title: Toll-like receptor 7 agonists: chemical feature based pharmacophore identification and molecular docking studies.
abstract: Chemical feature based pharmacophore models were generated for Toll-like receptors 7 (TLR7) agonists using HypoGen algorithm, which is implemented in the Discovery Studio software. Several methods tools used in validation of pharmacophore model were presented. The first hypothesis Hypo1 was considered to be the best pharmacophore model, which consists of four features: one hydrogen bond acceptor, one hydrogen bond donor, and two hydrophobic features. In addition, homology modeling and molecular docking studies were employed to probe the intermolecular interactions between TLR7 and its agonists. The results further confirmed the reliability of the pharmacophore model. The obtained pharmacophore model (Hypo1) was then employed as a query to screen the Traditional Chinese Medicine Database (TCMD) for other potential lead compounds. One hit was identified as a potent TLR7 agonist, which has antiviral activity against hepatitis virus in vitro. Therefore, our current work provides confidence for the utility of the selected chemical feature based pharmacophore model to design novel TLR7 agonists with desired biological activity.
authors.affiliation: Department of Laboratory Centre, the Affiliated Tenth People's Hospital, Tongji University, Shanghai, China.
authors.forename: Hui
authors.initials: H
authors.lastname: Yu
authors.forename: Hongwei
authors.initials: H
authors.lastname: Jin
authors.forename: Lidan
authors.initials: L
authors.lastname: Sun
authors.forename: Liangren
authors.initials: L
authors.lastname: Zhang
authors.forename: Gang
authors.initials: G
authors.lastname: Sun
authors.forename: Zhanli
authors.initials: Z
authors.lastname: Wang
authors.forename: Yongchun
authors.initials: Y
authors.lastname: Yu
mesh_terms: D000465:Algorithms; D000595:Amino Acid Sequence; D003198:Computer Simulation; D062126:Databases, Chemical; D015195:Drug Design; D004365:Drugs, Chinese Herbal / Q000737:chemistry / Q000494:pharmacology; D006801:Humans; D006860:Hydrogen Bonding; D057927:Hydrophobic and Hydrophilic Interactions; D008958:Models, Molecular; D062105:Molecular Docking Simulation; D008969:Molecular Sequence Data; D040681:Structural Homology, Protein; D013329:Structure-Activity Relationship; D051199:Toll-Like Receptor 7 / Q000819:agonists* / Q000737:chemistry* / Q000235:genetics
chemical_list: D004365:Drugs, Chinese Herbal; C495348:TLR7 protein, human; D051199:Toll-Like Receptor 7