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Complex approach for analysis of snake venom α-neurotoxins binding to HAP, the high-affinity peptide
Snake venom α-neurotoxins, invaluable pharmacological tools, bind with high affinity to distinct subtypes of nicotinic acetylcholine receptor. The combinatorial high-affinity peptide (HAP), homologous to the C-loop of α1 and α7 nAChR subunits, binds biotinylated α-bungarotoxin (αBgt) with nanomolar...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7052197/ https://www.ncbi.nlm.nih.gov/pubmed/32123252 http://dx.doi.org/10.1038/s41598-020-60768-y |
Sumario: | Snake venom α-neurotoxins, invaluable pharmacological tools, bind with high affinity to distinct subtypes of nicotinic acetylcholine receptor. The combinatorial high-affinity peptide (HAP), homologous to the C-loop of α1 and α7 nAChR subunits, binds biotinylated α-bungarotoxin (αBgt) with nanomolar affinity and might be a protection against snake-bites. Since there are no data on HAP interaction with other toxins, we checked its binding of α-cobratoxin (αCtx), similar to αBgt in action on nAChRs. Using radioiodinated αBgt, we confirmed a high affinity of HAP for αBgt, the complex formation is supported by mass spectrometry and gel chromatography, but only weak binding was registered with αCtx. A combination of protein intrinsic fluorescence measurements with the principal component analysis of the spectra allowed us to measure the HAP-αBgt binding constant directly (29 nM). These methods also confirmed weak HAP interaction with αCtx (>10000 nM). We attempted to enhance it by modification of HAP structure relying on the known structures of α-neurotoxins with various targets and applying molecular dynamics. A series of HAP analogues have been synthesized, HAP[L9E] analogue being considerably more potent than HAP in αCtx binding (7000 nM). The proposed combination of experimental and computational approaches appears promising for analysis of various peptide-protein interactions. |
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