000207010 001__ 207010
000207010 005__ 20181203023821.0
000207010 022__ $$a1381-6128
000207010 02470 $$2ISI$$a000349459600012
000207010 037__ $$aARTICLE
000207010 245__ $$aAntihypertensive drugs metabolism: an update to pharmacokinetic profiles and computational approaches
000207010 269__ $$a2015
000207010 260__ $$bBentham Science Publishers$$c2015$$aSharjah
000207010 300__ $$a17
000207010 336__ $$aJournal Articles
000207010 520__ $$aDrug discovery and development is a high-risk enterprise that requires significant investments in capital, time and scientific expertise. The studies of xenobiotic metabolism remain as one of the main topics in the research and development of drugs, cosmetics and nutritional supplements. Antihypertensive drugs are used for the treatment of high blood pressure, which is one the most frequent symptoms of the patients that undergo cardiovascular diseases such as myocardial infraction and strokes. In current cardiovascular disease pharmacology, four drug clusters - Angiotensin Converting Enzyme Inhibitors, Beta-Blockers, Calcium Channel Blockers and Diuretics - cover the major therapeutic characteristics of the most antihypertensive drugs. The pharmacokinetic and specifically the metabolic profile of the antihypertensive agents are intensively studied because of the broad inter-individual variability on plasma concentrations and the diversity on the efficacy response especially due to the P450 dependent metabolic status they present. Several computational methods have been developed with the aim to: (i) model and better understand the human drug metabolism; and (ii) enhance the experimental investigation of the metabolism of small xenobiotic molecules. The main predictive tools these methods employ are rule-based approaches, quantitative structure metabolism/activity relationships and docking approaches. This review paper provides detailed metabolic profiles of the major clusters of antihypertensive agents, including their metabolites and their metabolizing enzymes, and it also provides specific information concerning the computational approaches that have been used to predict the metabolic profile of several antihypertensive drugs.
000207010 6531_ $$ametabolism
000207010 6531_ $$aantihypertensive drugs
000207010 6531_ $$acomputational approaches
000207010 700__ $$0244259$$g206342$$aZisaki, Aikaterini
000207010 700__ $$0240448$$g133818$$aMiskovic, Ljubisa
000207010 700__ $$aHatzimanikatis, Vassily$$g174688$$0240657
000207010 773__ $$j21$$tCurrent Pharmaceutical Design$$k6$$q806-822
000207010 909C0 $$xU11422$$0252131$$pLCSB
000207010 909CO $$pSB$$particle$$ooai:infoscience.tind.io:207010
000207010 917Z8 $$x133818
000207010 937__ $$aEPFL-ARTICLE-207010
000207010 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000207010 980__ $$aARTICLE