Innovative Drug Research and Bioinformatics Group, School of Pharmaceutical Sciences and Collaborative Innovation Center for Brain Science, Chongqing University, Chongqing, China.
Innovative Drug Research and Bioinformatics Group, College of Pharmaceutical Sciences, Zhejiang University, Hangzhou, China.
CNS Neurosci Ther. 2018 Dec;24(12):1253-1263. doi: 10.1111/cns.13051. Epub 2018 Aug 14.
Alzheimer's disease (AD) is one of the leading causes of death in elderly people. Its pathogenesis is greatly associated with the abnormality of immune system. However, only a few immune-relevant AD drug target genes have been discovered up to now, and it is speculated that there are still many potential drug target genes of AD (at least immune-relevant genes) to be discovered. Thus, this study was designed to identify novel AD drug target genes and explore their biological properties.
A combinatorial approach was adopted for the first time to discover AD drug targets by collectively considering ontology inference and network analysis. Moreover, a novel strategy limiting the distance of reasoning and in turn reducing noise interference was further proposed to improve inference performance. Potential AD drug target genes were discovered by integrating information of multiple popular databases (TTD, DrugBank, PharmGKB, AlzGene, and BioGRID). Then, the enrichment analyses of the identified drug targets genes based on nine well-known pathway-related databases were conducted to explore the function of the identified potential drug target genes.
Eighteen potential drug target genes were finally identified, and 13 of them had been reported to be closely associated with AD. Enrichment analyses of these identified drug target genes, based on nine pathway-related databases, revealed that the enriched terms were primarily focus on immune-relevant biological processes. Four of those identified drug target genes are involved in the classical complement pathway and process of antigen presenting.
The well-reproducible results showed the good performance of the combinatorial approach, and the remaining five new targets could be a good starting point for our understanding of the pathogenesis and drug discovery of AD. Moreover, this study supported validity of the combinatorial approach integrating ontology inference with network analysis in the discovery of novel drug target for neurological diseases.
阿尔茨海默病（AD）是老年人死亡的主要原因之一。其发病机制与免疫系统异常密切相关。然而，迄今为止仅发现了少数与免疫相关的 AD 药物靶标基因，据推测，仍有许多潜在的 AD 药物靶标基因（至少与免疫相关基因）有待发现。因此，本研究旨在鉴定新的 AD 药物靶标并探索其生物学特性。
本研究首次采用组合方法，通过综合考虑本体推理和网络分析，发现 AD 药物靶标。此外，还提出了一种新的策略，通过限制推理的距离，从而减少噪声干扰，提高推理性能。通过整合多个流行的数据库（TTD、DrugBank、PharmGKB、AlzGene 和 BioGRID）的信息，发现潜在的 AD 药物靶标基因。然后，基于九个著名的通路相关数据库，对鉴定的药物靶标基因进行富集分析，以探讨鉴定的潜在药物靶标基因的功能。
最终鉴定出 18 个潜在的药物靶标基因，其中 13 个已被报道与 AD 密切相关。基于九个通路相关数据库对这些鉴定的药物靶标基因进行富集分析，结果表明，富集的术语主要集中在免疫相关的生物学过程上。其中 4 个鉴定的药物靶标基因参与经典补体途径和抗原呈递过程。
可重复的结果表明组合方法的性能良好，其余 5 个新靶点可能为我们理解 AD 的发病机制和药物发现提供一个良好的起点。此外，该研究支持了整合本体推理和网络分析的组合方法在发现神经疾病新药物靶标的有效性。
