Generative design and computational characterization of pyrazoline-based EGFR kinase inhibitor candidates.
- DOI
- 10.1016/j.jmgm.2026.109631
- Published
- 2026 Oct 26
- Container
- Journal of molecular graphics & modelling
- Publisher
- Not recorded
- Open access
- no
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Cite this work
BibTeX
@article{allodium:10.1016/j.jmgm.2026.109631,
title = {Generative design and computational characterization of pyrazoline-based EGFR kinase inhibitor candidates.},
author = {Bhendarkar K and Khedekar P and Islam MA and Wanode D and Ambatkar M and Chikhale R},
year = {2026},
journal = {Journal of molecular graphics \& modelling},
doi = {10.1016/j.jmgm.2026.109631},
url = {https://doi.org/10.1016/j.jmgm.2026.109631}
}RIS
TY - JOUR TI - Generative design and computational characterization of pyrazoline-based EGFR kinase inhibitor candidates. AU - Bhendarkar K AU - Khedekar P AU - Islam MA AU - Wanode D AU - Ambatkar M AU - Chikhale R PY - 2026 JO - Journal of molecular graphics & modelling DO - 10.1016/j.jmgm.2026.109631 UR - https://doi.org/10.1016/j.jmgm.2026.109631 ER -
APA
K, B., P, K., MA, I., D, W., M, A., & R, C. (2026). Generative design and computational characterization of pyrazoline-based EGFR kinase inhibitor candidates.. Journal of molecular graphics & modelling. https://doi.org/10.1016/j.jmgm.2026.109631
Source records
- pubmed · retrieved 2026-11-10T12:48:30.551Z
- europe-pmc · retrieved 2026-11-10T12:48:30.564Z