DrugBank 3.0: a comprehensive resource for 'Omics' research on drugs

药物数据库 药物作用 药物基因组学 药物发现 药品 数据科学 药理学 计算机科学 生物信息学 计算生物学 生物
作者
Craig Knox,Vivian Law,Timothy Jewison,Philip L.‐F. Liu,Son Ly,Alex Frolkis,Allison Pon,Kelly Banco,Christine Suet Yee Mak,Vanessa Neveu,Yannick Djoumbou,Roman Eisner,An Chi Guo,David S. Wishart
出处
期刊:Nucleic Acids Research [Oxford University Press]
卷期号:39 (Database): D1035-D1041 被引量:1565
标识
DOI:10.1093/nar/gkq1126
摘要

DrugBank (http://www.drugbank.ca) is a richly annotated database of drug and drug target information. It contains extensive data on the nomenclature, ontology, chemistry, structure, function, action, pharmacology, pharmacokinetics, metabolism and pharmaceutical properties of both small molecule and large molecule (biotech) drugs. It also contains comprehensive information on the target diseases, proteins, genes and organisms on which these drugs act. First released in 2006, DrugBank has become widely used by pharmacists, medicinal chemists, pharmaceutical researchers, clinicians, educators and the general public. Since its last update in 2008, DrugBank has been greatly expanded through the addition of new drugs, new targets and the inclusion of more than 40 new data fields per drug entry (a 40% increase in data 'depth'). These data field additions include illustrated drug-action pathways, drug transporter data, drug metabolite data, pharmacogenomic data, adverse drug response data, ADMET data, pharmacokinetic data, computed property data and chemical classification data. DrugBank 3.0 also offers expanded database links, improved search tools for drug-drug and food-drug interaction, new resources for querying and viewing drug pathways and hundreds of new drug entries with detailed patent, pricing and manufacturer data. These additions have been complemented by enhancements to the quality and quantity of existing data, particularly with regard to drug target, drug description and drug action data. DrugBank 3.0 represents the result of 2 years of manual annotation work aimed at making the database much more useful for a wide range of 'omics' (i.e. pharmacogenomic, pharmacoproteomic, pharmacometabolomic and even pharmacoeconomic) applications.
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