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利用基于文献的发现来识别新的治疗方法。

Using literature-based discovery to identify novel therapeutic approaches.

作者信息

Hristovski Dimitar, Rindflesch Thomas, Peterlin Borut

机构信息

University of Ljubljana, Medical faculty, Institute for Biostatistics and Medical Informatics, Ljubljana, Slovenia.

出版信息

Cardiovasc Hematol Agents Med Chem. 2013 Mar;11(1):14-24. doi: 10.2174/1871525711311010005.

Abstract

We present a promising in silico paradigm called literature-based discovery (LBD) and describe its potential to identify novel pharmacologic approaches to treating diseases. The goal of LBD is to generate novel hypotheses by analyzing the vast biomedical literature. Additional knowledge resources, such as ontologies and specialized databases, are often used to supplement the published literature. MEDLINE, the largest and most important biomedical bibliographic database, is the most common source for exploiting LBD. There are two variants of LBD, open discovery and closed discovery. With open discovery we can, for example, try to find a novel therapeutic approach for a given disease, or find new therapeutic applications for an existing drug. With closed discovery we can find an explanation for a relationship between two concepts. For example, if we already have a hypothesis that a particular drug is useful for a particular disease, with closed discovery we can identify the mechanisms through which the drug could have a therapeutic effect on the disease. We briefly describe the methodology behind LBD and then discuss in more detail currently available LBD tools; we also mention in passing some of those no longer available. Next we present several examples in which LBD has been exploited for identifying novel therapeutic approaches. In conclusion, LBD is a powerful paradigm with considerable potential to complement more traditional drug discovery methods, especially for drug target discovery and for existing drug relabeling.

摘要

我们提出了一种名为基于文献的发现(LBD)的有前景的计算机模拟范式,并描述了其识别治疗疾病新药理学方法的潜力。LBD的目标是通过分析大量生物医学文献来生成新的假设。其他知识资源,如实证本体和专业数据库,常被用于补充已发表的文献。MEDLINE是最大且最重要的生物医学文献数据库,是利用LBD最常用的来源。LBD有两种变体,即开放式发现和封闭式发现。通过开放式发现,例如,我们可以尝试为给定疾病找到一种新的治疗方法,或者为现有药物找到新的治疗应用。通过封闭式发现,我们可以找到两个概念之间关系的解释。例如,如果我们已经有一个假设,即某种特定药物对某种特定疾病有用,通过封闭式发现我们可以确定该药物对该疾病产生治疗效果的机制。我们简要描述LBD背后的方法,然后更详细地讨论当前可用的LBD工具;我们还顺便提及一些已不再可用的工具。接下来,我们展示几个利用LBD识别新治疗方法的例子。总之,LBD是一种强大的范式,有很大潜力补充更传统的药物发现方法,特别是在药物靶点发现和现有药物重新标记方面。

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