An integrated in silico screening framework for discovering novel antifungal peptide candidates using artificial intelligence and molecular docking
- DOI
- 10.1016/j.jmgm.2026.109543
- Published
- 2026-11
- Container
- Journal of Molecular Graphics and Modelling
- Publisher
- Elsevier BV
- Open access
- unknown
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Cite this work
BibTeX
@article{allodium:10.1016/j.jmgm.2026.109543,
title = {An integrated in silico screening framework for discovering novel antifungal peptide candidates using artificial intelligence and molecular docking},
author = {Hiroyuki Hamada and Yang Yiqi and Takeshi Zendo and Taizo Hanai},
year = {2026},
journal = {Journal of Molecular Graphics and Modelling},
doi = {10.1016/j.jmgm.2026.109543},
url = {https://doi.org/10.1016/j.jmgm.2026.109543}
}RIS
TY - JOUR TI - An integrated in silico screening framework for discovering novel antifungal peptide candidates using artificial intelligence and molecular docking AU - Hiroyuki Hamada AU - Yang Yiqi AU - Takeshi Zendo AU - Taizo Hanai PY - 2026 JO - Journal of Molecular Graphics and Modelling DO - 10.1016/j.jmgm.2026.109543 UR - https://doi.org/10.1016/j.jmgm.2026.109543 ER -
APA
Hamada, H., Yiqi, Y., Zendo, T., & Hanai, T. (2026). An integrated in silico screening framework for discovering novel antifungal peptide candidates using artificial intelligence and molecular docking. Journal of Molecular Graphics and Modelling. https://doi.org/10.1016/j.jmgm.2026.109543
Source records
- crossref · retrieved 2026-09-27T15:58:46.938Z