Title
Probabilistic model checking analysis of palytoxin effects on cell energy reactions of the Na+/K+-ATPase.
Abstract
Probabilistic model checking (PMC) is a technique used for the specification and analysis of complex systems. It can be applied directly to biological systems which present these characteristics, including cell transport systems. These systems are structures responsible for exchanging ions through the plasma membrane. Their correct behavior is essential for animal cells, since changes on those are responsible for diseases. In this work, PMC is used to model and analyze the effects of the palytoxin toxin (PTX) interactions with one of these systems. Our model suggests that ATP could inhibit PTX action. Therefore, individuals with ATP deficiencies, such as in brain disorders, may be more susceptible to the toxin. We have also used heat maps to enhance the kinetic model, which is used to describe the system reactions. The map reveals unexpected situations, such as a frequent reaction between unlikely pump states, and hot spots such as likely states and reactions. This type of analysis provides a better understanding on how transmembrane ionic transport systems behave and may lead to the discovery and development of new drugs to treat diseases associated to their incorrect behavior.
Year
DOI
Venue
2013
10.1109/TCBB.2013.97
IEEE/ACM Trans. Comput. Biology Bioinform.
Keywords
Field
DocType
probabilistic model checking,cell energy reactions,correct behavior,palytoxin toxin,cell transport system,kinetic model,ptx action,palytoxin effects,atp deficiency,probabilistic model checking analysis,incorrect behavior,transmembrane ionic transport system,animal cell,sodium,sodium potassium pump,toxicology,computational modeling,ions,probability,systems biology,molecular biophysics,model checking,biochemistry,potassium,enzymes,positive ions,probabilistic logic
Palytoxin,Model checking,Biochemistry,Computer science,Biophysics,Na+/K+-ATPase,Systems biology,Cell,Transmembrane protein,Molecular biophysics,Bioinformatics,Probabilistic model checking
Journal
Volume
Issue
ISSN
10
6
1557-9964
Citations 
PageRank 
References 
0
0.34
11
Authors
4