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.

Keywords: Q2 2025