Developing a comparative docking protocol for the prediction of peptide selectivity profiles: investigation of potassium channel toxins

Abstract

During the development of selective peptides against highly homologous targets, a reliable tool is sought that can predict information on both mechanisms of binding and relative affinities. These tools must first be tested on known profiles before application on novel therapeutic candidates. We therefore present a comparative docking protocol in HADDOCK using critical motifs, and use it to "predict" the various selectivity profiles of several major αKTX scorpion toxin families versus K(v)1.1, K(v)1.2 and K(v)1.3. By correlating results across toxins of similar profiles, a comprehensive set of functional residues can be identified. Reasonable models of channel-toxin interactions can be then drawn that are consistent with known affinity and mutagenesis. Without biological information on the interaction, HADDOCK reproduces mechanisms underlying the universal binding of αKTX-2 toxins, and K(v)1.3 selectivity of αKTX-3 toxins. The addition of constraints encouraging the critical lysine insertion confirms these findings, and gives analogous explanations for other families, including models of partial pore-block in αKTX-6. While qualitatively informative, the HADDOCK scoring function is not yet sufficient for accurate affinity-ranking. False minima in low-affinity complexes often resemble true binding in high-affinity complexes, despite steric/conformational penalties apparent from visual inspection. This contamination significantly complicates energetic analysis, although it is usually possible to obtain correct ranking via careful interpretation of binding-well characteristics and elimination of false positives. Aside from adaptations to the broader potassium channel family, we suggest that this strategy of comparative docking can be extended to other channels of interest with known structure, especially in cases where a critical motif exists to improve docking effectiveness.

Keywords: HADDOCK; Kv1.1; Kv1.2; Kv1.3; comparative docking; protein-protein docking; scorpion toxins; selectivity; α-KTx.

Figure 1

Exterior view of the K_v1 channels, highlighting the differences in morphology and residue types. Sidechains of exposed basic (blue), acidic (red) and aromatic residues (green) have been given coloured spheres to indicate the nature of potential interactions. Surface calculated by MSMS at 3 Å⁻² density and 1.5 Å probe radius and rendered with ambient occlusion by Tachyon in VMD before post-processing.

Figure 2

Comparison between constrained-and blind-docking data for two members of αKTX-2, margatoxin (MgTX, 1MTX.pdb) and noxioustoxin (NTX, 1SXM.pdb). Constrained docking results are presented in the 1st and 3rd rows, while blind docking results are in rows 2 and 4. Colours red, green and blue correspond to K_v1.1, K_v1.2, and K_v1.3 complexes, respectively. Numbers 1–10 above the dots indicate the rank of the complex at that configuration.

Figure 3

Superimposed chosen Kv-docked complexes of the family-2 toxins from constrained results. Colours red, green and blue correspond to K_v1.1, K_v1.2, and K_v1.3 complexes, respectively. Labelled residues indicate charged elements that interact (< 5 Å) with the channel in either all three cases (black) or two out of three cases (grey). Isolated charge contacts are labelled by colour of complex. Numbers after labels indicate the actual complex selected as sorted by HADDOCK energy, in the same order. Other interacting residues have been left unlabelled for simplicity.

Figure 4

Constrained-docking results for αKTx-4 member tityustoxin-K α vs. K_v1.1 (red), K_v1.2 (green) and K_v1.3 (blue). (a–c) HADDOCK Energy plots against pore-Lys distance and β-sheet RMSD with 2A9H.pdb. (d–f) Selected complexes are shown as a visual aid to docked conformations.

Figure 5

Blind docking data for three family-3 toxins. Colours red, green and blue correspond to K_v1.1, K_v1.2, and K_v1.3 complexes, respectively. Subscripts of the toxin show the source input ensembles used in docking. (a–i) Energy, RMSD and lysine insertion for toxin and channel pairs; (j–l) Superimposed images of chosen complex according to lowest HADDOCK energy with correct lysine-insertion. Labelled residues indicate charged elements that interact with the channel in all three cases (< 5 Å), although not necessarily at the same location. Pore-inserting lysine is unlabelled for simplicity.

Figure 6

Selected complexes from K_v1.2-selective members of αKTx-6, providing different views of the interaction. The toxin and channel have been displayed with spheres and surfaces to emphasise the spatial volume of the interaction, and an overview of peripheral contacts is presented. (g) Hypothetical model to explain a maximum block of <100% in this!family.

Figure 7

Comparison of docking modes between αKTx-6 HsTX1, αKTx-3 ADWX-1, and combinatorial toxin moka-1 vs. K_v1.1 (red), K_v1.2 (green) and K_v1.3 (blue). Toxin residues in contact with the channel have been shown in coloured spheres to visualise the spatial properties in binding.

Figure 8

Constrained-docking data for twelve toxins from various families, grouped according to experimental phenotype. The colours red, greenand blue represent docking versus K_v1.1, 1.2 and 1.3, respectively. The location of one or more major clusters that are potential models of the nativecomplex is additionally shaded yellow to aid interpretation. Its relative energy with repect to the non-binding background is potentially an indicatorof affinity.