Literature DB >> 19425139

Network analysis of adverse drug interactions.

Masataka Takarabe1, Shujiro Okuda, Masumi Itoh, Tosihaki Tokimatsu, Susumu Goto, Minoru Kanehisa.   

Abstract

Harmful effects associated with use of drugs are caused as a result of their side effects and combined use of different drugs. These drug interactions result in increased or decreased drug effects, or produce other new unwanted effects and are serious problems for medical institutions and pharmaceutical companies. In this study, we created a drug-drug interaction network from drug package inserts and characterized drug interactions. The known information about the potential risk of drug interactions is described in drug package inserts. Japanese drug package inserts are stored in the JAPIC (Japan Pharmaceutical Information Center) database and GenomeNet provides the GenomeNet pharmaceutical products database, which integrate the JAPIC and KEGG databases. We extracted drug interaction data from GenomeNet, where interactions are classified according to risks, contraindications or cautions for coadministration, and some entries include information about enzymes metabolizing the drugs. We defined drug target and drug-metabolizing enzymes as interaction factors using information on them in KEGG DRUG, and classified drugs into pharmacological/chemical subgroups. In the resulting drug-drug interaction network, the drugs that are associated with the same interaction factors are closely interconnected. Mechanisms of these interactions were then identified by each interaction factor. To characterize other interactions without interaction factors, we used the ATC classification system and found an association between interaction mechanisms and pharmacological/chemical subgroups.

Mesh:

Substances:

Year:  2008        PMID: 19425139

Source DB:  PubMed          Journal:  Genome Inform        ISSN: 0919-9454


  6 in total

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Authors:  Peter Csermely; Tamás Korcsmáros; Huba J M Kiss; Gábor London; Ruth Nussinov
Journal:  Pharmacol Ther       Date:  2013-02-04       Impact factor: 12.310

2.  Discovering drug-drug interactions: a text-mining and reasoning approach based on properties of drug metabolism.

Authors:  Luis Tari; Saadat Anwar; Shanshan Liang; James Cai; Chitta Baral
Journal:  Bioinformatics       Date:  2010-09-15       Impact factor: 6.937

3.  Pharmacointeraction network models predict unknown drug-drug interactions.

Authors:  Aurel Cami; Shannon Manzi; Alana Arnold; Ben Y Reis
Journal:  PLoS One       Date:  2013-04-19       Impact factor: 3.240

4.  Targets of drugs are generally, and targets of drugs having side effects are specifically good spreaders of human interactome perturbations.

Authors:  Áron R Perez-Lopez; Kristóf Z Szalay; Dénes Türei; Dezső Módos; Katalin Lenti; Tamás Korcsmáros; Peter Csermely
Journal:  Sci Rep       Date:  2015-05-11       Impact factor: 4.379

5.  Potential Drug-drug Interactions in Post-CCU of a Teaching Hospital.

Authors:  Mohammad Haji Aghajani; Mohammad Sistanizad; Mohammad Abbasinazari; Mahdieh Abiar Ghamsari; Ladan Ayazkhoo; Olia Safi; Katayoon Kazemi; Mehran Kouchek
Journal:  Iran J Pharm Res       Date:  2013       Impact factor: 1.696

6.  Characterizing the network of drugs and their affected metabolic subpathways.

Authors:  Chunquan Li; Desi Shang; Yan Wang; Jing Li; Junwei Han; Shuyuan Wang; Qianlan Yao; Yingying Wang; Yunpeng Zhang; Chunlong Zhang; Yanjun Xu; Wei Jiang; Xia Li
Journal:  PLoS One       Date:  2012-10-24       Impact factor: 3.240

  6 in total

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