2D-QSAR Study of Thiazole derivatives as 5-Lipoxygenase inhibitors
DOI:
https://doi.org/10.18687/LACCEI2024.1.1.1785Palabras clave:
2D-QSAR models, Thiazole derivatives, 5-Lipoxygenase, anti-inflammatory drugsResumen
Abstract - The inhibition of 5-Lipoxygenase (5-LO) has become a rational approach for the development of anti-inflammatory drugs. This study aimed to work on a trending machine learning approach with an open-source data analysis Python script for the discovery of 5-lipoxygenase inhibitors (5-LOX) by building two-dimensional-quantitative structure–activity relationships (2D-QSAR) of a series of 59 Thiazole derivatives acting as inhibitors of 5-LOX. The generated 2D-QSAR model showed a good correlation coefficient of 0.626 and a good prediction coefficient of the test set of 0.621. The predictive ability of the 2D-QSAR models was assessed via external (test set with 12 compounds). The proposed model gave significant statistical quality.
Descargas
Publicado
2024-07-27
Número
Sección
Articles
Derechos de autor
Derechos de autor 2024 LACCEI
Licencia
Esta obra está bajo una Licencia Creative Commons Atribución-NoComercial-CompartirIgual 4.0 Internacional.
LACCEI conserva el copyright de todos los artículos publicados bajo los términos de su acuerdo de transferencia de copyright. Como titular del copyright, LACCEI distribuye los artículos al público bajo la Licencia Internacional Creative Commons Atribución-NoComercial-CompartirIgual 4.0 (CC BY-NC-SA 4.0).
Cómo citar
Ariza-Rúa, D., Hurtado Márquez, J., Marbello-Peña, H., Chavarro-Mesa, E., & Carranza-López, L. (2024). 2D-QSAR Study of Thiazole derivatives as 5-Lipoxygenase inhibitors. LACCEI, 1(10). https://doi.org/10.18687/LACCEI2024.1.1.1785