Xiaojun Yao

CoMFA/CoMSIA/HQSAR and Docking Study of the Binding Mode of Selective Cyclooxygenase (COX‐2) Inhibitors

Abstract The intermolecular interaction between four types of anti‐inflammatory inhibitors (oxazoles, pyrazoles, pyrroles and imidazoles) and COX‐2 receptor was studied. The results of docking suggest that they have similar interaction mechanism. The most active compounds of these four types of inhibitors could both form several hydrogen bonds with residues His90, Arg513, Leu352 and Arg120, and develop hydrophobic interaction with residues Phe518, Leu352 and Leu359. This is consistent with the investigation reported by R. G. Kurumbail et al. (Nature. 1996, 384, 644‐648). A common 3D‐QSAR model could be constructed with these four categories of COX‐2 inhibitors using the method of docking‐ guided conformer selection. The cross‐validated q2 values are found as 0.741 and 0.632 for CoMFA and CoMSIA respectively. And the non‐cross‐validated r2 values are 0.887 and 0.885. 54 inhibitors constitute the test set used to validate the model. The results show that this model possesses good predictive ability for diverse COX‐2 inhibitors. Furthermore, a HQSAR model was used to evaluate the influence of substituents on anti‐inflammatory activity. Compared with the results of previous works, our model possesses significantly better prediction ability. It could help us to well understand the interaction mechanism between inhibitors and COX‐2 receptor, and to make quantitative prediction of their inhibitory activities.

Comparative study of non nucleoside inhibitors with hiv-1 reverse transcriptase based on 3D-QSAR and docking

The intermolecular interaction between two types of non nucleoside reverse transcriptase inhibitors (NNRTIs), HEPT and TIBO, and HIV reverse transcriptase receptor (HIVRT) was investigated. The result of docking study showed that two types of NNRTIs presented similar interaction mechanism with HIVRT. The most active compound of every type of inhibitors could form one hydrogen bond with the residue Lys101 and has hydrophobic interaction with residues Tyr181, Tyr188 and Tyr318, etc. Three 3D-QSAR models including two partial correlation models (one for each family of HEPT and TIBO) and a mixed model gathering two families were constructed. Comparative study of these models indicated that the mixed model offered the strongest prediction ability. For this model, the cross-validated q 2 values were 0.720 and 0.675, non-cross-validated r 2 values were 0.940 and 0.920 for CoMFA and CoMSIA, respectively. It has been validated by using a test set of 27 inhibitors. Compared with previously reported works, our model showed better prediction ability. It could help us to insight the interaction between NNRTIs and HIVRT, and to design new anti-HIV NNRTIs inhibitors.