Pharmacophore Modeling and Docking Based QSAR Studies of Aryl Amidino Isoxazoline Derivatives to Design Potential FXa Inhibitors

Abstract

In order to elucidate the structural requirements for human factor Xa receptor antagonism, 72 antagonists belonging to isoxazolidine chemical class were selected from the literature and conducted molecular modeling studies. Best binding conformations were isolated by docking selected molecules into the receptor binding site. To further explore the structure-activity relationships within the considered chemical class, a pharmacophore model and QSAR analyses were developed. Pharmacophore models of these inhibitors were established by using the HipHop and HypoGen algorithms implemented in the Catalyst software package. The best quantitative pharmacophore model, which has the highest correlation coefficient (0.92), consisted of two hydrogen bond donor, a hydrophobic aromatic, and a ring aromatic feature. The model was further validated by test set and cross validation method. Molecular shape analysis (MSA) and Molecular field analysis (MFA) were used as the QSAR techniques. Two conformer-based alignment strategies were employed to construct reliable 3D-QSAR models. The docked conformer-based alignment strategy gave the best 3D-QSAR models. The best MFA and MSA models gave a cross-validated coefficient q(2) of 0.641 and 0.816, non-cross-validated r(2) values of 0.736 and 0.902, 20% out r(2) values of 0.743 and 0.871, respectively. The information obtained from molecular modelling studies was very helpful to design some novel selective inhibitors of factor Xa with desired activity.