Toll-like receptor 7 （TLR7）, the best known TLRs, has been demonstrated to be useful in fighting against infectious disease. In our study, three-dimensional （3D） pharmacophore models were constructed from a set of...Toll-like receptor 7 （TLR7）, the best known TLRs, has been demonstrated to be useful in fighting against infectious disease. In our study, three-dimensional （3D） pharmacophore models were constructed from a set of 5 TLR7 agonists. Among the 10 common-featured models generated by program Discovery Studio/HipHop, a hypothesis （Hypo2） including one hydrogen-bond donor （D）, one hydrogen-bond acceptor （A）, and two hydrophobic （H） features was considered to be important in evaluating the ligands with TLR7 agonistic activity. The obtained pharmacophore model was further validated using a set of test molecules and the Catalyst TLR7-agonist-subset database. Hypo2 has been shown to identify a range of highly potent TLR7 agonists. Finally, the obtained pharmacophore was further validated using docking studies. Taken together, this model can be utilized as a guide for future studies to design the structurally novel TLR7 agonists.展开更多
基金supported by the National Natural Science Foundation of China(Grant No.20902068)Natural Science Foundation of Inner Mongolia Autonomous Region,China(Grant No.2011BS1201)+1 种基金Program for Young Talents of ScienceTechnology in Universities of Inner Mongolia Autonomous Region,China
文摘Toll-like receptor 7 （TLR7）, the best known TLRs, has been demonstrated to be useful in fighting against infectious disease. In our study, three-dimensional （3D） pharmacophore models were constructed from a set of 5 TLR7 agonists. Among the 10 common-featured models generated by program Discovery Studio/HipHop, a hypothesis （Hypo2） including one hydrogen-bond donor （D）, one hydrogen-bond acceptor （A）, and two hydrophobic （H） features was considered to be important in evaluating the ligands with TLR7 agonistic activity. The obtained pharmacophore model was further validated using a set of test molecules and the Catalyst TLR7-agonist-subset database. Hypo2 has been shown to identify a range of highly potent TLR7 agonists. Finally, the obtained pharmacophore was further validated using docking studies. Taken together, this model can be utilized as a guide for future studies to design the structurally novel TLR7 agonists.
