Deng Fangfang, Ma Shuying, Xie Meihong, Zhang Xiaoyun, Li Peizhen, Zhai Honglin
College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 730000, Gansu, People's Republic of China.
Mol Biosyst. 2014 Aug;10(8):2202-14. doi: 10.1039/c4mb00183d.
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.
Toll样受体8激动剂有望成为疫苗佐剂的候选物，尤其是用于新生儿疫苗。在本研究中，我们建立了可靠的模型并探索了有价值的信息，这些信息可以在分子水平上解释已知的实验事实。首先，我们将整个数据集分为四个子集，并基于简化分子线性输入规范（SMILES）获得了许多可靠的模型。其次，将整个数据集分为三个子集，并建立了其他可靠的比较分子场分析（CoMFA）和比较分子相似性指数分析（CoMSIA）模型。第三，我们使用各种验证方法对测试集验证了这些模型的预测能力。最后，为了更好地理解激动剂与Toll样受体8之间的结合模式，应用分子对接来揭示影响激动剂对Toll样受体8活性的结构因素。此外，采用分子动力学模拟进一步验证对接结果。分子建模获得的结果相互支持，这不仅提供了预测激动剂活性的模型，还有助于更好地理解在设计具有所需活性的新型激动剂时应考虑的基本特征。
