Department of Biomedical Informatics, Vanderbilt University School of Medicine, Nashville, TN 37232, USA.
BMC Bioinformatics. 2012 Jun 11;13 Suppl 9(Suppl 9):S7. doi: 10.1186/1471-2105-13-S9-S7.
Understanding drug bioactivities is crucial for early-stage drug discovery, toxicology studies and clinical trials. Network pharmacology is a promising approach to better understand the molecular mechanisms of drug bioactivities. With a dramatic increase of rich data sources that document drugs' structural, chemical, and biological activities, it is necessary to develop an automated tool to construct a drug-target network for candidate drugs, thus facilitating the drug discovery process.
We designed a computational workflow to construct drug-target networks from different knowledge bases including DrugBank, PharmGKB, and the PINA database. To automatically implement the workflow, we created a web-based tool called DTome (Drug-Target interactome tool), which is comprised of a database schema and a user-friendly web interface. The DTome tool utilizes web-based queries to search candidate drugs and then construct a DTome network by extracting and integrating four types of interactions. The four types are adverse drug interactions, drug-target interactions, drug-gene associations, and target-/gene-protein interactions. Additionally, we provided a detailed network analysis and visualization process to illustrate how to analyze and interpret the DTome network. The DTome tool is publicly available at http://bioinfo.mc.vanderbilt.edu/DTome.
As demonstrated with the antipsychotic drug clozapine, the DTome tool was effective and promising for the investigation of relationships among drugs, adverse interaction drugs, drug primary targets, drug-associated genes, and proteins directly interacting with targets or genes. The resultant DTome network provides researchers with direct insights into their interest drug(s), such as the molecular mechanisms of drug actions. We believe such a tool can facilitate identification of drug targets and drug adverse interactions.
理解药物的生物活性对于药物发现的早期阶段、毒理学研究和临床试验至关重要。网络药理学是一种更好地理解药物生物活性分子机制的有前途的方法。随着丰富的数据源的急剧增加，这些数据记录了药物的结构、化学和生物活性，因此有必要开发一种自动化工具来构建候选药物的药物-靶点网络，从而促进药物发现过程。
我们设计了一个计算工作流程，从包括 DrugBank、PharmGKB 和 PINA 数据库在内的不同知识库中构建药物-靶点网络。为了自动实现工作流程，我们创建了一个名为 DTome（药物-靶点相互作用工具）的基于网络的工具，它由一个数据库模式和一个用户友好的网络界面组成。DTome 工具利用基于网络的查询来搜索候选药物，然后通过提取和整合四种类型的相互作用来构建 DTome 网络。这四种相互作用是不良药物相互作用、药物-靶点相互作用、药物-基因关联和靶点/基因-蛋白相互作用。此外，我们提供了详细的网络分析和可视化过程，以说明如何分析和解释 DTome 网络。DTome 工具可在 http://bioinfo.mc.vanderbilt.edu/DTome 上公开获取。
正如抗精神病药物氯氮平的结果所示，DTome 工具对于研究药物、不良相互作用药物、药物主要靶点、药物相关基因以及直接与靶点或基因相互作用的蛋白之间的关系是有效且有前途的。所得的 DTome 网络为研究人员提供了对其感兴趣的药物的直接了解，例如药物作用的分子机制。我们相信这样的工具可以促进药物靶点和药物不良相互作用的识别。
