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EK-DRD:基于实验知识启发的药物重定位综合数据库。

EK-DRD: A Comprehensive Database for Drug Repositioning Inspired by Experimental Knowledge.

机构信息

Joint International Research Laboratory of Synthetic Biology and Medicine, Guangdong Provincial Engineering and Technology Research Center of Biopharmaceuticals, School of Biology and Biological Engineering , South China University of Technology , Guangzhou 510006 , China.

出版信息

J Chem Inf Model. 2019 Sep 23;59(9):3619-3624. doi: 10.1021/acs.jcim.9b00365. Epub 2019 Sep 3.

Abstract

Drug repositioning, or the identification of new indications for approved therapeutic drugs, has gained substantial traction with both academics and pharmaceutical companies because it reduces the cost and duration of the drug development pipeline and the likelihood of unforeseen adverse events. To date there has not been a systematic effort to identify such opportunities, in part because of the lack of a comprehensive resource for an enormous amount of unsystematic drug repositioning information to support scientists who could benefit from this endeavor. To address this challenge, we developed a new database, the Experimental Knowledge-Based Drug Repositioning Database (EK-DRD), by using text and data mining as well as manual curation. EK-DRD contains experimentally validated drug repositioning annotation for 1861 FDA-approved and 102 withdrawn small-molecule drugs. Annotation was done at four levels using 30 944 target assay records, 3999 cell assay records, 585 organism assay records, and 8889 clinical trial records. Additionally, approximately 1799 repositioning protein or target sequences coupled with 856 related diseases and 1332 pathways are linked to the drug entries. Our web-based software displays a network of integrative relationships between drugs, their repositioning targets, and related diseases. The database is fully searchable and supports extensive text, sequence, chemical structure, and relational query searches. EK-DRD is freely accessible at http://www.idruglab.com/drd/index.php .

摘要

药物重定位,或鉴定已批准治疗药物的新适应症,已引起学术界和制药公司的广泛关注,因为它降低了药物开发管道的成本和时间,并且降低了不可预见的不良事件的可能性。迄今为止,尚未进行系统的努力来识别这种机会,部分原因是缺乏全面的资源来支持可能从这项工作中受益的科学家,以获取大量非系统性药物重定位信息。为了解决这一挑战,我们使用文本和数据挖掘以及手动策展,开发了一个新的数据库,即实验知识驱动的药物重定位数据库(EK-DRD)。EK-DRD 包含 1861 种 FDA 批准和 102 种已撤回的小分子药物的经过实验验证的药物重定位注释。注释使用 30944 个目标测定记录、3999 个细胞测定记录、585 个生物体测定记录和 8889 个临床试验记录,在四个级别上进行。此外,大约 1799 种重定位蛋白或目标序列与 856 种相关疾病和 1332 种途径相关联,与药物条目相关联。我们的基于网络的软件显示了药物、其重定位目标和相关疾病之间的综合关系网络。该数据库完全可搜索,并支持广泛的文本、序列、化学结构和关系查询搜索。EK-DRD 可在 http://www.idruglab.com/drd/index.php 免费获得。

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