2D-QSAR Study of Thiazole derivatives as 5-Lipoxygenase inhibitors

Abstract

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.