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Ligand-based pharmacophore modeling for the discovery of Na[sub]V1.7 inhibitors
ID
Piga, Martina
(
Author
),
ID
Lukacs, Peter
(
Author
),
ID
Pesti, Krisztina
(
Author
),
ID
Várady, György
(
Author
),
ID
Varga, Zoltán
(
Author
),
ID
Zidar, Nace
(
Author
),
ID
Tomašič, Tihomir
(
Author
)
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MD5: 4C29309E161F7863E2A70C05D11A6F1D
URL - Source URL, Visit
https://link.springer.com/article/10.1007/s10822-026-00898-z
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Abstract
Voltage-gated sodium channel Na$_v$1.7 is a key mediator of electrical excitability and signal transmission in peripheral nociceptors and has emerged as a highly attractive therapeutic target for the development of novel analgesic agents. However, the development of selective Na$_v$1.7 inhibitors has been characterized by significant challenges, with repeated failures in clinical trials despite encouraging preclinical data. In this study, we developed and validated a series of ligand-based pharmacophore models (LBPMs) that can be useful for the discovery of novel Na$_v$1.7 inhibitors with improved selectivity profiles. Using the VGSC database as our primary data source, we focused on sulfonamide-based inhibitors targeting the voltage-sensing domain IV (VSD-IV). Validation against active compounds and decoys demonstrated that most models achieved good discrimination performance with high areas under the curve (AUC) and strong enrichment factors. External validation using 22 inhibitors extracted from recent literature confirmed the models’ capability to identify novel Na$_v$1.7 inhibitors. Virtual screening of 3 million commercially available compounds retrieved promising hits and known inhibitors, with molecular docking studies revealing binding modes consistent with established sulfonamide-based inhibitors. Experimental validation identified one compound with measurable selectivity for Na$_v$1.7 over Na$_v$1.5, providing preliminary support for the utility of the developed virtual screening workflow. In parallel, we developed Na$_v$1.5 LBPMs to assess selectivity profiles and minimize potential cardiotoxic effects. Overall, our findings provide valuable computational tools and structural insights for the rational design of selective Na$_v$1.7 inhibitors, offering important starting points for developing analgesics with reduced off-target effects.
Language:
English
Keywords:
NaV1.7 inhibitors
,
pharmacophore model
,
selectivity
,
virtual screening
,
voltage-gated sodium channel
Work type:
Article
Typology:
1.01 - Original Scientific Article
Organization:
FFA - Faculty of Pharmacy
Publication status:
Published
Publication version:
Version of Record
Year:
2026
Number of pages:
15 str.
Numbering:
Vol. 40, art. 198
PID:
20.500.12556/RUL-188594
UDC:
615.4:54
ISSN on article:
1573-4951
DOI:
10.1007/s10822-026-00898-z
COBISS.SI-ID:
287230979
Publication date in RUL:
24.09.2026
Views:
137
Downloads:
28
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Record is a part of a journal
Title:
Journal of computer-aided molecular design
Shortened title:
J. comput.-aided mol. des.
Publisher:
Kluwer
ISSN:
1573-4951
COBISS.SI-ID:
513182745
Licences
License:
CC BY 4.0, Creative Commons Attribution 4.0 International
Link:
http://creativecommons.org/licenses/by/4.0/
Description:
This is the standard Creative Commons license that gives others maximum freedom to do what they want with the work as long as they credit the author.
Secondary language
Language:
Slovenian
Keywords:
zaviralci NaV1.7
,
farmakoforni model
,
selektivnost
,
virtualni presejalni test
,
napetostno odvisen natrijev kanal
,
farmacevtska kemija
Projects
Funder:
ARIS - Slovenian Research and Innovation Agency
Project number:
P1-0208
Name:
Farmacevtska kemija: načrtovanje, sinteza in vrednotenje učinkovin
Funder:
Other - Other funder or multiple funders
Project number:
PD143055
Name:
National Research, Development and Innovation Office
Acronym:
NKFIH
Funder:
Other - Other funder or multiple funders
Project number:
FK147267
Name:
National Research, Development and Innovation Office
Acronym:
NKFIH
Funder:
Other - Other funder or multiple funders
Project number:
2025-1.2.4-TÉT-2025-00007
Name:
Hungarian–Slovenian bilateral grant
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