Jump to main content
Jump to site search
Access to RSC content Close the message box

Continue to access RSC content when you are not at your institution. Follow our step-by-step guide.


Issue 8, 2014
Previous Article Next Article

Study on the agonists for the human Toll-like receptor-8 by molecular modeling

Author affiliations

Abstract

Toll-like receptor-8 agonists could be promising candidates for vaccine adjuvants, especially for neonatal vaccines. In this study, we established reliable models and explored valuable information which could explain the known experimental facts at the molecular level. Firstly, we divided the whole dataset into four splits and obtained many dependable models based on the simplified molecular input line entry system (SMILES). Secondly, the whole dataset was divided into three splits and other reliable comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were established. Thirdly, we validated the prediction ability of these models using various validation methods for the test set. Lastly, for a better understanding of the binding modes between agonists and Toll-like receptor-8, molecular docking was applied to reveal the structural factors that impact the activity of agonists towards Toll-like receptor-8. Furthermore, molecular dynamics simulation was employed to further validate the docking results. The results obtained from molecular modeling support each other, which not only provides models to predict the activities of agonists but also leads to a better understanding of the essential features that should be considered when designing novel agonists with desired activities.

Graphical abstract: Study on the agonists for the human Toll-like receptor-8 by molecular modeling

Back to tab navigation

Supplementary files

Article information


Submitted
25 Mar 2014
Accepted
28 Apr 2014
First published
28 Apr 2014

Mol. BioSyst., 2014,10, 2202-2214
Article type
Paper

Study on the agonists for the human Toll-like receptor-8 by molecular modeling

F. Deng, S. Ma, M. Xie, X. Zhang, P. Li and H. Zhai, Mol. BioSyst., 2014, 10, 2202
DOI: 10.1039/C4MB00183D

Search articles by author

Spotlight

Advertisements