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BMC Syst Biol. 2017 Feb 24;11(1):28. doi: 10.1186/s12918-016-0382-0.

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

Author information

1
Bioinformatics Unit, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy. dimos.kapetis@gmail.com.
2
Neuroalgology Unit, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy. dimos.kapetis@gmail.com.
3
Neuroalgology Unit, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy.
4
Present address: San Raffaele Scientific Institute and Vita-Salute University, Milan, Italy.
5
Department of Neurology, Yale University School of Medicine, New Haven, USA.
6
Center for Neuroscience and Regeneration Research, Yale University School of Medicine, New Haven, USA.
7
Bioinformatics Unit, IRCCS Foundation "Carlo Besta" Neurological Institute, Milan, Italy.
8
Department of Clinical Genetics, Maastricht University Medical Center, Maastricht, The Netherlands.
9
Department of Knowledge Engineering, Maastricht University, Maastricht, The Netherlands.
10
Department of Neurology, Maastricht University Medical Center, Maastricht, The Netherlands.
11
Department of Neurology, Spaarne Hospital, Hoofddorp, The Netherlands.
12
Laboratory of Excellence Ion Channel Science and Therapeutics, Institute of Molecular and Cellular Pharmacology, CNRS UMR7275 & University of Nice-Sophia Antipolis, Valbonne, France.

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 (CC ct ), closeness (C ct ), and eccentricity (E ct ), and calculated their variation (Δ value  = mutant value -WT value ). Pathogenic NaV1.7 mutations showed significantly higher variation of |ΔB ct | compared to benign variants and polymorphisms. Using the cut-off value ±0.26 calculated by receiver operating curve analysis, we found that ΔB 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 |ΔB ct | value as a potential in-silico marker.

KEYWORDS:

Network analysis; Neuropathic pain; Sodium channel; Structural modeling

PMID:
28235406
PMCID:
PMC5324268
DOI:
10.1186/s12918-016-0382-0
[Indexed for MEDLINE]
Free PMC Article

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