Refining the NaV1.7 pharmacophore of a class of venom-derived peptide inhibitors via a combination of in silico screening and rational engineering.

Ion channels are among the main targets of venom peptides. Extensive functional screening has identified a number of these peptides as modulators of the voltage-gated sodium channel subtype NaV1.7, a potential target for the treatment of chronic pain. In this study, we used a bioinformatic approach that can automatically identify NaV1.7 gating modifier toxins from sequence information alone. The method further enables the incorporation of evolutionarily accessible sequence space in structure-activity relationship studies. The in silico method identified a putative NaV1.7 inhibitor, μ-theraphotoxin Cg4a, which we produced recombinantly and confirmed as a NaV1.7 inhibitor. Using structural and mutagenesis studies, we propose an improved definition of the pharmacophore of this class of NaV1.7 inhibitors, aiding future in silico screening and classification of NaV1.7 inhibitors.