title: QSAR analysis of cyclooxygenase inhibitor using particle swarm optimization and multiple linear regression.
abstract: Quantitative structure-activity relationship (QSAR) models of inhibiting action of some diarylimidazole derivatives on cylcooxygenase (COX) enzyme were constructed using modified particle swarm optimization (PSO) method. As a comparison to this method, the genetic algorithm (GA) was also tested. It has been demonstrated that the modified PSO is a useful tool for variable selection comparable to GA and even superior to GA. QSAR models are constructed separately for COX-2 inhibitory activity and selectivity of COX-2 inhibition over COX-1. The spatial descriptors play a key role in the compounds' activity and selectivity to COX-2, especially Jurs descriptors. Polar interactions are the principal binding strength between compounds and COX-2 enzyme. In addition, the aqueous desolvation free energy (FH2O) value of substituent will affect the COX-2 inhibitory activity, while the charge distribution can affect the selectivity to COX-2.
authors.affiliation: State Key Laboratory of Chemo/Biosensing and Chemometrics, College of Chemistry and Chemical Engineering, Hunan University, Changsha 410082, PR China.
authors.forename: Jian-Xia
authors.initials: JX
authors.lastname: Lü
authors.forename: Qi
authors.initials: Q
authors.lastname: Shen
authors.forename: Jian-Hui
authors.initials: JH
authors.lastname: Jiang
authors.forename: Guo-Li
authors.initials: GL
authors.lastname: Shen
authors.forename: Ru-Qin
authors.initials: RQ
authors.lastname: Yu
mesh_terms: D016861:Cyclooxygenase Inhibitors / Q000737:chemistry*; D016014:Linear Models; D021281:Quantitative Structure-Activity Relationship
chemical_list: D016861:Cyclooxygenase Inhibitors