{"title":"Computational Pharmacogenetics of P-Glycoprotein Mediated Antiepileptic Drug Resistance","authors":"Sindhu Varghese, Ashok Palaniappan","doi":"10.2174/1875036201811010197","DOIUrl":null,"url":null,"abstract":"The treatment of epilepsy using antiepileptogenic drugs is complicated by drug resistance, resulting in treatment failure in more than one-third of cases. Human P-glycoprotein (hPGP;MDR1) is a known epileptogenic mediator.Given that experimental investigations have suggested a role for pharmacogenetics in this treatment failure, it would be of interest to study hPGP polymorphisms that might contribute to the emergence of drug resistance. Changes in protein functional activity could result from mutations as well as altered abundance. Bioinformatics approaches were used to assess and rank the functional impact of 20 missenseMDR1polymorphisms and the top five were selected. The structures of the wildtype and variant hPGP were modelled based on the mouse PGP structure. Docking studies of the wildtype and variant hPGP with four standard anti-epileptic drugs were carried out.Our results revealed that the drug binding site with respect to the wildtype protein was uniform. However, the variant hPGP proteins displayed a repertoire of binding sites with stronger binding affinities towards the drug.Our studies indicated that specific polymorphisms inMDR1could drive conformational changes of PGP structure, facilitating altered contacts with drug-substrates and thus modifying their bioavailability. This suggests thatMDR1polymorphisms could actively contribute to the emergence of pharmaco-resistance in antiepileptic therapy.","PeriodicalId":38956,"journal":{"name":"Open Bioinformatics Journal","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Open Bioinformatics Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2174/1875036201811010197","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"Computer Science","Score":null,"Total":0}
引用次数: 1
Abstract
The treatment of epilepsy using antiepileptogenic drugs is complicated by drug resistance, resulting in treatment failure in more than one-third of cases. Human P-glycoprotein (hPGP;MDR1) is a known epileptogenic mediator.Given that experimental investigations have suggested a role for pharmacogenetics in this treatment failure, it would be of interest to study hPGP polymorphisms that might contribute to the emergence of drug resistance. Changes in protein functional activity could result from mutations as well as altered abundance. Bioinformatics approaches were used to assess and rank the functional impact of 20 missenseMDR1polymorphisms and the top five were selected. The structures of the wildtype and variant hPGP were modelled based on the mouse PGP structure. Docking studies of the wildtype and variant hPGP with four standard anti-epileptic drugs were carried out.Our results revealed that the drug binding site with respect to the wildtype protein was uniform. However, the variant hPGP proteins displayed a repertoire of binding sites with stronger binding affinities towards the drug.Our studies indicated that specific polymorphisms inMDR1could drive conformational changes of PGP structure, facilitating altered contacts with drug-substrates and thus modifying their bioavailability. This suggests thatMDR1polymorphisms could actively contribute to the emergence of pharmaco-resistance in antiepileptic therapy.
期刊介绍:
The Open Bioinformatics Journal is an Open Access online journal, which publishes research articles, reviews/mini-reviews, letters, clinical trial studies and guest edited single topic issues in all areas of bioinformatics and computational biology. The coverage includes biomedicine, focusing on large data acquisition, analysis and curation, computational and statistical methods for the modeling and analysis of biological data, and descriptions of new algorithms and databases. The Open Bioinformatics Journal, a peer reviewed journal, is an important and reliable source of current information on the developments in the field. The emphasis will be on publishing quality articles rapidly and freely available worldwide.