Potency- and Selectivity-Enhancing Mutations of Conotoxins for Nicotinic Acetylcholine Receptors Can Be Predicted Using Accurate Free-Energy Calculations

Abstract

Nicotinic acetylcholine receptor (nAChR) subtypes are key drug targets, but it is challenging to pharmacologically differentiate between them because of their highly similar sequence identities. Furthermore, α-conotoxins (α-CTXs) are naturally selective and competitive antagonists for nAChRs and hold great potential for treating nAChR disorders. Identifying selectivity-enhancing mutations is the chief aim of most α-CTX mutagenesis studies, although doing so with traditional docking methods is difficult due to the lack of α-CTX/nAChR crystal structures. Here, we use homology modeling to predict the structures of α-CTXs bound to two nearly identical nAChR subtypes, α3β2 and α3β4, and use free-energy perturbation (FEP) to re-predict the relative potency and selectivity of α-CTX mutants at these subtypes. First, we use three available crystal structures of the nAChR homologue, acetylcholine-binding protein (AChBP), and re-predict the relative affinities of twenty point mutations made to the α-CTXs LvIA, LsIA, and GIC, with an overall root mean square error (RMSE) of 1.08 ± 0.15 kcal/mol and an R2 of 0.62, equivalent to experimental uncertainty. We then use AChBP as a template for α3β2 and α3β4 nAChR homology models bound to the α-CTX LvIA and re-predict the potencies of eleven point mutations at both subtypes, with an overall RMSE of 0.85 ± 0.08 kcal/mol and an R2 of 0.49. This is significantly better than the widely used molecular mechanics—generalized born/surface area (MM-GB/SA) method, which gives an RMSE of 1.96 ± 0.24 kcal/mol and an R2 of 0.06 on the same test set. Next, we demonstrate that FEP accurately classifies α3β2 nAChR selective LvIA mutants while MM-GB/SA does not. Finally, we use FEP to perform an exhaustive amino acid mutational scan of LvIA and predict fifty-two mutations of LvIA to have greater than 100X selectivity for the α3β2 nAChR. Our results demonstrate the FEP is well-suited to accurately predict potency- and selectivity-enhancing mutations of α-CTXs for nAChRs and to identify alternative strategies for developing selective α-CTXs.

Alchemical Free Energy Calculations to Investigate Protein–Protein Interactions: the Case of the CDC42/PAK1 Complex

“… 47 In our case, we have also found that the MM/GBSA method returned a larger error in the quantification of the effect of each mutation, even when multiple snapshots were considered from MD trajectories of the wt and mutated systems. As in other reported studies, 65 , 70 in our case, the alchemical free energy calculations outperformed MM/GBSA, with an accuracy that can assist in the design of mutagenesis experiments. The alchemical free energy calculation is thus a powerful method in the context of studying protein–protein interactions too.…”

Marine natural products

“…651 Homology modelling combined with free-energy perturbation has been used to classify nAChR selective a4/7-conotoxin LvIA mutants, suggesting it outperforms the more commonly used molecular mechanics-generalised born/surface area method as a technique to predict potency-and selectivity-enhancing mutations of a-conotoxins. 652 Investigation of engineered variants of aconotoxin LvIB identied the inuence of residues Gln141, Asn184 and Lys186 on a7 nAChR species selectivity. 653 Xylenelinked cysteine [2,4] modied analogues of a-conotoxin TxIB have enhanced serum stability and show selectivity towards a6/ a3b2b3 nAChR's 654 while an alkyne variant, replacing cysteine [1,3], of a-conotoxin Vc1.1 failed to inhibit a7 and ha9a10 nAChR's but was a GABA B R selective agonist and also reversed mechanical allodynia in vivo.…”

Marine Origin Ligands of Nicotinic Receptors: Low Molecular Compounds, Peptides and Proteins for Fundamental Research and Practical Applications

“…An example is the application of the ToxDock docking algorithm for the successful design of α-conotoxin GID analogs with reduced affinity for its second target [ 157 ]. Another example is the use of free perturbation energy calculations to perform an amino acid mutation scanning of α-conotoxin LvIA and predict mutations resulting in the increase of its selectivity towards α3β2 nAChR [ 158 ].…”