Alpha-conotoxin analogs with additional positive charge show increased selectivity towards Torpedo californica and some neuronal subtypes of nicotinic acetylcholine receptors.

Alpha-conotoxins from Conus snails are indispensable tools for distinguishing various subtypes of nicotinic acetylcholine receptors (nAChRs), and synthesis of alpha-conotoxin analogs may yield novel antagonists of higher potency and selectivity. We incorporated additional positive charges into alpha-conotoxins and analyzed their binding to nAChRs. Introduction of Arg or Lys residues instead of Ser12 in alpha-conotoxins GI and SI, or D12K substitution in alpha-conotoxin SIA increased the affinity for both the high- and low-affinity sites in membrane-bound Torpedo californica nAChR. The effect was most pronounced for [D12K]SIA with 30- and 200-fold enhancement for the respective sites, resulting in the most potent alpha-conotoxin blocker of the Torpedo nAChR among those tested. Similarly, D14K substitution in alpha-conotoxin [A10L]PnIA, a blocker of neuronal alpha7 nAChR, was previously shown to increase the affinity for this receptor and endowed [A10L,D14K]PnIA with the capacity to distinguish between acetylcholine-binding proteins from the mollusks Lymnaea stagnalis and Aplysia californica. We found that [A10L,D14K]PnIA also distinguishes two alpha7-like anion-selective nAChR subtypes present on identified neurons of L. stagnalis: [D14K] mutation affected only slightly the potency of [A10L]PnIA to block nAChRs on neurons with low sensitivity to alpha-conotoxin ImI, but gave a 50-fold enhancement of blocking activity in cells with high sensitivity to ImI. Therefore, the introduction of an additional positive charge in the C-terminus of alpha-conotoxins targeting some muscle or neuronal nAChRs made them more discriminative towards the respective nAChR subtypes. In the case of muscle-type alpha-conotoxin [D12K]SIA, the contribution of the Lys12 positive charge to enhanced affinity towards Torpedo nAChR was rationalized with the aid of computer modeling.