Network topology of NaV1.7 mutations in sodium channel-related painful disorders

Dimos Kapetis*, Jenny Sassone, Yang Yang, Barbara Galbardi, Markos N. Xenakis, Ronald L. Westra, Radek Szklarczyk, Patrick Lindsey, Catharina G. Faber, Monique Gerrits, Ingemar S. J. Merkies, Sulayman D. Dib-Hajj, Massimo Mantegazza, Stephen G. Waxman, PROPANE Study Grp, Hubertus J.M. Smeets, Giuseppe Lauria

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

22 Citations (Web of Science)

Abstract

Background: Gain-of-function mutations in SCN9A gene that encodes the voltage-gated sodium channel NaV1.7 have been associated with a wide spectrum of painful syndromes in humans including inherited erythromelalgia, paroxysmal extreme pain disorder and small fibre neuropathy. These mutations change the biophysical properties of NaV1.7 channels leading to hyperexcitability of dorsal root ganglion nociceptors and pain symptoms. There is a need for better understanding of how gain-of-function mutations alter the atomic structure of Nav1.7.

Results: We used homology modeling to build an atomic model of NaV1.7 and a network-based theoretical approach, which can predict interatomic interactions and connectivity arrangements, to investigate how pain-related NaV1.7 mutations may alter specific interatomic bonds and cause connectivity rearrangement, compared to benign variants and polymorphisms. For each amino acid substitution, we calculated the topological parameters betweenness centrality (B-ct), degree (D), clustering coefficient (CCct), closeness (C-ct), and eccentricity (E-ct), and calculated their variation (Delta(value) = mutant (value)-WT (value)). Pathogenic NaV1.7 mutations showed significantly higher variation of |Delta B-ct| compared to benign variants and polymorphisms. Using the cut-off value +/- 0.26 calculated by receiver operating curve analysis, we found that Delta B-ct correctly differentiated pathogenic NaV1.7 mutations from variants not causing biophysical abnormalities (nABN) and homologous SNPs (hSNPs) with 76% sensitivity and 83% specificity.

Conclusions: Our in-silico analyses predict that pain-related pathogenic NaV1.7 mutations may affect the network topological properties of the protein and suggest |Delta B-ct| value as a potential in-silico marker.

Original languageEnglish
Article number28
Number of pages16
JournalBMC Systems Biology
Volume11
DOIs
Publication statusPublished - 24 Feb 2017

Keywords

  • Sodium channel
  • Neuropathic pain
  • Structural modeling
  • Network analysis
  • TRANSFER-RNA SYNTHETASE
  • MOLECULAR-DYNAMICS SIMULATIONS
  • OF-FUNCTION MUTATIONS
  • NA(V)1.7 MUTATION
  • PRIMARY ERYTHERMALGIA
  • ELECTROPHYSIOLOGICAL PROPERTIES
  • RESPONSIVE ERYTHROMELALGIA
  • NEURON HYPEREXCITABILITY
  • STRUCTURE PREDICTION
  • SLOW-INACTIVATION

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