel, but decreased by only less than 10 fold in the case of the IKCa channel .
Differential molecular information of other residues in MTX
However, these interaction modes mediated through Lys27 and Lys30 of the MTX in recognizing the IKCa channel differed obviously from those involving MTX and the Kv1.2 channel, in which both Lys27 and Lys30 formed strong polar interactions with the channel . Within a contact distance of 5Å, the Lys27 and Lys30 of MTX, respectively, contacted closely with the conserved acidic residue, Asp379, in the pore region of the Kv1.2 channel and formed strong electrostatic interactions (Figure 5B).
Effects of K27A and K30A mutants on interactive energies (Kcal/mol)
Distinct channel vestibules constitute different recognition modes toward maurotoxin
The α-KTx family of K+-channel blockers has been proved to function as informative molecular probes for the structure-function analysis of K+ channels. Although the IKCa and Kv1.2 channels have distinct tissue distributions and biophysical features [11–16], both can be blocked by MTX with a similar pharmacology profile. Thus, identifying the differential determinants that are responsible for the MTX binding of the IKCa and Kv1.2 channels could help discover the different topologies of a mechanistically interesting part of these two channels: the outer vestibule of the ion-conduction pore.
Different polar and nonpolar contributions to the binding free energies in MTX-IKCa and MTX-Kv1.2 complexes
Through combined computational methods, including ZDOCK, clustering analysis, and MDS, a reasonably stable MTX-IKCa complex structure was obtained. Further study of this structure showed that in spite of sharing similar pharmacological profiles toward both IKCa and Kv1.2 channels, MTX associated with the IKCa channel in a quite different mode compared to that of MTX interacting with the Kv1.2 channel. In the bound complex, MTX assumed the β-sheet domain as the interaction surface with the Lys23 occluding the pore of the IKCa channel in a manner similar to its interaction with the Kv1.2 channel. However, the conformation of another key residue Tyr32, which was the key to the stability of the complex structure, differed greatly when MTX recognized the IKCa channel, compared to the process with the Kv1.2 channel. It continued lying on the linker connecting the selectivity filter and the S6 helix of the IKCa channel, forming strong polar and nonpolar interactions with residues on the pore region of the channel. In addition, the Lys7 of MTX is possibly involved in the toxin-channel interface reorganization process; however, it does not contact any residues of the IKCa channel directly in the final conformation. This is in contrast with the fact that the Lys7 of MTX formed strong polar interactions with the Asp373 at the pore region of the Kv1.2 channel. In addition, electrostatic and vdW interactions contributed equally to the binding of MTX with IKCa, whereas the MTX-Kv1.2 association featured dominant electrostatic contribution. Such conformational and energetic differences in recognition could be well explained by the different functional roles of the channel vestibules. The longer, neutral-charged IKCa channel turret played an important role in stabilizing the final IKCa-MTX complex, with four residues--Gln229, Ala230, Ala233, and Thr234 forming polar and non-polar interactions with MTX. On the contrary, the shorter Kv1.2-channel turret is highly negatively charged and is barely involved in recognizing MTX. In all, the differences in the binding mechanisms of MTX toward the IKCa and Kv1.2 channels unveiled in this study could offer a better understanding of the physicochemical properties and conformational distinctness of the two channels and thus give a hint for designing MTX-derived inhibitors to discriminate between these two channels.
Atomic Coordinates and Molecular Docking
The atomic coordinates of MTX (PDB code: 1TXM) were downloaded from the PDB . The previous segment-assembly homology model was applied to obtain the structure of the pore region of the IKCa channel . This model was then subjected to 5-nanosecond (ns) MDS for equilibration.
To improve the docking performance, all 35 conformations of MTX were used to dock with the equilibrated IKCa structure through the ZDOCK program , a fast Fourier transform (FFT)-based, initial-stage rigid-body molecular-docking algorithm. Each docking produced 1000 candidate complexes, thus 35000 candidate MTX-IKCa complexes were obtained and used for the clustering analysis. According to the orientation of the MTX β-sheet domain, the 35000 complexes were then divided into four main binding modes. Clustering analysis and experimental data-based screening [17, 18] were then carried out on all the complexes to select the possible hits from all modes. Candidates from each binding mode were then subjected to a 500-step energy minimization using the Sander module of the Amber-8 suit of programs . By calculating the ligand-receptor binding energies with the ANAL program of Amber-8, appropriate candidate complexes were identified for further MDS study.
All the simulations in this work were carried out using the Amber-8 program  on a 64-CPU Dawning TC4000L cluster (Beijing, China). The generalized Born model , which has been successfully used to study other toxin-channel interactions [22, 24, 25, 32, 33], was applied in this study.
All the candidate complexes selected by the screening process went through 400-picosecond (ps) equilibration and 500-ps unrestrained simulations to introduce more flexibility. The equilibration steps were taken by gradually reducing the force constant--from 5.0 (kcal/mol)/Å2 for restraining all the heavy atoms, to 0.02 (kcal/mol)/Å2 for heavy atoms of the backbone only. The temperature was set at 300 K, with a cutoff distance of 12 Å. For the most reasonably stable complex selected after a 500-ps unrestrained simulation, an additional 10-ns unrestrained simulation was conducted to introduce enough flexibility and to probe into the interaction details. Throughout all the energy minimization and simulation processes, the ff99 force field (Parm 99)  was applied.
During the simulation, the membrane around the channel has not been taken into account. It is because that the scorpion peptide binds to the extracellular part of the channel according to mutagenesis studies and solid-state NMR results [6, 35–37], where the interaction is hardly affected by the membrane and the transmenbrane segment of channel. Other study groups have also used the same membrane-ignoring measures in molecular simulation studies of toxin-channel interactions [22–25, 32, 33, 38–40]. However, the importance of the membrane in the functioning of channels has been increasingly recognized. A transmembrane protein system could be more reliable if the role of the membrane were taken into account.
Calculation of Free energy of Binding by the Molecular mechanics--Generalized Born Surface Area method
where T is the temperature, S is the solute entropy, ΔGgas is the interaction energy between A and B in the gaseous phase, and , , and are the solvation free energies of A, B, and AB, which are estimated using the GBSA method . That is, , and so forth. ΔGGB and ΔGSA are the electrostatic and nonpolar terms, respectively. ΔEbond, ΔEangle, and ΔEtorsion are contributions to the intramolecular energy ΔEintra of the complex. EvdW is vdW interaction energy. Because of the constant contribution of -T ΔS for each docked complex, we quote ΔG*binding for ΔGbinding + T ΔS in the discussion. To verify the quality and validity of the resulting MTX-IKCa complexes, the relative free energy of binding, ΔG*binding, was calculated using MM-GBSA for postprocessing-collected snapshots from the MD trajectories. In this work, 30 snapshots from the last 30-ps MDS were used for analysis of the free energy of binding.
This work was supported by grants from the National Natural Sciences Foundation of China (number 30900265, 30770519 and 30973636), the China Postdoctoral Science Foundation (number 20090451075) and the National Basic Research Program of China (2010CB529800).
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