Identification of Novel 5-Lipoxygenase-Activating Protein (FLAP) Inhibitors by an Integrated Method of Pharmacophore Virtual Screening, Docking, QSAR and ADMET Analyses

This study explored a series of reported 5-lipoxygenase-activating protein (FLAP) inhibitors to understand their structural requirements and identify potential new inhibitor scaffolds through automated unbiased procedures. Docking studies have revealed that binding affinity can be influenced by several key interactions with Phe114 Lys116 from chain B Val21, Phe25, His28 Lys29 C in the FLAP-binding site. A ligand-based alignment three-dimensional (3D)-quantitative structure–activity relationship (QSAR) was adopted, resulting robust model statistically significant noncross-validated coefficient ([Formula: see text]), cross-validated correlation text]) predictive squared text]). Overall, analysis important electrostatic steric attributes responsible for FLAP inhibitory activity, which appeared correlate well docking results. In addition, two two-dimensional (2D)-QSAR models text], [Formula: text] were developed genetic function approximation (GFA). HypoGen 1, proposed pharmacophore model, used database mining inhibitors. The bioactivity retrieved hits then evaluated silico based on validated QSAR models, followed pharmacokinetics toxicity predictions.