Document Detail


Defining candidate drug characteristics for Long-QT (LQT3) syndrome.
MedLine Citation:
PMID:  21675815     Owner:  NLM     Status:  In-Data-Review    
Abstract/OtherAbstract:
Mutations of the SCN5A gene can significantly alter the function of cardiac myocyte sodium channels leading to increased risk of ventricular arrhythmia. Over the past decade, detailed Markov models of the action potential of cardiac cells have been developed. In such models, the effects of a drug can be treated as alterations in on- and off rates between open and inactivated states on one hand, and blocked states on the other hand. Our aim is to compute the rates specifying a drug in order to: (a) restore the steady-state open probability of the mutant channel to that of normal wild type channels; and (b) minimize the difference between whole cell currents in drugged mutant and wild type cells. The difference in the electrochemical state vector of the cell can be measured in a norm taking all components and their dynamical properties into account. Measured with this norm, the difference between the state of the mutant and wild-type cell was reduced by a factor of 36 after the drug was introduced and by factors of 4 over mexitiline and 25 over lidocaine. The results suggest the potential to synthesize more effective drugs based on mechanisms of action of existing compounds.
Authors:
Aslak Tveito Tveito; Glenn T Lines; Pan Li; Andrew McCulloch
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Publication Detail:
Type:  Journal Article    
Journal Detail:
Title:  Mathematical biosciences and engineering : MBE     Volume:  8     ISSN:  1551-0018     ISO Abbreviation:  Math Biosci Eng     Publication Date:  2011 Jul 
Date Detail:
Created Date:  2011-06-16     Completed Date:  -     Revised Date:  -    
Medline Journal Info:
Nlm Unique ID:  101197794     Medline TA:  Math Biosci Eng     Country:  United States    
Other Details:
Languages:  eng     Pagination:  861-73     Citation Subset:  IM    
Affiliation:
Center for Biomedical Computing, Simula Research Laboratory, P.O. Box 134, Lysaker 1325, Norway. aslak@simula.no.
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