Peer-reviewedCC BY-NC-ND 4.0Scientific Reports
Identification of a natural product derived NaV1.5 sodium channel modulator through integrated machine learning and molecular modeling
Related
- Identification of esculin as a direct modulator of IGF1 in cervical cancer with integrated computational and experimental studies
- Machine Learning‐Guided Identification of Madecassoside as a Potential RAD51 Modulator That Sensitizes Breast Cancer Cells to Cisplatin
- In silico characterization of Desmodium gangeticum compounds as dual modulators of MAO-B and 5-HT2A in Parkinson’s disease: an integrated approach combining molecular docking, ADMET profiling, MM-GBSA, QSAR modeling, and molecular dynamics simulation
- Integrated machine learning, pharmacophore screening, and structure-based computational approaches for the identification of novel JAK3 inhibitors
- Identification of phillyrin as a PPAR-γ ligand through network pharmacology and molecular modeling
BibTeX
@article{khosravi2026identification,
title = {{Identification of a natural product derived NaV1.5 sodium channel modulator through integrated machine learning and molecular modeling}},
author = {Sina Khosravi and Fatemeh Yarmohammadi and Mahdi Hatamipour and Benyamin Hoseini and Mojgan Nejabat and Seyed Ali Farokh and Farzin Hadizadeh and Gholamreza Karimi},
journal = {Scientific Reports},
year = {2026},
month = oct,
doi = {10.1038/s41598-026-76489-7},
url = {https://www.nature.com/articles/s41598-026-76489-7},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Identification of a natural product derived NaV1.5 sodium channel modulator through integrated machine learning and molecular modeling
AU - Sina Khosravi
AU - Fatemeh Yarmohammadi
AU - Mahdi Hatamipour
AU - Benyamin Hoseini
AU - Mojgan Nejabat
AU - Seyed Ali Farokh
AU - Farzin Hadizadeh
AU - Gholamreza Karimi
PY - 2026
DA - 2026/10/25
JO - Scientific Reports
DO - 10.1038/s41598-026-76489-7
UR - https://www.nature.com/articles/s41598-026-76489-7
SN - 2045-2322
ER -