Toll-Like Receptor 7 Agonists: Chemical Feature Based Pharmacophore Identification and Molecular Docking Studies

Hongwei Jin,Yongchun Yu,Hui Yu,Zhanli Wang,Lidan Sun,Gang Sun,Liangren Zhang

doi:10.1371/journal.pone.0056514

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.

Highlights

Toll-like receptors (TLRs) are a family of highly conserved pattern recognition receptors (PRR) that can recognize pathogenassociated molecular patterns (PAMPs) present on or in bacteria, viruses, fungi and parasites [1]
This study represents the first successful attempt to obtain a pharmacophore model Hypo1 that defines the pharmacophoric requirements for Toll-like receptors 7 (TLR7) agonistic activity
Our current model can be utilized as a guide for future studies to design the structurally novel TLR7 agonists

Summary

Introduction

Toll-like receptors (TLRs) are a family of highly conserved pattern recognition receptors (PRR) that can recognize pathogenassociated molecular patterns (PAMPs) present on or in bacteria, viruses, fungi and parasites [1]. Sensing these patterns by the TLRs initiates innate and adaptive immune responses against pathogens [2]. Thirteen TLRs have been reported [3]. Agonists of the TLRs could enhance a specific immune response and have been proposed to be useful in battling cancer or infectious disease [4]. Several TLR agonists are in clinical development [5]

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