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Research Articles

Insights into the binding mode and functional components of the analgesic-antitumour peptide from Buthus martensii Karsch to human voltage-gated sodium channel 1.7 based on dynamic simulation analysis

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Pages 1868-1879 | Received 28 Dec 2018, Accepted 09 May 2019, Published online: 22 May 2019
 

Abstract

Voltage-gated sodium (Nav) channels are transmembrane proteins composed of four homologous domains (DI–DIV) that play important roles in membrane excitability in neurons and muscles. Analgesic-antitumour peptide (AGAP) is a neurotoxin from the scorpion Buthus martensii Karsch, and has been shown to exert analgesic effect by binding on site 4 of human Nav1.7 (hNav1.7). Mechanistic details about this binding, however, remain unclear. To address this issue, we compared the binding modes of AGAP/AGAPW38G/AGAPW38F and the hNav1.7 voltage-sensing domain on DII (VSD2hNav1.7) using homology modeling, molecular docking, molecular dynamics simulation and steered molecular dynamics. Results revealed the key role of tryptophan at position 38 on the binding of AGAP to VSD2hNav1.7. Pivotal roles are played also by residues on the β-turn and negatively charged residues at the C-terminal. We further show that electrostatic interaction is the main contributor to the binding free energy of the complex. Agreement between our computational simulation findings and prior experimental data supports the accuracy of the described mechanism. Accordingly, these results can provide valuable information for designing potent toxin analgesics targeting hNav1.7 with high affinity.

Communicated by Ramaswamy H. Sarma

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work was supported by the National Natural Science Foundation of China under Grant No. 81473432; Young Teachers’ Career Development Support Plan from Shenyang Pharmaceutical University under Grant No. ZQN2016013 and Innovation Talent support Program for Colleges and Universities in Liaoning province under Grant No. LR2016076.

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