Identification of Aethina Tumida Kir Channels As Putative Targets of The

Article Identiﬁcation of Aethina tumida Kir Channels as Putative Targets of the Bee Venom Peptide Tertiapin Using Structure-Based Virtual Screening Methods

Craig A. Doupnik

Department of Molecular Pharmacology & Physiology, University of South Florida College of Medicine, Tampa, FL 33612, USA; [email protected]

Received: 20 August 2019; Accepted: 18 September 2019; Published: 19 September 2019

Abstract: Venoms are comprised of diverse mixtures of proteins, peptides, and small molecules. Identifying individual venom components and their target(s) with mechanism of action is now attainable to understand comprehensively the effectiveness of venom cocktails and how they collectively function in the defense and predation of an organism. Here, structure-based computational methods were used with bioinformatics tools to screen and identify potential biological targets of tertiapin (TPN), a venom peptide from Apis mellifera (European honey bee). The small hive beetle (Aethina tumida (A. tumida)) is a natural predator of the honey bee colony and was found to possess multiple inwardly rectifying K+ (Kir) channel subunit genes from a genomic BLAST search analysis. Structure-based virtual screening of homology modelled A. tumida Kir (atKir) channels found TPN to interact with a docking profile and interface “footprint” equivalent to known TPN-sensitive mammalian Kir channels. The results support the hypothesis that atKir channels, and perhaps other insect Kir channels, are natural biological targets of TPN that help defend the bee colony from infestations by blocking K+ transport via atKir channels. From these in silico findings, this hypothesis can now be subsequently tested in vitro by validating atKir channel block as well as in vivo TPN toxicity towards A. tumida. This study highlights the utility and potential benefits of screening in virtual space for venom peptide interactions and their biological targets, which otherwise would not be feasible.

Keywords: bee venom; bioinformatics; computational docking; homology modelling; ion channel structure; protein–peptide interactions; tertiapin; venom peptides; virtual screening; small hive beetle

Key Contribution: Using structure-based computational modelling techniques, Kir channels expressed in the small hive beetle were discovered as suitable targets for channel block by the Apis mellifera venom peptide tertiapin. This novel ﬁnding highlights the utilization of computational tools in setting new research directions, and potentially expands the repertoire of venom actions aiding in honeybee defense from natural insect predators.

1. Introduction Venoms from Hymenoptera and other venomous species are comprised of diverse mixtures of proteins, peptides, and small molecules [1,2]. The composition of these “venom cocktails” are species-dependent, where the concentration of individual toxin components can vary by age, sex, diet, and diﬀerent environmental conditions [3]. Envenomation eﬃcacy is largely driven by the adaptive evolutionary pressures that select for certain venom genes based on their ability to either: (1) aid in predation, (2) aid in defense from predation, and/or (3) aid in reproductive health and survival (e.g., anti-microbial and anti-parasitic activity) [4].

Toxins 2019, 11, 546; doi:10.3390/toxins11090546 www.mdpi.com/journal/toxins Toxins 2019, 11, 546 2 of 17

One of the well-established molecular targets of venom-derived toxins are the ion channels expressed in natural prey and predators. As potent modulators of ion channel function during envenomation, venom-derived peptides contribute to the overall venom response by causing a variety of physiologic responses including paralysis for host capture and pain for defense from predators [5]. The atomic-level structural details that have emerged for both venom-derived peptides and several ion channels have enabled structure-based computational screening techniques to be deployed for identifying potential target effectors for venom components in silico [6]. These methods are also helping to guide rational peptide design efforts to re-engineer venom peptides for potential drug development purposes [7–9]. While most efforts have focused on molecular targets of venom components in laboratory mammals and human tissues, understanding the biological targets of venom-derived peptides encountered in nature is essential for providing a comprehensive understanding of the evolutionary adaptations that drive target selectivity and affinity, and thereby contribute to overall venom efficacy. Such an insight can also be valuable in identifying potential off-target effects in humans where venom-derived peptides are being developed for both therapeutic and non-therapeutic basic research applications [10]. Here, the use of structure-based virtual screening techniques was deployed to search and identify putative ion channel targets using a small venom peptide from Apis mellifera (A. melliferra) venom called tertiapin (TPN). Venom produced by female worker bees is used primarily for individual defensive purposes, and to protect the colony from various invertebrates as well as vertebrate predators and/or pests. The updated genome assembly of A. melliferra (Amel_4.5) with venom transcriptomic analysis indicates over 100 proteins and peptides are present in honey bee venom to collectively mediate these responses [11]. TPN is a 21-amino acid peptide that represents a relatively small fractional component (0.1%) of the total protein content of bee venom [12], and was serendipitously discovered in 1998 to bind and block a subset of mammalian Kir channels [13,14]. The evolution-driven biological target(s) of TPN encountered in nature, however, is currently not established. Here, a hypothesis-driven in silico screening strategy is presented that supports insect Kir channels as potential natural targets for TPN-mediated channel block for bee colony defense from the small hive beetle. This novel finding highlights how the application of structure-based computational tools such as molecular docking can create new research directions by demonstrating mechanistically feasible and testable hypotheses on the adaptive pressures that drive interaction of venom peptides with their natural biological targets.

2. Results

2.1. Reliability of Molecular Docking of TPN to Kir Channel-Modelled Structures

The rat Kir1.1 channel is the prototypical TPN-sensitive Kir channel, having an IC50 of ~2 nM for functional channel block [14]. Interestingly, however, the human Kir1.1 channel isoform is insensitive to TPN block due primarily to two key amino acid differences in the outer vestibule of the Kir1.1 channel where TPN is known to bind [15,16]. Previous computational docking studies of NMR-derived TPN ensemble conformers (PDB ID 1TER.pdb [17]) to a homology-modelled rat Kir1.1 channel identified a favored TPN conformer having a pore-blocking binding pose where the positively charged C-terminal lysine side chain of TPN inserts and occupies the S1 K+ binding site in the channel selectivity filter [7]. Moreover, the computational docking scores reliably differentiate TPN interactions among homology-modelled Kir1.1 isoforms known to be sensitive (rat) and insensitive (human and zebrafish) to TPNQ channel block [7]. Thus, structure-based interactions between TPN and rat Kir1.1, derived from computational docking methods and validated in vitro, are thought to represent the high-affinity bound and blocked state of the channel [13] (but also see Reference [18]). To further test the reliability of this approach, the same molecular docking protocol used for the homology-modelled rat Kir1.1 channel was applied to crystal structures of the TPN-sensitive murine Kir3.2 channel homo-tetramer [19,20]. Mammalian Kir3.2 channel subunits are expressed in neuronal and endocrine cells and assemble primarily as hetero-tetrameric channels with different Kir3.x subunits, Toxins 2019, 11, 546 3 of 17

Toxins 2018, 10, x FOR PEER REVIEW 3 of 17 and functionand endocrine to inhibit cells membrane and assemble excitability primarily [21 as]. Whenhetero-tetrameric heterologously channels expressed with different in Xenopus Kir3.x oocytes, the homo-tetramericsubunits, and function Kir3.2 constructto inhibit membrane used for excitability X-ray crystallography [21]. When heterologously yields channels expressed functionally in Xenopus oocytes, the homo-tetrameric Kir3.2 construct used for X-ray crystallography yields channels blocked by the oxidation-resistant TPNQ variant peptide in a manner similar to hetero-tetrameric functionally blocked by the oxidation-resistant TPNQ variant peptide in a manner similar to hetero- Kir3.1/3.2 channels [20,22–24]. Thus, docking TPN to the Kir3.2 crystal structure precludes homology tetrameric Kir3.1/3.2 channels [20,22–24]. Thus, docking TPN to the Kir3.2 crystal structure precludes modellinghomology of the Kirmodelling channel. of the Kir channel. Shown inShown Figure in1 Figure, rigid-body 1, rigid-body docking docking of TPN of conformersTPN conformers to the to Kir3.2the Kir3.2 channel channel crystal crystal structures was dependentstructures on was the dependent NMR-derived on the TPNNMR-derived conformer TPN usedconformer for docking, used for docking, similar tosimilar that to observed that with TPN dockingobserved to the with homology-modelled TPN docking to the homology-modelle rKir1.1 channeld [rKir1.17]. For channel the Kir3.2 [7]. For channel, the Kir3.2 the channel, TPN conformer the TPN conformer that yielded the highest docking score for both the closed-state and pre-opened- that yieldedstate theconformations highest docking was TPN-13. score for both the closed-state and pre-opened-state conformations was TPN-13.

Figure 1. Preferential docking of the tertiapin (TPN)-13 conformer to mKir3.2 channel structures. A. StructuralFigure rendering 1. Preferential of docking the Kir3.2 of the closed tertiapin state (TPN)- (3SYA.pdb)13 conformer(ribbon to mKir3.2 diagram) channel structures. with TPN A. (orange, solid rendering)Structural positionedrendering of the above Kir3.2 the closed outer state vestibule. (3SYA.pdb)B. (ribbonStructural diagram) rendering with TPN (orange, of the “pre-opened”solid conformationrendering) of Kir3.2 positioned channel above in complexthe outer withvestibule. Gβγ B.dimers Structural (4KFM.pdb) rendering (ribbonof the “pre-opened” diagram) with TPN conformation of Kir3.2 channel in complex with Gβγ dimers (4KFM.pdb) (ribbon diagram) with TPN (solid rendering) depicted above the outer vestibule of the channel. C & D. Plots of the top 100-ranked scores for all 21 TPN conformers docked to the Kir3.2 channel closed-state conformation (C) and pre-opened-state conformation (D). The data curves and asterisks indicated in red correspond to the TPN-13 conformer that yielded the highest score for each Kir3.2 channel conformation. E. Plot of the maximal docking scores (mean SD, top 5 complexes) for each TPN conformer docked to the Kir3.2 ± channel closed-state conformation (3SYA, green symbols) and pre-opened-state conformation (4KFM, blue symbols). Toxins 2018, 10, x FOR PEER REVIEW 4 of 17

(solid rendering) depicted above the outer vestibule of the channel. C & D. Plots of the top 100-ranked scores for all 21 TPN conformers docked to the Kir3.2 channel closed-state conformation (C) and pre- opened-state conformation (D). The data curves and asterisks indicated in red correspond to the TPN- 13 conformer that yielded the highest score for each Kir3.2 channel conformation. E. Plot of the maximal docking scores (mean ± SD, top 5 complexes) for each TPN conformer docked to the Kir3.2 channel closed-state conformation (3SYA, green symbols) and pre-opened-state conformation (4KFM, blue symbols). Toxins 2019, 11, 546 4 of 17 To further characterize the structural similarity among the 21 TPN conformers, hierarchical clustering analysis of the calculated pairwise alpha-carbon amino acid backbone RMSD values for theTo NMR further ensemble characterize structures the structuralwas performed similarity (Figure among 2). The the 21RMSD TPN cluster conformers, analysis hierarchical identified 4 clusteringdistinct sub-conformations analysis of the calculated for TPN, pairwise where alpha-carbonconformers TPN-12 amino and acid TPN-13 backbone belonged RMSD valuesto the same for thesub-conformation NMR ensemble cluster structures group was and performed were closest (Figure in structural2). The RMSD similarity cluster among analysis the 21 identified conformers 4 distinct(Figure sub-conformations2A). As previously reported, for TPN, wherethe TPN-12 conformers conformer TPN-12 yielded and the TPN-13 top-ranked belonged docking to the score same for sub-conformationthe homology-modelled cluster group rat Kir1.1 and werechannel closest [7] and in structural represented similarity the second among best the docking 21 conformers score for (FigureKir3.22 A).(see As Figure previously 1). Thus, reported, the TPN thedocking TPN-12 results conformer to Kir3.2 yielded channels the in top-ranked both closed docking and pre-opened score forconformations the homology-modelled are in good ratagreement Kir1.1 channel with the [7 ]prev andiously represented characterized the second rat Kir1.1 best docking docking score study for and Kir3.2support (see Figurea favored1). Thus,role for the the TPN TPN docking sub-conformati results to Kir3.2on state channels represented in both by closed the cluster and pre-opened group that conformationsincludes TPN-12 are inand good TPN-13 agreement conformers. with theOne previously of the major characterized structural contributors rat Kir1.1 docking mediating study the anddifferent support TPN a favored sub-conformations role for the TPN was sub-conformation the orientation of state the C3–C14 represented disulfide by the bond cluster that group contributes that includesto the overall TPN-12 tertiary and TPN-13 peptide conformers. structure and One orient of theation major of the structural surface contributors exposed side mediating chains (Figure the diff2B).erent TPN sub-conformations was the orientation of the C3–C14 disulfide bond that contributes to the overall tertiary peptide structure and orientation of the surface exposed side chains (Figure2B).

Figure 2. Hierarchical clustering of NMR-derived TPN structural conformers based on pairwise RMSD analysis. A. Heatmap and cluster analysis of the calculated pairwise RMSD along the TPN 21-amino acid alpha-carbon backbone. RMSD analysis was performed using VMD software, with the resulting 21 21 matrix (21 TPN conformers by 21 TPN amino acids) analyzed using Heatmapper × (http://www.heatmapper.ca). The red asterisks denote the TPN-12 and TPN-13 conformer clusters that yield the top docking scores to Kir3.2 and are structurally similar. B. Structural alignment of TPN-1 and TPN-12 conformers, highlighting the different disulfide (Cys3–Cys14) bond configuration contributing to different peptide conformations. Toxins 2018, 10, x FOR PEER REVIEW 5 of 17

Figure 2. Hierarchical clustering of NMR-derived TPN structural conformers based on pairwise RMSD analysis. A. Heatmap and cluster analysis of the calculated pairwise RMSD along the TPN 21- amino acid alpha-carbon backbone. RMSD analysis was performed using VMD software, with the resulting 21 × 21 matrix (21 TPN conformers by 21 TPN amino acids) analyzed using Heatmapper (http://www.heatmapper.ca). The red asterisks denote the TPN-12 and TPN-13 conformer clusters that yield the top docking scores to Kir3.2 and are structurally similar. B. Structural alignment of TPN- Toxins 2019, 11, 546 1 and TPN-12 conformers, highlighting the different disulfide (Cys3–Cys14) bond configuration5 of 17 contributing to different peptide conformations.

Surface renderingsSurface renderings of TPN-13 dockedof TPN-13 to thedocked Kir3.2 to channelthe Kir3.2 are channel shown are in Figure shown3 wherein Figure the 3 entire where the TPN peptideentire structure TPN peptide is shown structure to be boundis shown deep to be within bound thedeep channel within the outer channel vestibule outer andvestibule plugs and the plugs channel likethe a “cork channel in alike bottle”. a “cork The in TPN a bottle”. peptide The interacts TPN peptide in an asymmetricinteracts in an manner asymmetric making manner diﬀerent making different contacts with the four identical Kir3.2 subunits. However, similar to the modelled Kir1.1 contacts with the four identical Kir3.2 subunits. However, similar to the modelled Kir1.1 channel, channel, the C-terminal TPN K21 side chain occupies the central channel pore with other TPN the C-terminal TPN K21 side chain occupies the central channel pore with other TPN residues making residues making contact with Kir3.2 vestibule residues including the Kir3.2 turret structures. contact with Kir3.2 vestibule residues including the Kir3.2 turret structures.

Figure 3. Binding pose of TPN docked to the Kir3.2 channel. A. Surface renderings of the TPN-13 Figure 3. Binding pose of TPN docked to the Kir3.2 channel. A. Surface renderings of the TPN-13 conformer (shown in orange) docked to the Kir3.2 channel (subunits A, B, C, and D color-coded). conformer (shown in orange) docked to the Kir3.2 channel (subunits A, B, C, and D color-coded). TPN-13 was docked to the Kir3.2 channel closed state (3SYA.pdb) using Cluspro 2.0. Shown are a top TPN-13 was docked to the Kir3.2 channel closed state (3SYA.pdb) using Cluspro 2.0. Shown are a top view (upper image) from an extracellular vantage point, and a side view (lower image) where the TPN view (upper image) from an extracellular vantage point, and a side view (lower image) where the peptide is mostly occluded from the view by Kir3.2 subunit A (magenta). B. Solid side-view rendering TPN peptide is mostly occluded from the view by Kir3.2 subunit A (magenta). B. Solid side-view (upper image)rendering of the TPN-docked (upper image) Kir3.2 of the channel TPN-docked with subunitKir3.2 channel A removed with subunit to expose A removed for viewing to expose the for docked TPN-13viewing conformer the docked (in orange) TPN-13 withinconformer the channel(in orange) vestibule. within the The channel lower vestibule. image is aThe “sectioned” lower image is side-view renderinga “sectioned” that exposes side-view the rendering location ofthat the exposes C-terminal the TPNlocation lysine of the (K21) C-terminal located at TPN the mouthlysine (K21) of the channellocated pore. at Also the mouth visible of is the the channel juxtaposed pore. TPNAlso visi peptideble is the with juxtaposed the Kir3.2 TPN turret peptide domain with from the Kir3.2 subunit D. turret domain from subunit D.

2.2. Virtual Screening for TPN-Interacting Kir Channels Given the reproducible outcomes for TPN docking to homology-modelled rKir1.1 channel and the two mKir3.2 channel crystal structures, homology models for 14 diﬀerent mouse Kir channel isoforms (Figure4A) were constructed analogous to rKir1.1 and then screened in silico for docking interactions with the TPN-12 conformer. The homology-modelled Kir channels were all homo-tetramers, and the only Kir channel not examined was Kir2.3 which contained a signiﬁcantly larger extracellular turret loop region that precluded reliable modelling and assembly of the Kir2.3 homo-tetramer using the Swiss-Model homology-modelling program (see Materials and Methods section). Toxins 2018, 10, x FOR PEER REVIEW 6 of 17

2.2. Virtual Screening for TPN-Interacting Kir Channels

Toxins 2019, 11,Given 546 the reproducible outcomes for TPN docking to homology-modelled rKir1.1 channel and 6 of 17 the two mKir3.2 channel crystal structures, homology models for 14 different mouse Kir channel isoforms (Figure 4A) were constructed analogous to rKir1.1 and then screened in silico for docking Theinteractions ranked TPN-12 with the docking TPN-12 conformer. score profile The obtainedhomology-modelled from the Kir virtual channels screen were of all mouse homo- Kir channel tetramers, and the only Kir channel not examined was Kir2.3 which contained a significantly larger structuresextracellular is shown turret in loop Figure region4B, that where precluded the reli scoringable modelling algorithm and assembly is weighted of the Kir2.3 for receptor–ligandhomo- shape complementarity,tetramer using the Swiss-Model electrostatic homology-modelli contacts, andng vanprogram der (see Waal Materials forces and [25 Methods]. As reported section). previously, the top-rankedThe ranked docking TPN-12 scores docking begin score profile to rapidly obtained diminish from the virtual within screen the of top mouse ten Kir scored channel complexes. The averagestructures score is forshown the in top Figure 5 complexes 4B, where the for scor eaching Kir algorithm channel is weighted is shown for in receptor–ligand Figure4C. In shape agreement with complementarity, electrostatic contacts, and van der Waal forces [25]. As reported previously, the functionaltop-ranked studies, docking three mousescores begin Kir channelsto rapidly dimi withnish the within highest the dockingtop ten scored scores complexes. were channels The known to be sensitiveaverage score to functional for the top 5 TPN complexesQ block, for each namely Kir ch Kir1.1,annel is Kir3.2,shown in and Figure Kir3.4. 4C. In agreement Unexpectedly, with however, the Kir channelfunctional having studies, thethree second mouse Kir highest channels docking with the score highest was docking Kir4.1. scores When were examining channels known the top-ranked dockingto scores, be sensitive the to order functional for energetically TPNQ block, namely favored Kir1.1, interactions Kir3.2, and Kir3.4. with Unexpectedly, TPN-12 was however, Kir1.1 > Kir4.1 > the Kir channel having the second highest docking score was Kir4.1. When examining the top-ranked Kir3.4 >dockingKir3.2 scores,> Kir3.1. the order The for Kir3.1 energetically docking favored scores interactions were comparable with TPN-12to was the Kir1.1 TPN-insensitive > Kir4.1 > Kir2.1 channel,Kir3.4 which > Kir3.2 is in > agreement Kir3.1. The withKir3.1 thedocking insensitivity scores were of comparable homomeric to the mutant TPN-insensitive Kir3.1 channels Kir2.1 to TPNQ block [26channel,]. Moreover, which is the in agreement other seven with Kirthe insensitivity channels with of homomeric lowest TPNmutant docking Kir3.1 channels scores to are TPN alsoQ known to block [26]. Moreover, the other seven Kir channels with lowest TPN docking scores are also known be insensitive to TPNQ block (i.e., Kir2.x, Kir6.2, and Kir7.1) and therefore establish a baseline profile to be insensitive to TPNQ block (i.e., Kir2.x, Kir6.2, and Kir7.1) and therefore establish a baseline for Kir channels insensitive to TPN [27]. These initial findings from the virtual screen across mouse profile for Kir channels insensitive to TPN [27]. These initial findings from the virtual screen across Kir channelsmouse largelyKir channels agree largely with knownagree with Kir known channel Kir TPN channel sensitivities, TPN sensitivities, but suggest but suggest the modelled the Kir4.1 channelmodelled outer vestibule Kir4.1 channel structure outer presents vestibule a viablestructure receptor presents targeta viable for receptor TPN interactions target for TPN comparable to known TPN-sensitiveinteractions comparable Kir channels. to known TPN-sensitive Kir channels.

Figure 4. TPN docking profile to mammalian Kir channels. A. Dendrogram illustrating the amino acid sequence similarity of mouse and human Kir channel isoforms. A multiple sequence alignment was performed using the Constraint-based Multiple Alignment Tool (COBALT, National Center for Biotechnology Information). The tree function was used to generate the dendrogram illustrating the clustering of Kir channel subunit isoforms into their different gene subfamilies [21]. The red asterisks denote Kir channels known to be functionally blocked by TPN. B. Top-ranked docking scores for the TPN-12 conformer to the outer vestibule of 12 different homology-modelled mouse Kir channels. The rat Kir1.1 profile previously reported is also shown for comparison, and is identical to mKir1.1. The five Kir channels with the highest docking scores are color-coded; mKir1.1 (red), mKir4.1 (yellow), mKir3.4 (blue), Kir3.2 (green), and mKir3.1 (orange). C. Comparison of maximal docking scores for the TPN–Kir channel complexes. Bars represent the mean SD for the top five-ranked complexes for each ± TPN12-docked Kir channel complex. Colored bars correspond to the Kir channels color labelled in panel B. Toxins 2018, 10, x FOR PEER REVIEW 7 of 17

Figure 4. TPN docking profile to mammalian Kir channels. A. Dendrogram illustrating the amino acid sequence similarity of mouse and human Kir channel isoforms. A multiple sequence alignment was performed using the Constraint-based Multiple Alignment Tool (COBALT, National Center for Biotechnology Information). The tree function was used to generate the dendrogram illustrating the clustering of Kir channel subunit isoforms into their different gene subfamilies [21]. The red asterisks denote Kir channels known to be functionally blocked by TPN. B. Top-ranked docking scores for the TPN-12 conformer to the outer vestibule of 12 different homology-modelled mouse Kir channels. The rat Kir1.1 profile previously reported is also shown for comparison, and is identical to mKir1.1. The five Kir channels with the highest docking scores are color-coded; mKir1.1 (red), mKir4.1 (yellow), mKir3.4 (blue), Kir3.2 (green), and mKir3.1 (orange). C. Comparison of maximal docking scores for the TPN–Kir channel complexes. Bars represent the mean ± SD for the top five-ranked complexes for each TPN12-docked Kir channel complex. Colored bars correspond to the Kir channels color labelled Toxins 2019, 11, 546 7 of 17 in panel B.

2.3.2.3. Interface Interface Analysis Analysis of of TPN-Docked TPN-Docked Kir Kir Channels Channels GivenGiven the the unexpected unexpected high high TPN TPN docking docking score score to to the the homology-modelled homology-modelled Kir4.1 Kir4.1 channel, channel, refinedreﬁned docking docking of of TPN TPN to to Kir4.1 Kir4.1 was was performed performed next next to to compare compare the the predicted predicted Kir Kir channel–TPN channel–TPN interfaceinterface contacts contacts using using PISA PISA [28]. [28]. Shown Shown in in Figure Figure 5,5, the the TPN TPN interface interface “footprint” “footprint” on on the the Kir4.1 Kir4.1 channelchannel vestibule vestibule waswas similarsimilar to to those those on on both both the TPN-sensitivethe TPN-sensitive rat Kir1.1 rat Kir1.1 and mouse and Kir3.2mouse channels, Kir3.2 channels,where three where major three subunit major contact subunit sites contact within sites the Kir within channel the vestibuleKir channel were vestibule observed. were These observed. interface These“hot spots”interface corresponded “hot spots” corresponded to: (1) the turret to: (1) region, the turret (2) a region, “ring” (2) region a “ring” located region along located the wallalong of thethe wall channel of the vestibule, channel andvestibule, (3) the and pore (3) entry the pore region. entry Most region. of theMost exposed of the residueexposed side residue chains side of chainsTPN participateof TPN participate in the predicted in the predicted asymmetric asymmetric binding binding interface interface in a Kir in subunit-dependent a Kir subunit-dependent manner. manner.For mKir4.1, For mKir4.1, the predicted the formationspredicted formations of hydrogen of bonds hydrogen were fewer,bonds sharingwere fewer, some conservedsharing some sites conservedin the channel sites in turret the channel and pore turret regions and but pore absent region ins thebut mid-levelabsent in the ring mid-level region where ring region mKir4.1 where lacks mKir4.1an equivalent lacks an acidic equivalent reside acidic present reside in rat present Kir1.1 in and rat mouse Kir1.1 Kir3.2.and mouse The Kir3.2. docking The pose docking for TPN-12 pose forwithin TPN-12 the Kir4.1within vestibule the Kir4.1 is shownvestibule in Figureis shown6, indicating in Figure a6, similar indicating general a similar orientation general where orientation the TPN whereC-terminal the TPN K21 C-terminal side chain K21 was side positioned chain was and po insertssitioned into and the inserts channel into pore. the channel pore.

Figure 5. Comparative analysis of the docked tertiapin “footprint” among 3 of the highest scored Kir channel outer vestibules. Diagrams for the subunit assembled Kir channel tetramer arrangements (top view) for the homology-modelled mKir1.1 (red) and mKir4.1 (yellow) channels, and the mKir3.2 (green) homo-tetrameric channel. The predicted amino acid contacts between TPN and each Kir channel subunit are listed in each diagram below, with interfacing residues indicated in yellow and residues making hydrogen bonds or salt bridge link indicated in orange. Inaccessible residues are shown in dark blue, and solvent-accessible residues not involved in the TPN–Kir channel inferface are shown in light blue. TPN–Kir channel Interface analysis was performed using the PISA program on the top-scored docked complexes. Toxins 2018, 10, x FOR PEER REVIEW 8 of 17

onToxins the top-scored2019, 11, 546 docked complexes. 8 of 17

Figure 6. Surface interface and contact sites for the TPN-docked mKir4.1 channel complex. A. Surface rendering of the modelled outer vestibule of the mKir4.1 channel (top view, left; side view, right). Yellow Figure residues6. Surface depict interface PISA-predicted and contact interface sites sites, for withthe TPN-docked orange residues mKir4.1 depicting channel sites with complex. predicted A. Surface H-bonds with the docked TPN peptide. For the side-view image, one of the channel subunits has rendering of the modelled outer vestibule of the mKir4.1 channel (top view, left; side view, right). been removed to expose the pore region of the vestibule. B. Surface rendering of TPN (red) docked Yellowto residues the outer vestibuledepict PISA-predicted of mKir4.1 channel interface (top view, left;sites, side with view, orange right). Forresidues the side-view depicting image, sites with predictedthe locationH-bonds of TPN with K21 the in thedocked pore is exposedTPN peptide. with one ofFor the the channel side-view subunits image, removed. one of the channel subunits has been removed to expose the pore region of the vestibule. B. Surface rendering of TPN 2.4. Testing TPNQ Block of Kir4.1 Channels Expressed in Xenopus Oocytes (red) docked to the outer vestibule of mKir4.1 channel (top view, left; side view, right). For the side- To test whether TPN functionally blocks mKir4.1 channels, the mouse Kir4.1 isoform was expressed view image, the location of+ TPN K21 in the pore is exposed with one of the channel subunits removed. in Xenopus oocytes and K currents recorded before and during 100 nM TPNQ application. Shown in + Figure7,K currents produced by expressed Kir4.1 channels were insensitive to 100 nM TPNQ, 2.4. Testinga concentration TPNQ Block that of blocks Kir4.1 nearly Channels 100% Expressed of the rKir1.1 in Xenopus channel current Oocytes [7, 14]. The lack of mKir4.1 Tochannel test whether block by 100TPN nM functionally TPNQ is also consistent blocks withmKir4.1 a previous channels, study thatthe examined mouse theKir4.1 blocking isoform was effects of a TPN derivative on Kir4.1 channels [27]. Thus, despite the positive in silico docking Q + expressedscores in demonstrating Xenopus oocytes good shapeand K complementarity currents recorded between before the receptor and during (mKir4.1) 100 and nM ligand TPN (TPN),Q application. + Shownthe in aFigureffinity for7, TPNK currentsQ block of produced functional Kir4.1by expressed channels isKir4.1 sufficiently channels low, indicatingwere insensitive the virtual to 100 nM TPNQ, screeninga concentration finding represents that blocks a “false nearly positive” 100% that of is likelythe rKir1.1 due to fewer channel and/or current weaker interaction[7,14]. The lack of mKir4.1hotspots. channel This block structure-based by 100 nM result TPN mayQ is nevertheless also consistent serve as with a useful a previous guide for re-engineeringstudy that examined the the TPN peptide scaffold to produce stronger interactions that yield a higher-affinity TPN variant that blocking effectsQ of a TPNQ derivative on Kir4.1 channels [27]. Thus, despite the positive in silico can functionally block the Kir4.1 channel receptor given its demonstrated shape complementarity. docking scores demonstrating good shape complementarity between the receptor (mKir4.1) and ligand (TPN), the affinity for TPNQ block of functional Kir4.1 channels is sufficiently low, indicating the virtual screening finding represents a “false positive” that is likely due to fewer and/or weaker interaction hotspots. This structure-based result may nevertheless serve as a useful guide for re- engineering the TPNQ peptide scaffold to produce stronger interactions that yield a higher-affinity TPN variant that can functionally block the Kir4.1 channel receptor given its demonstrated shape complementarity.

Toxins 2018, 10, x FOR PEER REVIEW 9 of 17 Toxins 2019, 11, 546 9 of 17

Figure 7. Validation testing for functional block of mKir4.1 channels by TPNQ. A. Electrophysiological Figure 7. Validation testing for functional block of mKir4.1 channels by TPNQ. A. Electrophysiological recordings of mKir4.1 channel currents before and during application of TPNQ in Xenopus oocytes. recordings of mKir4.1 channel currents before and during application of TPNQ in Xenopus oocytes. The time-course plot shows the amplitude of membrane currents at 80 mV during 2-electrode The time-course plot shows the amplitude of membrane currents− at −80 mV during 2-electrode voltage clamp recording. Indicated by the red bar, high K+ (98 mM) application evokes inward + voltage clamp recording.+ Indicated by the red bar, high K (98 mM) application evokes inward mKir4.1-mediated K currents. Application of either 100 nM TPNQ (green) or 1 µM BaCl2 (blue) + mKir4.1-mediated K currents. Application2+ of either 100 nM TPNQ (green) or 1 μM BaCl2 (blue) demonstrates TPNQ insensitivity and Ba sensitivity of mKir4.1 currents. Right panel: Membrane 2+ currentsdemonstrates evoked by TPN theQ voltage-ramp insensitivity protocol and Ba display sensitivity the inward of mKir4.1 rectification currents. properties Right panel: of the mKir4.1Membrane currents evoked by the voltage-ramp protocol display the inward rectification properties of the channel currents in the absence and presence of either 100 nM TPNQ (green) or 1 µM BaCl2 (blue). ThemKir4.1 results arechannel representative currents in of the 7 di absencfferente oocytes. and presenceB. Positive of either control 100 comparison,nM TPNQ (green) showing or 1similar μM BaCl2 electrophysiological(blue). The results recordings are representative of rat Kir1.1 of channel7 different currents oocytes. before B. Positive and during control application comparison, of 100 showing nM similar electrophysiological recordings+ of rat Kir1.1 channel currents before and during+ application TPNQ in Xenopus oocytes. High K (20 mM) was applied to evoke inward rKir1.1-mediated K currents of 100 nM TPNQ in Xenopus oocytes. High K+ (20 mM) was applied to evoke inward rKir1.1-mediated (red bar), where application of 100 nM TPNQ (green) blocked all the Kir1.1-mediated inward currents. + TheK results currents are representative(red bar), where of 5 application different oocytes. of 100 nM TPNQ (green) blocked all the Kir1.1-mediated inward currents. The results are representative of 5 different oocytes. 2.5. Hypothesis Testing with Structure-Based Virtual Screening 2.5. Hypothesis Testing with Structure-Based Virtual Screening The natural biological target of TPN as an active component of bee venom is currently not known.The venomnatural produced biological by ta stingingrget of femaleTPN as worker an active bees component is used primarily of bee for venom defensive is currently purposes not fromknown. individual The predationvenom produced and to protect by stinging the colony female from worker a variety bees of is di ffusederent primarily predators for and defensive pests encounteredpurposes infrom nature. individual The ability predation to produce and to an protect effective the and colony deterring from a noxious variety stimulusof different following predators a stingand ispests the resultencountered of several in nature. venom The components ability to thatproduce work an in effective concert onand diverse deterring molecular noxious targets stimulus expressedfollowing across a sting a wide is the range result of predatoryof several speciesvenom encounteredcomponents inthat nature work [12 in, 29concert]. How on TPN diverse specifically molecular mighttargets contribute expressed towards across the a wide bee defense range of response predatory is not species clear, encountered while blocking in nature renal Kir1.1[12,29]. channels How TPN andspecifically/or neuronal might and cardiaccontribute Kir3.x towards channels the in bee mammals defense seems response implausible. is not clear, Insects while are blocking among the renal manyKir1.1 natural channels predators and/or and neuronal pests that and bees cardiac encounter Kir3.x in channels nature, andin mammals therefore seems a testable implausible. hypothesis Insects is thatare certain among insect the Kirmany channels natural are predators the natural and targets pests of th TPNat bees in bee encounter venom. in nature, and therefore a testableTo begin hypothesis to test this is hypothesis,that certain theinsect TPN Kir virtual channels screening are the protocolnatural targets was applied of TPN to in Kir bee channels venom. identifiedTo frombegin a to BLAST test this search hypothesis, of the recently the TPN reported virtual screening small hive protocol beetle was genome applied (Aethina to Kir tumida, channels identified from a BLAST search of the recently reported small hive beetle genome (Aethina tumida,

Toxins 2018, 10, x FOR PEER REVIEW 10 of 17

Toxins 2019, 11, 546 10 of 17 assembly Atum_1.0, NW_017852934.1) [30]. The small hive beetle is a natural parasite of A. mellifera and is normally maintained by guard bee aggression towards adult and beetle larva that includes assemblyenvenomation Atum_1.0, [31,32]. NW_017852934.1) Eight predicted [ 30Aethina]. The tumida small hive(A. tumida beetle) is Kir a natural (atKir) parasitechannel subunits of A. mellifera in the andgenomic is normally Reference maintained Sequence by database guard bee were aggression identified towards from the adult BLAST and search beetle using larva the that mouse includes Kir3.2 envenomationsubunit sequence, [31,32 with]. Eight six having predicted full-lengthAethina tumidasequence(A. similarity tumida) Kir to (thatatKir) of channelthe TPN-sensitive subunitsin mouse the genomicKir3.2 channel Reference (Figure Sequence 8). A database multiple were sequence identiﬁed comparison from the BLASTwith the search family using of mouse the mouse Kir channel Kir3.2 subunitsubunits sequence, indicated with the sixatKir having channel full-length subunits sequence were most similarity similar to thateachof other, the TPN-sensitive clustering as a mouse distinct Kir3.2atKir channelchannel (Figuregene family8). A that multiple was closest sequence to the comparison mammalian with Kir the channel family gene of mouse subfamily Kir channelexpressed subunitspredominantly indicated in the epithelialatKir channel cells and subunits involved were in most K+ similarhomeostasis to each (i.e., other, Kir1.1, clustering Kir4.x, as and a distinct Kir7.1) at(FigureKir channel 9B). gene family that was closest to the mammalian Kir channel gene subfamily expressed predominantly in epithelial cells and involved in K+ homeostasis (i.e., Kir1.1, Kir4.x, and Kir7.1) (Figure9B).

Figure 8. Multiple sequence alignment of six Kir channel subunit proteins identified in a BLAST search of the Aethina tumida (A. tumida) genome. The TPN-sensitive mouse Kir3.2 channel sequence was included for comparison, where the percentages of coverage (cov) and identity (pid) are shown for eachFigureA. tumida 8. MultipleKir (at Kir)sequence channel alignment subunit referencedof six Kir cha to Kir3.2.nnel subunit The location proteins of theidentified 2 transmembrane in a BLAST domainssearch of (TM1 the andAethina TM2) tumida are indicated, (A. tumida connected) genome. by The the aminoTPN-sensitive acid sequence mouse of Kir3.2 the the channel outer vestibule sequence regionwas included that forms for the comparison, receptor for where TPN bindingthe percentages and block. of coverage (cov) and identity (pid) are shown for each A. tumida Kir (atKir) channel subunit referenced to Kir3.2. The location of the 2 Structuraltransmembrane models domains of the (TM1 six at andKir TM2) channels are indicated, were next connected constructed by the amino with homologyacid sequence modelling of the limitedthe to outer the outer vestibule vestibule region regionthat forms as describedthe receptor for for the TPN mouse binding Kir and channels. block. Molecular docking of TPN (conformer 13) identified two atKir channels (XP_019865983.1 and XP_019865939.1) that displayed TPN dockingStructural profiles models nearly of equivalentthe six atKir to thechannels TPN-sensitive were next mKir3.2 constructed channel with (3SYA.pdb) homology (Figure modelling9C,D). Thelimited interface to the and outer putative vestibule hot spots region for as TPN described interactions for the with mouse each Kir of thesechannels.atKir Molecular channelswere docking then of furtherTPN analyzed.(conformer 13) identified two atKir channels (XP_019865983.1 and XP_019865939.1) that displayed TPN docking profiles nearly equivalent to the TPN-sensitive mKir3.2 channel (3SYA.pdb)

Toxins 2018, 10, x FOR PEER REVIEW 11 of 17

(Figure 9C,D). The interface and putative hot spots for TPN interactions with each of these atKir Toxinschannels2019, 11were, 546 then further analyzed. 11 of 17

Figure 9. Docking TPN to homology-modelled atKir channels. A. Photograph of the small hive Figure 9. Docking TPN to homology-modelled atKir channels. A. Photograph of the small hive beetle, beetle, A. tumida, courtesy of the University of Florida, Entomology and Nematology Department. A. tumida, courtesy of the University of Florida, Entomology and Nematology Department. B. B. Cladogram tree from a multiple sequence alignment depicting the pairwise similarity and associated Cladogram tree from a multiple sequence alignment depicting the pairwise similarity and associated clustering among mouse Kir channel subunit protein sequences and the six identified atKir channel clustering among mouse Kir channel subunit protein sequences and the six identified atKir channel subunits. The neighbor-joining tree was created using the Clustal Omega program at the European subunits. The neighbor-joining tree was created using the Clustal Omega program at the European Bioinformatics Institute (EMBL-EBI) without distance corrections. C. TPN docking scores for each Bioinformatics Institute (EMBL-EBI) without distance corrections. C. TPN docking scores for each homology-modelled atKir channel. TPN docking scores to the TPN-sensitive mouse Kir1.1 (black dotted homology-modelled atKir channel. TPN docking scores to the TPN-sensitive mouse Kir1.1 (black line) and Kir3.2 channels (green dotted line) were included for benchmark comparisons. The two atKir dotted line) and Kir3.2 channels (green dotted line) were included for benchmark comparisons. The channels having TPN docking scores similar to Kir3.2 are XP_019865983.1 (red line) and XP_019865939.1 two atKir channels having TPN docking scores similar to Kir3.2 are XP_019865983.1 (red line) and (yellow line). Molecular docking was performed using ZDOCK and the TPN-13 conformer as described XP_019865939.1 (yellow line). Molecular docking was performed using ZDOCK and the TPN-13 in Methods. D. Maximal TPN docking scores from the plots in panel C are shown for comparisons in conformer as described in Methods. D. Maximal TPN docking scores from the plots in panel C are descending order. The top 5 docking scores (mean SD) are plotted for each homology-modelled atKir shown for comparisons in descending order. The± top 5 docking scores (mean ± SD) are plotted for channel with comparisons to those for mKir1.1 and mKir3.2. each homology-modelled atKir channel with comparisons to those for mKir1.1 and mKir3.2. As shown in Figure 10, the predicted interface contacts between TPN and the atKir channel As shown in Figure 10, the predicted interface contacts between TPN and the atKir channel (XP_019865983.1) outer vestibule were analogous to those between TPN-blocked mouse Kir1.1 and (XP_019865983.1) outer vestibule were analogous to those between TPN-blocked mouse Kir1.1 and Kir3.2 channels, with electrostatic contacts occurring at two adjacent subunit aspartic acid residues Kir3.2 channels, with electrostatic contacts occurring at two adjacent subunit aspartic acid residues (D113) located in the channel turret region, as well as the central “GYG” K+ selectivity filter at the pore (D113) located in the channel turret region, as well as the central “GYG” K+ selectivity filter at the entry region. Moreover, the most favored docking pose of TPN to the atKir channels was comparable pore entry region. Moreover, the most favored docking pose of TPN to the atKir channels was to the rat Kir1.1 and mouse Kir3.2 channels (cf. Figure3), where the side chain of TPN K21 occupied comparable to the rat Kir1.1 and mouse Kir3.2 channels (cf. Figure 3), where the side chain of TPN the pore selectivity filter (Figure9). Sequence comparison of the outer vestibules of TPN-sensitive K21 occupied the pore selectivity filter (Figure 9). Sequence comparison of the outer vestibules of mouse Kir channels with the 2 atKir channels (Figure9A) highlight the common presence of critical TPN-sensitive mouse Kir channels with the 2 atKir channels (Figure 9A) highlight the common acidic residues in the turret region that are necessary for high-affinity TPN binding [15,26]. These in presence of critical acidic residues in the turret region that are necessary for high-affinity TPN binding at silico[15,26]. findings These in therefore silico findings support therefore the hypothesis support that the TPNhypothesis targets that insect TPN Kir targets channels, insect where Kir channels, two Kir channels were identified as putative natural targets that can next be functionally tested with expression in the Xenopus oocyte system. Toxins 2018, 10, x FOR PEER REVIEW 12 of 17

where two atKir channels were identified as putative natural targets that can next be functionally Toxinstested2019 with, 11, 546expression in the Xenopus oocyte system. 12 of 17

Figure 10. TPN docked to a homology-modelled atKir channel. A. Sequence alignment of the outer vestibule region of TPN-sensitive mouse Kir channels and the two identified atKir channels with high TPN docking scores (see Figure8). The turret and pore regions are indicated and highlight the variable turretFigure sequences 10. TPN containingdocked to a acidic homology-modelled residues that are at necessaryKir channel. for electrostaticA. Sequence contactsalignment in TPNof the binding. outer B.vestibuleSurface region renderings of TPN-sensitive of the outer mouse vestibule Kir of channels the homology-modelled and the two identifiedatKir at channelKir channels XP_019865983.1. with high LeftTPN panel: docking top scores view where(see Figure PISA-predicted 8). The turret TPN an interfaced pore regions sites are are indicated indicated in and yellow, highlight and sitesthe withvariable predicted turret electrostaticsequences containing contacts with acidic the residues docked TPNthat peptideare necessary indicated for electrostatic in orange. Center contacts panel: in topTPN view binding. with the B. dockedSurface TPNrenderings peptide of shown the outer in red, vestibule and atKir of subunitthe homology-modelled turret residues (D113) atKir indicated.channel RightXP_019865983.1. panel: side viewLeft ofpanel: the dockedtop view TPN where with PISA-pre one atKirdicted channel TPN subunit interface removed sites toare expose indicated the pore in + regionyellow, where and TPNsites K21with ispredicted predicted electrostatic to make electrostatic contacts with contacts the withindocked the TPNatKir peptide channel indicated “GYG” in K selectivityorange. Center filter. panel: top view with the docked TPN peptide shown in red, and atKir subunit turret residues (D113) indicated. Right panel: side view of the docked TPN with one atKir channel subunit 3. Discussion removed to expose the pore region where TPN K21 is predicted to make electrostatic contacts within Thethe at resultsKir channel of this “GYG” study K highlighted+ selectivity filter. both the utility and the limitations of structure-based virtual screening for venom peptides and their biological targets. The similar TPN docking and interface profiles3. Discussion of TPN-sensitive Kir3.2 and homology-modelled Kir1.1 channels provide further evidence for theThe reliability results of of this molecular study highlighted docking as both a first-line the utility screening and the limitations tool for TPN-sensitive of structure-based Kir channels. virtual Thescreening unexpected for venom docking peptides results and that their predicted biological TPN targets. block of The mKir4.1 similar channels TPN docking indicated and the interface virtual screeningprofiles of methods TPN-sensitive are suffi Kir3.2ciently and sensitive homology-modelled to generate “false Kir1.1 positive” channels interactions, provide andfurther thus evidence have the potentialfor the reliability to identify of novel molecular venom docking targets as in a silico first-l forine subsequent screening tool validation for TPN-sensitive testing in vitro Kir. channels. Moreover, theseThe unexpected finding indicated docking mKir4.1 results channels that predicted form a favorableTPN block outer of mKir4.1 vestibule channels receptor indicated for TPN interactionsthe virtual (i.e.,screening shape methods complementarity), are sufficiently but lacksensitive key interfaceto generate contact “false sitespositive” necessary interactions, for high-a andffi thusnity have TPN bindingthe potential and channel to identify block. novel This venom observation targets may in silico aid future for subsequent peptide re-engineering validation testing efforts, in takingvitro. intoMoreover, account these the unique finding surface indicated chemistry mKir4.1 of thechannels Kir4.1 form outer avestibule favorable as outer either vestibule a homo-tetramer receptor for or a hetero-tetramerTPN interactions assembled (i.e., shape with complementarity), other Kir channel but subunits lack key (e.g.,interface Kir4.2 contact or Kir5.1). sites necessary for high- affinityThe TPN primary binding discovery and channel deploying block. this computationalThis observation approach may aid is thefuture novel peptide finding re-engineering that insect Kir channels,efforts, taking specifically into account certain Kir the channels unique expressedsurface ch inemistryA. tumida of thethat Kir4.1 are distantly outer vestibule related to mammalianas either a epithelialhomo-tetramer Kir channels, or a hetero-tetramer may be the naturalassembled targets with ofother the Kir TPN channel venom subunits peptide (e.g., that Kir4.2 aid in or honeybee Kir5.1). defense by lethally blocking K+ transport processes in insect predators. This hypothesis, assessed initially and supported using the virtual screening approach, can now focus on validation testing Toxins 2019, 11, 546 13 of 17 of the 2 specific atKir channels that were identified as potentially TPN-sensitive using heterologous expression systems and functional assays. This role in bee defense would seemingly be more favorable to drive adaptive evolution of the TPN gene in A. mellifera, given insect predator encounters are expected to significantly outnumber encounters with mammalian predators. Other insect predators and their Kir channels of interest, including wasps and hornets, could similarly be screened using the structure-based molecular docking approach described here. Six putative atKir channels were identified in this study, of those by comparison, five Kir channel subunit genes have been reported for the Aedes aegypti genome and three in Drosophila melanogaster [33,34]. The Aedes Kir channels are important for regulating secretion of K+ in Malpighian tubules and have emerged as new targets for insecticide development and mosquito control [35]. The role of atKir channels in the physiology of the small hive beetle is not currently known, but may similarly regulate transepithelial secretion of K+ from hemolymph to urine for fluid homeostasis. There are inherent assumptions with the in silico structural modelling of atKir channels that should be acknowledged, including less structural conservation in the transmembrane domains and large C-terminal domain and how this may affect the outer vestibule structure and TPN docking results. There also is the possible scenario that native atKir channels are hetero-tetramers and would similarly impact the TPN binding landscape. The TPN conformer used for rigid-body docking was also selected based on optimal conformer docking to the mammalian Kir channels (i.e., TPN-13). It remains possible that other TPN conformations preferentially dock to insect Kir channels, where incorporating NMR ensemble docking protocols and scoring would help obviate this current bias [36]. However, despite the absence of a high-resolution TPN–Kir channel complex, the virtual screening and docking results for TPN-sensitive Kir channels consistently point to a conserved mechanism for channel block, where key electrostatic contacts with multiple channel turrets and the vestibule ring region positions the C-terminal lysine side chain of TPN to occupy the channel pore and block conduction with high-affinity binding. The novel in silico results described here establish a solid rationale for follow-up of in vitro validation assays that otherwise would not have been considered or tested. This new research direction will further address the reliability of the structural models, where future refinements to the virtual screening protocol can be introduced along with any emergent or new structural details of a high-resolution TPN–Kir channel complex. Screening and testing venom peptide interactions in vitro with other insect ion channel targets encountered in nature is impractical and an unlikely undertaking. The computational screening approach described here for hypothesis testing of TPN interactions with the atKir channels highlights a more practical approach to identifying potential targets in silico that can then be tested in vitro. Applying this approach to a wider range of homology-modelled K+ channels, both homo- and hetero-tetrameric assemblies, is very feasible and could accelerate the discovery process of venom peptide targets encountered in nature.

4. Materials and Methods

4.1. Ion Channel Structures and Homology Modelling Three high-resolution crystal structures of Kir channels were used for computationally screening venom peptide interactions: the Gallus gallus Kir2.2 channel (3JYC.pdb), and the Mus musculus Kir3.2 channel in both closed-state and pre-opened conformations (3SYA.pdb and 4KFM.pdb, respectively). For homology-modelled Kir channels, the Kir2.2 channel served as the structural template where domain modelling was restricted to the outer vestibule region (~50 amino acids) to produce a chimeric Kir channel structure using the Swiss-Model homology-modelling server as described previously [7]. The homology-modelled Kir channel subunit was then assembled as a tetramer based on the macromolecular I4 space group determined for the assembled cKir2.2 tetramer using the PDBe PISA program (Protein Interfaces, Surfaces, and Assemblies: http://pdbe.org/pisa/). All structural renderings were performed using PyMol (v1.6, Schrödinger, New York, NY, USA). Toxins 2019, 11, 546 14 of 17

4.2. Computational Docking of TPN to Kir Channel Structures All NMR solution structures of TPN (1TER.pdb) [17] were initially used for in silico docking to the Kir3.2 channel outer vestibule structures using ZDOCK 3.0.2 [25]. ZDOCK performs rigid-body searches of docking orientations between the TPN conformer and the Kir channel outer vestibule, generating 2000 complexes for each Kir channel ranked by an initial-stage scoring function that computes optimized pairwise shape complementarity, electrostatic energies, and a pairwise statistical energy potential for interface atomic contacts energies [37]. The calculated and ranked TPN docking scores were then quantitatively compared among each Kir channel tested as previously reported [7].

4.3. Kir Channel–TPN Interface Analysis To evaluate the predicted molecular contacts between the docked TPN peptide and Kir channels, the Cluspro2.0 program was used for refined docking and RMSD greedy clustering to identify the energetically-favored complex for subsequent interface analysis [38]. The predicted interface contacts were then determined using the PDBePISA program [28,39]. PISA identifies interface contacts based on physical–chemical models of macromolecular interactions and chemical thermodynamics identified within the docked structural complexes.

4.4. Kir Channel Expression in Xenopus Oocytes

To test TPNQ sensitivity of the Kir4.1 channel in vitro, Xenopus oocytes were injected with cRNA transcribed in vitro by T7 RNA polymerase (mMessage mMachine, Ambion, Austin, TX, USA) from a linearized pCMV6 vector with the mouse Kir4.1 cDNA containing a Myc-DDK tag at the C-terminus (NM_001039484, Origene Technologies, Inc., Rockville, MD, USA). For a positive assay control, some oocytes were injected with cRNA encoding the rat Kir1.1 channel of which >95% was blocked by 100 nM TPNQ. Oocytes were maintained for 3–5 days at 17–19 ◦C prior to electrophysiological recording in the following solution (in mM): 82.5 NaCl, 2.5 KCl, 1.0 CaCl2, 1.0 MgCl2, 1.0 NaHPO4, 5.0 HEPES, 2.5 Na pyruvate, at pH 7.5 (NaOH), with 5% heat-inactivated horse serum. Single-stage V–VI oocytes were isolated as described previously by collagenase digestion of ovarian lobes (Xenopus 1, Dexter, MI, USA) [40].

4.5. Two-Electrode Voltage Clamp Recording from Xenopus Oocytes Macroscopic mKir4.1 and rKir1.1 channel currents were recorded by two-electrode voltage clamp recording techniques where oocytes were initially superfused with the following bath solution (in mM): 98 NaCl, 1 MgCl2, and 5 HEPES at pH 7.5 (NaOH). Glass electrodes having tip resistances of 0.8–1.0 MΩ were used to clamp oocytes at a holding membrane potential of 80 mV. After establishing a baseline − holding current, the bath solution was changed to a “high K+ solution” that was comprised of an equal molar substitution of NaCl for KCl. For mKir4.1 recordings, the extracellular K+ concentration was 98 mM, and for rKir1.1 recordings, the concentration was 20 mM K+. These concentrations were determined empirically to control for peak K+ current amplitudes, and were attributed to diﬀerences in Kir4.1 vs Kir1.1 channel expression, single-channel conductance, and single-channel open time probability. From the 80 mV holding potential, large inward K+ currents were evoked and − were due to the expressed Kir channels, as un-injected oocytes yielded inward currents of <100 nA (data not shown). + Rapid application and washout of 100 nM TPNQ or 1 mM BaCl2 (dissolved in high K solutions) was performed as described previously [40]. TPNQ (lyophilized solid, Tocris Bioscience, Bristol, UK) was initially dissolved in water as a 100 µM stock solution, then aliquoted and stored at 23 C until − ◦ used on the day of the experiment by diluting in the high K+ electrophysiological recording solution. Voltage ramps from 80 to +20 mV (200 ms in duration) were evoked periodically to assess the − inward rectiﬁcation characteristics of Kir channel currents during changes in the recording solutions. All recordings were performed at room temperature (21–23 ◦C). The membrane currents were digitized, Toxins 2019, 11, 546 15 of 17 stored, and later analyzed using an Analog-to-Digital acquisition board and PC computer (pCLAMP software, Digidata 1200 acquisition system, Axon Instruments, Foster City, CA, USA). Experiments were replicated in 7 oocytes.

Funding: This research received no external funding. The Article Processing Charges were funded by the University of South Florida Morsani College of Medicine. Conﬂicts of Interest: The author declares no conﬂicts of interest.

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